Sentiment analysis,a cornerstone of natural language processing,has witnessed remarkable advancements driven by deep learning models which demonstrated impressive accuracy in discerning sentiment from text across vari...Sentiment analysis,a cornerstone of natural language processing,has witnessed remarkable advancements driven by deep learning models which demonstrated impressive accuracy in discerning sentiment from text across various domains.However,the deployment of such models in resource-constrained environments presents a unique set of challenges that require innovative solutions.Resource-constrained environments encompass scenarios where computing resources,memory,and energy availability are restricted.To empower sentiment analysis in resource-constrained environments,we address the crucial need by leveraging lightweight pre-trained models.These models,derived from popular architectures such as DistilBERT,MobileBERT,ALBERT,TinyBERT,ELECTRA,and SqueezeBERT,offer a promising solution to the resource limitations imposed by these environments.By distilling the knowledge from larger models into smaller ones and employing various optimization techniques,these lightweight models aim to strike a balance between performance and resource efficiency.This paper endeavors to explore the performance of multiple lightweight pre-trained models in sentiment analysis tasks specific to such environments and provide insights into their viability for practical deployment.展开更多
Dear Editor,This letter proposes a novel Nash bargaining solution-based multiobjective model predictive control(MPC)scheme to deal with the interaction force control and the path-following problem of the constrained i...Dear Editor,This letter proposes a novel Nash bargaining solution-based multiobjective model predictive control(MPC)scheme to deal with the interaction force control and the path-following problem of the constrained interactive robot.Considering the elastic interaction force model,a mechanical trade-off always exists between the interaction force and position,which means that neither force nor path following can satisfy their desired demands completely.Based on this consideration,two irreconcilable control specifications,the force object function and the position track object function,are proposed,and a new multi-objective MPC scheme is then designed.展开更多
No attempt has been made to date to model growth in girth of rubber tree （Hevea brasiliansis）. We evaluated the few widely used growth functions to identify the most parsimonious and biologically reasonable model fo...No attempt has been made to date to model growth in girth of rubber tree （Hevea brasiliansis）. We evaluated the few widely used growth functions to identify the most parsimonious and biologically reasonable model for describing the girth growth of young rubber trees based on an incomplete set of young age measurements. Monthly data for girth of immature trees （age 2 to 12 yearsi from two locations were sub- jected to modelling. Re-parameterized, unconstrained and constrained growth functions,of Richards （RM）, Gompertz （GM） and the monomo- lecular ＇model ^（MM） were fitted to data. Duration of growth was the firsf constraint introduced. In the stagel We attempted a population aver- age （PA） model to capture the trend in growth. The best PA model was fitted as a subject specific （SS） model. We used appropriate error vari- ance-covariance structure to account for correlation due to repeated measurements over time. Unconstrainecl functions underestimated the asymptotic maximum that did not reflective carrying capacity of the locations. Underestimafions were attributed to the partial set＇ of meas- urements made during the early growth phase of the trees. MM proved superior to RM and GM. In the randomcoefficient models, both Gf and Go appeared to be influenced by tree level effects. Inclusion of diagonal definite positive matrix removed the correlation between random effects. The results were similar at both locations. In the overall assessment MM appeared as the candidate model for studying the girth-age relationships in Hevea trees. Based on the fitted model we conclude that, in Hevea trees, growth rate is maintained at maximum value at to, then decreases until the final state at dG/dt 〉 0, resulting in yield curve with no period of accelerating growth. One physiological explanation is that photosynthetic activity in Hevea trees decreases as girth increases and constructive metabolism is larger than destructive metabolism.展开更多
The coal-bearing strata of the deep Upper Paleozoic in the GS Sag have high hydrocarbon potential. Because of the absence of seismic data, we use electromagnetic （MT） and gravity data jointly to delineate the distri...The coal-bearing strata of the deep Upper Paleozoic in the GS Sag have high hydrocarbon potential. Because of the absence of seismic data, we use electromagnetic （MT） and gravity data jointly to delineate the distribution of deep targets based on well logging and geological data. First, a preliminary geological model is established by using three-dimensional （3D） MT inversion results. Second, using the formation density and gravity anomalies, the preliminary geological model is modified by interactive inversion of the gravity data. Then, we conduct MT-constrained inversion based on the modified model to obtain an optimal geological model until the deviations at all stations are minimized. Finally, the geological model and a seismic profile in the middle of the sag is analysed. We determine that the deep reflections of the seismic profile correspond to the Upper Paleozoic that reaches thickness up to 800 m. The processing of field data suggests that the joint MT-gravity modeling and constrained inversion can reduce the multiple solutions for single geophysical data and thus improve the recognition of deep formations. The MT-constrained inversion is consistent with the geological features in the seismic section. This suggests that the joint MT and gravity modeling and constrained inversion can be used to delineate deep targets in similar basins.展开更多
In transonic wind tunnel tests,the pulsating airflow is prone to induce the first order resonance of the sting support system.The resonance limits the wind tunnel test envelope,makes the test data inaccurate,and bring...In transonic wind tunnel tests,the pulsating airflow is prone to induce the first order resonance of the sting support system.The resonance limits the wind tunnel test envelope,makes the test data inaccurate,and brings potential security risks.In this paper,a model support sting with constrained layer damping(CLD)treatment is proposed to reduce the first order resonance response.The CLD treatment mainly consists of material selection and geometric optimization processes.The damping performance of the optimized CLD sting is compared with an AISI 1045 steel sting with the identical diameter in laboratory.The frequency response curves of the CLD sting support system and the AISI 1045 steel sting support system are obtained by sine sweep tests.The test results show that the first order resonance response of the CLD sting support system is 37.3%of that of the AISI 1045 steel sting support system.The first order damping ratios are calculated from the frequency response curves by half power point method.It is found that the first order damping ratio of the CLD sting support system is approximately 2.6 times that of the AISI 1045 steel sting support system.展开更多
Trust region methods are powerful and effective optimization methods. The conic model method is a new type of method with more information available at each iteration than standard quadratic-based methods. The adva...Trust region methods are powerful and effective optimization methods. The conic model method is a new type of method with more information available at each iteration than standard quadratic-based methods. The advantages of the above two methods can be combined to form a more powerful method for constrained optimization. The trust region subproblem of our method is to minimize a conic function subject to the linearized constraints and trust region bound. At the same time, the new algorithm still possesses robust global properties. The global convergence of the new algorithm under standard conditions is established.展开更多
A detailed knowledge of the thickness of the lithosphere in the North China craton（NCC） is important for understanding the significant tectonic reactivation of the craton in Mesozoic and Ce-nozoic.We achieve this go...A detailed knowledge of the thickness of the lithosphere in the North China craton（NCC） is important for understanding the significant tectonic reactivation of the craton in Mesozoic and Ce-nozoic.We achieve this goal by applying the newly proposed continuous wavelet transform theory to the Gravity Field Model（EGM 2008） data in the region.Distinct structural variations are identified in the scalogram image of profile Alxa-Datong（大同）-Qingdao（青岛）-Yellow Sea（profile ABC）,trans-versing the main units of NCC,which we interpret as mainly representing the Moho and lithosphere-asthenosphere boundary（LAB） undulations.The imaged LAB is as shallow as 60-70 km in the south-east basin and coastal areas and deepens to no more than 140 km in the northwest mountain ranges and continental interior.A rapid change of about 30 km in the LAB depth was detected at around the boundary between the Bohai（渤海） Bay basin（BBB） and the Taihang（太行） Mountains（TM）,roughly coincident with the distinct gravity decrease of more than 100 mGal that marks the North-South Grav-ity Lineament（NSGL） in the region.At last we present the gravity modeling work based on the spectral analysis results,incorporating with the observations on high-resolution seismic images and surface to-pography.The observed structural differences between the eastern and western NCC are likely associ-ated with different lithospheric tectonics across the NSGL.Combined with seismic tomography results and geochemical and petrological data,this sug-gests that complex modification of the litho-sphere probably accompanied significant litho-spheric thinning during the tectonic reactivation of the old craton.展开更多
Three dimensional (3D) microscopic distributions of dolomite and calcite in a limestone sample have been analyzed with a data-constrained modeling (DCM) technique using synchrotron radiation-based multi-energy X-ray c...Three dimensional (3D) microscopic distributions of dolomite and calcite in a limestone sample have been analyzed with a data-constrained modeling (DCM) technique using synchrotron radiation-based multi-energy X-ray computed tomography (CT) data as constraints. In order to optimize the experimental parameters, X-ray CT simulations and DCM analysis of a numerical phantom consisting of calcite (CaCO3) and dolomite (CaMg(CO3)2) have been used to investigate the effects on the predicted results in relation to noise, X-ray energy and sample-to-detector distance (SDD). The simulation results indicate that the optimal X-ray energies are 25 and 35 keVs, and the SDD is 10 mm. The high resolution 3D distributions of mineral phases of a natural limestone have been obtained. The results are useful for quantitative understanding of mineral, porosity, and physical property distributions in relation to oil and gas reservoirs hosted in carbonate rocks, which account for more than half of the world’s conventional hydrocarbon resources. The case studied is also instructive for the applicability of the DCM methods for other types of composite materials with modest atomic number contrasts between the mineral phases.展开更多
With an increase in model resolution,compact high-order numerical advection scheme can improve its effectiveness and competitiveness in oceanic modeling due to its high accuracy and scalability on massive-processor co...With an increase in model resolution,compact high-order numerical advection scheme can improve its effectiveness and competitiveness in oceanic modeling due to its high accuracy and scalability on massive-processor computers.To provide high-quality numerical ocean simulation on overset grids,we tried a novel formulation of the fourth-order multi-moment constrained finite volume scheme to simulate continuous and discontinuous problems in the Cartesian coordinate.Utilizing some degrees of freedom over each cell and derivatives at the cell center,we obtained a two-dimensional(2D)cubic polynomial from which point values on the extended overlap can achieve fourth-order accuracy.However,this interpolation causes a lack of conservation because the flux between the regions are no longer equal;thus,a flux correction is implemented to ensure conservation.A couple of numerical experiments are presented to evaluate the numerical scheme,which confirms its approximately fourth-order accuracy in conservative transportation on overset grid.The test cases reveal that the scheme is effective to suppress numerical oscillation in discontinuous problems,which may be powerful for salinity advection computing with a sharp gradient.展开更多
Most of the current evolutionary algorithms for constrained optimization algorithm are low computational efficiency. In order to improve efficiency, an improved differential evolution with shrinking space technique an...Most of the current evolutionary algorithms for constrained optimization algorithm are low computational efficiency. In order to improve efficiency, an improved differential evolution with shrinking space technique and adaptive trade-off model, named ATMDE, is proposed to solve constrained optimization problems. The proposed ATMDE algorithm employs an improved differential evolution as the search optimizer to generate new offspring individuals into evolutionary population. For the con- straints, the adaptive trade-off model as one of the most important constraint-handling techniques is employed to select better individuals to retain into the next population, which could effectively handle multiple constraints. Then the shrinking space technique is designed to shrink the search region according to feedback information in order to improve computational efficiency without losing accuracy. The improved DE algorithm introduces three different mutant strategies to generate different offspring into evo- lutionary population. Moreover, a new mutant strategy called ＂DE/rand/best/l＂ is constructed to generate new individuals according to the feasibility proportion ofcurrent population. Finally, the effectiveness of the pro- posed method is verified by a suite of benchmark functions and practical engineering problems. This research presents a constrained evolutionary algorithm with high efficiency and accuracy for constrained optimization problems.展开更多
This work is concerned with identification and nonlinear predictive control method for MIMO Hammerstein systems with constraints. Firstly, an identification method based on steady-state responses and sub-model method ...This work is concerned with identification and nonlinear predictive control method for MIMO Hammerstein systems with constraints. Firstly, an identification method based on steady-state responses and sub-model method is introduced to MIMO Hammerstein system. A modified version of artificial bee colony algorithm is proposed to improve the prediction ability of Hammerstein model. Next, a computationally efficient nonlinear model predictive control algorithm(MGPC) is developed to deal with constrained problem of MIMO system. The identification process and performance of MGPC are shown. Numerical results about a polymerization reactor validate the effectiveness of the proposed method and the comparisons show that MGPC has a better performance than QDMC and basic GPC.展开更多
Background： Measurements of tree heights and diameters are essential in forest assessment and modelling. Tree heights are used for estimating timber volume, site index and other important variables related to forest ...Background： Measurements of tree heights and diameters are essential in forest assessment and modelling. Tree heights are used for estimating timber volume, site index and other important variables related to forest growth and yield, succession and carbon budget models. However, the diameter at breast height （dbh） can be more accurately obtained and at lower cost, than total tree height. Hence, generalized height-diameter （h-d） models that predict tree height from dbh, age and other covariates are needed. For a more flexible but biologically plausible estimation of covariate effects we use shape constrained generalized additive models as an extension of existing h-d model approaches. We use causal site parameters such as index of aridity to enhance the generality and causality of the models and to enable predictions under projected changeable climatic conditions. Methods： We develop unconstrained generalized additive models （GAM） and shape constrained generalized additive models （SCAM） for investigating the possible effects of tree-specific parameters such as tree age, relative diameter at breast height, and site-specific parameters such as index of aridity and sum of daily mean temperature during vegetation period, on the h-d relationship of forests in Lower Saxony, Germany. Results： Some of the derived effects, e.g. effects of age, index of aridity and sum of daily mean temperature have significantly non-linear pattern. The need for using SCAM results from the fact that some of the model effects show partially implausible patterns especially at the boundaries of data ranges. The derived model predicts monotonically increasing levels of tree height with increasing age and temperature sum and decreasing aridity and social rank of a tree within a stand, The definition of constraints leads only to marginal or minor decline in the model statistics like AIC An observed structured spatial trend in tree height is modelled via 2-dimensional surface fitting. Conclusions： We demonstrate that the SCAM approach allows optimal regression modelling flexibility similar to the standard GAM but with the additional possibility of defining specific constraints for the model effects. The longitudinal character of the model allows for tree height imputation for the current status of forests but also for future tree height prediction.展开更多
A decentralized adaptive neural network sliding mode position/force control scheme is proposed for constrained reconfigurable manipulators. Different from the decentralized control strategy in multi-manipulator cooper...A decentralized adaptive neural network sliding mode position/force control scheme is proposed for constrained reconfigurable manipulators. Different from the decentralized control strategy in multi-manipulator cooperation, the proposed decentralized position/force control scheme can be applied to series constrained reconfigurable manipulators. By multiplying each row of Jacobian matrix in the dynamics by contact force vector, the converted joint torque is obtained. Furthermore, using desired information of other joints instead of their actual values, the dynamics can be represented as a set of interconnected subsystems by model decomposition technique. An adaptive neural network controller is introduced to approximate the unknown dynamics of subsystem. The interconnection and the whole error term are removed by employing an adaptive sliding mode term. And then, the Lyapunov stability theory guarantees the stability of the closed-loop system. Finally, two reconfigurable manipulators with different configurations are employed to show the effectiveness of the proposed decentralized position/force control scheme.展开更多
Background： Generalized height-diameter curves based on a re-parameterized version of the Korf function for Norway spruce （Piceo abies （L.） Karst.）, Scots pine （Pinus sylvestris L.） and silver birch （Betula pe...Background： Generalized height-diameter curves based on a re-parameterized version of the Korf function for Norway spruce （Piceo abies （L.） Karst.）, Scots pine （Pinus sylvestris L.） and silver birch （Betula pendula Roth） in Norwa are presented. The Norwegian National Forest Inventory （NFI） is used as data base for estimating the model parameters. The derived models are developed to enable spatially explicit and site sensitive tree height imputatio in forest inventories as well as future tree height predictions in growth and yield scenario simulations. Methods： Generalized additive mixed models （gamm） are employed to detect and quantify potentially non-linear effects of predictor variables. In doing so the quadratic mean diameter serves as longitudinal covariate since stand ag as measured in the NFI, shows only a weak correlation with a stands developmental status in Norwegian forests. Additionally the models can be locally calibrated by predicting random effects if measured height-diameter pairs are available. Based on the model selection of non-constraint models, shape constraint additive models （scare） were fit tc incorporate expert knowledge and intrinsic relationships by enforcing certain effect patterns like monotonicity. Results： Model comparisons demonstrate that the shape constraints lead to only marginal differences in statistical characteristics but ensure reasonable model predictions. Under constant constraints the developed models predict increasing tree heights with decreasing altitude, increasing soil depth and increasing competition pressure of a tree. / two-dimensional spatially structured effect of UTM-coordinates accounts for the potential effects of large scale spatial correlated covariates, which were not at our disposal. The main result of modelling the spatially structured effect is lower tree height prediction for coastal sites and with increasing latitude. The quadratic mean diameter affects both the level and the slope of the height-diameter curve and both effects are positive. Conclusions： In this investigation it is assumed that model effects in additive modelling of height-diameter curves which are unfeasible and too wiggly from an expert point of view are a result of quantitatively or qualitatively limited data bases. However, this problem can be regarded not to be specific to our investigation but more general since growth and yield data that are balanced over the whole data range with respect to all combinations of predictor variables are exceptional cases. Hence, scare may provide methodological improvements in several applications by combining the flexibility of additive models with expert knowledge.展开更多
Electromechanical actuators are widely used in many industrial applications. There are usually some constraints existing in a designed system. This paper proposes a simple method to design constrained controllers for ...Electromechanical actuators are widely used in many industrial applications. There are usually some constraints existing in a designed system. This paper proposes a simple method to design constrained controllers for electromechanical actuators. The controllers merge the ideas exploited in internal model control and model predictive control. They are designed using the standard control system structure with unity negative feedback. The structure of the controllers is relatively simple as well as the design process. The output constraint handling mechanism is based on prediction of the control plant behavior many time steps ahead. The mechanism increases control performance and safety of the control plant. The benefits offered by the proposed controllers have been demonstrated in real-life experiments carried out in control systems of two electromechanical actuators： a DC motor and an electrohydraulic actuator.展开更多
Tapered ring with thin wall and three high ribs(TRTWTHR),showing complicated geometry(wall thickness is less than 4 mm and rib height exceeds 20 mm),is extensively utilized to fabricate the critical structural parts o...Tapered ring with thin wall and three high ribs(TRTWTHR),showing complicated geometry(wall thickness is less than 4 mm and rib height exceeds 20 mm),is extensively utilized to fabricate the critical structural parts of aerospace equipment such as spacecraft cabin,rocket body and fuel tank because of light weight and high carrying capacity.How to fabricate TRTWTHR with high performance is a critical problem that aerospace area needs to solve.In this work,constraining ring rolling(CRR)technique is first adopted to form TRTWTHR.However.unreasonable metal streamlines(UMS)and uncoordinated growth of three ribs easily occur in CRR of TRTWTHR,which makes the forming quality of TRTWTHR difficult to be controlled.Faced with this difficulty,an analytical model that can predict UMS and the height of three ribs in CRR of TRTWTHR is established so as to guide the process design of CRR.Subsequently,the reliability of the established analytical model and the feasibility of CRR of TRTWTHR are confirmed by FE simulation and experiment.Then,using the established analytical model,the window of UMS occurring relevant to the tapered angle of TRTWTHR and the location of the rib of middle end is developed.Finally,three uncoordinated growth modes among three ribs are found when the width of three ribs is identical and UMS do not occur,and the mechanisms of three uncoordinated growth modes are revealed.展开更多
This paper addresses an uncertain nonlinear control system problem with complex state constraints and mismatched uncertainties.A novel Gaussian Mixture Model(GMM)based adaptive PID-Nonsingular Terminal Sliding Mode Co...This paper addresses an uncertain nonlinear control system problem with complex state constraints and mismatched uncertainties.A novel Gaussian Mixture Model(GMM)based adaptive PID-Nonsingular Terminal Sliding Mode Control(NTSMC)(GMM-adaptive-PID-NTSMC)method is proposed.It is achieved by combining a GMM based adaptive potential function with a novel switching surface of PID-NTSMC.Next,the stability of the closed-loop system is proved.The main contribution of this paper is that the GMM method is applied to obtain the analytic description of the complex bounded state constraints,ensuring that the states'constraints are not violated with GMM-based adaptive potential function.The developed potential function can consider the influence of uncertainties.More importantly,the GMM-adaptive-PID-NTSMC can be generalized to control a more representative class of uncertain nonlinear systems with constrained states and mismatched uncertainties.In addition,the proposed controller enhances the robustness,and requires less control cost and reduces the steady state error with respect to the Artificial Potential Function based Nonsingular Terminal Sliding Mode Control(APF-NTSMC),GMM-NTSMC and GMM-adaptive-NTSMC.At last,numerical simulation is performed to validate the superior performance of the proposed controller.展开更多
Aiming at a class of nonlinear systems with multiple equilibrium points, we present a dual-mode model predictive control algorithm with extended terminal constraint set combined with control invariant set and gain sch...Aiming at a class of nonlinear systems with multiple equilibrium points, we present a dual-mode model predictive control algorithm with extended terminal constraint set combined with control invariant set and gain schedule. Local LQR control laws and the corresponding maximum control invariant sets can be designed for finite equilibrium points. It is guaranteed that control invariant sets are overlapped each other. The union of the control invariant sets is treated as the terminal constraint set of predictive control. The feasibility and stability of the novel dual-mode model predictive control are investigated with both variable and fixed horizon. Because of the introduction of extended terminal constrained set, the feasibility of optimization can be guaranteed with short prediction horizon. In this way, the size of the optimization problem is reduced so it is computationally efficient. Finally, a simulation example illustrating the algorithm is presented.展开更多
To efficiently predict the mechanical parameters of granular soil based on its random micro-structure,this study proposed a novel approach combining numerical simulation and machine learning algorithms.Initially,3500 ...To efficiently predict the mechanical parameters of granular soil based on its random micro-structure,this study proposed a novel approach combining numerical simulation and machine learning algorithms.Initially,3500 simulations of one-dimensional compression tests on coarse-grained sand using the three-dimensional(3D)discrete element method(DEM)were conducted to construct a database.In this process,the positions of the particles were randomly altered,and the particle assemblages changed.Interestingly,besides confirming the influence of particle size distribution parameters,the stress-strain curves differed despite an identical gradation size statistic when the particle position varied.Subsequently,the obtained data were partitioned into training,validation,and testing datasets at a 7:2:1 ratio.To convert the DEM model into a multi-dimensional matrix that computers can recognize,the 3D DEM models were first sliced to extract multi-layer two-dimensional(2D)cross-sectional data.Redundant information was then eliminated via gray processing,and the data were stacked to form a new 3D matrix representing the granular soil’s fabric.Subsequently,utilizing the Python language and Pytorch framework,a 3D convolutional neural networks(CNNs)model was developed to establish the relationship between the constrained modulus obtained from DEM simulations and the soil’s fabric.The mean squared error(MSE)function was utilized to assess the loss value during the training process.When the learning rate(LR)fell within the range of 10-5e10-1,and the batch sizes(BSs)were 4,8,16,32,and 64,the loss value stabilized after 100 training epochs in the training and validation dataset.For BS?32 and LR?10-3,the loss reached a minimum.In the testing set,a comparative evaluation of the predicted constrained modulus from the 3D CNNs versus the simulated modulus obtained via DEM reveals a minimum mean absolute percentage error(MAPE)of 4.43%under the optimized condition,demonstrating the accuracy of this approach.Thus,by combining DEM and CNNs,the variation of soil’s mechanical characteristics related to its random fabric would be efficiently evaluated by directly tracking the particle assemblages.展开更多
文摘Sentiment analysis,a cornerstone of natural language processing,has witnessed remarkable advancements driven by deep learning models which demonstrated impressive accuracy in discerning sentiment from text across various domains.However,the deployment of such models in resource-constrained environments presents a unique set of challenges that require innovative solutions.Resource-constrained environments encompass scenarios where computing resources,memory,and energy availability are restricted.To empower sentiment analysis in resource-constrained environments,we address the crucial need by leveraging lightweight pre-trained models.These models,derived from popular architectures such as DistilBERT,MobileBERT,ALBERT,TinyBERT,ELECTRA,and SqueezeBERT,offer a promising solution to the resource limitations imposed by these environments.By distilling the knowledge from larger models into smaller ones and employing various optimization techniques,these lightweight models aim to strike a balance between performance and resource efficiency.This paper endeavors to explore the performance of multiple lightweight pre-trained models in sentiment analysis tasks specific to such environments and provide insights into their viability for practical deployment.
基金supported by the National Natural Science Foundation of China(62303095)the Natural Science Foundation of Sichuan Province(2023NSFSC0872).
文摘Dear Editor,This letter proposes a novel Nash bargaining solution-based multiobjective model predictive control(MPC)scheme to deal with the interaction force control and the path-following problem of the constrained interactive robot.Considering the elastic interaction force model,a mechanical trade-off always exists between the interaction force and position,which means that neither force nor path following can satisfy their desired demands completely.Based on this consideration,two irreconcilable control specifications,the force object function and the position track object function,are proposed,and a new multi-objective MPC scheme is then designed.
文摘No attempt has been made to date to model growth in girth of rubber tree （Hevea brasiliansis）. We evaluated the few widely used growth functions to identify the most parsimonious and biologically reasonable model for describing the girth growth of young rubber trees based on an incomplete set of young age measurements. Monthly data for girth of immature trees （age 2 to 12 yearsi from two locations were sub- jected to modelling. Re-parameterized, unconstrained and constrained growth functions,of Richards （RM）, Gompertz （GM） and the monomo- lecular ＇model ^（MM） were fitted to data. Duration of growth was the firsf constraint introduced. In the stagel We attempted a population aver- age （PA） model to capture the trend in growth. The best PA model was fitted as a subject specific （SS） model. We used appropriate error vari- ance-covariance structure to account for correlation due to repeated measurements over time. Unconstrainecl functions underestimated the asymptotic maximum that did not reflective carrying capacity of the locations. Underestimafions were attributed to the partial set＇ of meas- urements made during the early growth phase of the trees. MM proved superior to RM and GM. In the randomcoefficient models, both Gf and Go appeared to be influenced by tree level effects. Inclusion of diagonal definite positive matrix removed the correlation between random effects. The results were similar at both locations. In the overall assessment MM appeared as the candidate model for studying the girth-age relationships in Hevea trees. Based on the fitted model we conclude that, in Hevea trees, growth rate is maintained at maximum value at to, then decreases until the final state at dG/dt 〉 0, resulting in yield curve with no period of accelerating growth. One physiological explanation is that photosynthetic activity in Hevea trees decreases as girth increases and constructive metabolism is larger than destructive metabolism.
基金supported by the National Science and Technology Major Project(No.2016ZX05018006)the National Key Research Development Program(No.2016YFC0601104)the National Natural Science Foundation of China(No.41472136)
文摘The coal-bearing strata of the deep Upper Paleozoic in the GS Sag have high hydrocarbon potential. Because of the absence of seismic data, we use electromagnetic （MT） and gravity data jointly to delineate the distribution of deep targets based on well logging and geological data. First, a preliminary geological model is established by using three-dimensional （3D） MT inversion results. Second, using the formation density and gravity anomalies, the preliminary geological model is modified by interactive inversion of the gravity data. Then, we conduct MT-constrained inversion based on the modified model to obtain an optimal geological model until the deviations at all stations are minimized. Finally, the geological model and a seismic profile in the middle of the sag is analysed. We determine that the deep reflections of the seismic profile correspond to the Upper Paleozoic that reaches thickness up to 800 m. The processing of field data suggests that the joint MT-gravity modeling and constrained inversion can reduce the multiple solutions for single geophysical data and thus improve the recognition of deep formations. The MT-constrained inversion is consistent with the geological features in the seismic section. This suggests that the joint MT and gravity modeling and constrained inversion can be used to delineate deep targets in similar basins.
基金supported by Fenglei Youth Innovation Fund of China Aerodynamics Research&Development Center(PJD20180189)Shandong Provincial Natural Science Foundation of China(2019JMRH0307)supported by grants from Shandong University and Taishan Scholar Foundation。
文摘In transonic wind tunnel tests,the pulsating airflow is prone to induce the first order resonance of the sting support system.The resonance limits the wind tunnel test envelope,makes the test data inaccurate,and brings potential security risks.In this paper,a model support sting with constrained layer damping(CLD)treatment is proposed to reduce the first order resonance response.The CLD treatment mainly consists of material selection and geometric optimization processes.The damping performance of the optimized CLD sting is compared with an AISI 1045 steel sting with the identical diameter in laboratory.The frequency response curves of the CLD sting support system and the AISI 1045 steel sting support system are obtained by sine sweep tests.The test results show that the first order resonance response of the CLD sting support system is 37.3%of that of the AISI 1045 steel sting support system.The first order damping ratios are calculated from the frequency response curves by half power point method.It is found that the first order damping ratio of the CLD sting support system is approximately 2.6 times that of the AISI 1045 steel sting support system.
文摘Trust region methods are powerful and effective optimization methods. The conic model method is a new type of method with more information available at each iteration than standard quadratic-based methods. The advantages of the above two methods can be combined to form a more powerful method for constrained optimization. The trust region subproblem of our method is to minimize a conic function subject to the linearized constraints and trust region bound. At the same time, the new algorithm still possesses robust global properties. The global convergence of the new algorithm under standard conditions is established.
基金supported by the National Natural ScienceFoundation of China (Nos. 91014002,40821061)the SpecialFund for Basic Scientific Research of Central Colleges,China University of Geosciences (Wuhan) (No. CUGL100205)+1 种基金the Ph.D. Program Foundation of Ministry of Education of Chinafor Distinguished Young Scholars (No. 200804911523)the Ministry of Education of China (No. B07039)
文摘A detailed knowledge of the thickness of the lithosphere in the North China craton（NCC） is important for understanding the significant tectonic reactivation of the craton in Mesozoic and Ce-nozoic.We achieve this goal by applying the newly proposed continuous wavelet transform theory to the Gravity Field Model（EGM 2008） data in the region.Distinct structural variations are identified in the scalogram image of profile Alxa-Datong（大同）-Qingdao（青岛）-Yellow Sea（profile ABC）,trans-versing the main units of NCC,which we interpret as mainly representing the Moho and lithosphere-asthenosphere boundary（LAB） undulations.The imaged LAB is as shallow as 60-70 km in the south-east basin and coastal areas and deepens to no more than 140 km in the northwest mountain ranges and continental interior.A rapid change of about 30 km in the LAB depth was detected at around the boundary between the Bohai（渤海） Bay basin（BBB） and the Taihang（太行） Mountains（TM）,roughly coincident with the distinct gravity decrease of more than 100 mGal that marks the North-South Grav-ity Lineament（NSGL） in the region.At last we present the gravity modeling work based on the spectral analysis results,incorporating with the observations on high-resolution seismic images and surface to-pography.The observed structural differences between the eastern and western NCC are likely associ-ated with different lithospheric tectonics across the NSGL.Combined with seismic tomography results and geochemical and petrological data,this sug-gests that complex modification of the litho-sphere probably accompanied significant litho-spheric thinning during the tectonic reactivation of the old craton.
文摘Three dimensional (3D) microscopic distributions of dolomite and calcite in a limestone sample have been analyzed with a data-constrained modeling (DCM) technique using synchrotron radiation-based multi-energy X-ray computed tomography (CT) data as constraints. In order to optimize the experimental parameters, X-ray CT simulations and DCM analysis of a numerical phantom consisting of calcite (CaCO3) and dolomite (CaMg(CO3)2) have been used to investigate the effects on the predicted results in relation to noise, X-ray energy and sample-to-detector distance (SDD). The simulation results indicate that the optimal X-ray energies are 25 and 35 keVs, and the SDD is 10 mm. The high resolution 3D distributions of mineral phases of a natural limestone have been obtained. The results are useful for quantitative understanding of mineral, porosity, and physical property distributions in relation to oil and gas reservoirs hosted in carbonate rocks, which account for more than half of the world’s conventional hydrocarbon resources. The case studied is also instructive for the applicability of the DCM methods for other types of composite materials with modest atomic number contrasts between the mineral phases.
基金Dr.X.L.Li at the China Meteorological Administration.This study was supported by grants from the National Natural Science Foundation of China(Nos.41575103 and 91637210).
文摘With an increase in model resolution,compact high-order numerical advection scheme can improve its effectiveness and competitiveness in oceanic modeling due to its high accuracy and scalability on massive-processor computers.To provide high-quality numerical ocean simulation on overset grids,we tried a novel formulation of the fourth-order multi-moment constrained finite volume scheme to simulate continuous and discontinuous problems in the Cartesian coordinate.Utilizing some degrees of freedom over each cell and derivatives at the cell center,we obtained a two-dimensional(2D)cubic polynomial from which point values on the extended overlap can achieve fourth-order accuracy.However,this interpolation causes a lack of conservation because the flux between the regions are no longer equal;thus,a flux correction is implemented to ensure conservation.A couple of numerical experiments are presented to evaluate the numerical scheme,which confirms its approximately fourth-order accuracy in conservative transportation on overset grid.The test cases reveal that the scheme is effective to suppress numerical oscillation in discontinuous problems,which may be powerful for salinity advection computing with a sharp gradient.
基金Supported by National Science Foundation for Excellent Young Scholars,China(Grant No.51222502)Funds for Distinguished Young Scientists of Hunan Province,China(Grant No.14JJ1016)Major Program of National Natural Science Foundation of China(Grant No.51490662)
文摘Most of the current evolutionary algorithms for constrained optimization algorithm are low computational efficiency. In order to improve efficiency, an improved differential evolution with shrinking space technique and adaptive trade-off model, named ATMDE, is proposed to solve constrained optimization problems. The proposed ATMDE algorithm employs an improved differential evolution as the search optimizer to generate new offspring individuals into evolutionary population. For the con- straints, the adaptive trade-off model as one of the most important constraint-handling techniques is employed to select better individuals to retain into the next population, which could effectively handle multiple constraints. Then the shrinking space technique is designed to shrink the search region according to feedback information in order to improve computational efficiency without losing accuracy. The improved DE algorithm introduces three different mutant strategies to generate different offspring into evo- lutionary population. Moreover, a new mutant strategy called ＂DE/rand/best/l＂ is constructed to generate new individuals according to the feasibility proportion ofcurrent population. Finally, the effectiveness of the pro- posed method is verified by a suite of benchmark functions and practical engineering problems. This research presents a constrained evolutionary algorithm with high efficiency and accuracy for constrained optimization problems.
基金Projects(61573052,61273132)supported by the National Natural Science Foundation of China
文摘This work is concerned with identification and nonlinear predictive control method for MIMO Hammerstein systems with constraints. Firstly, an identification method based on steady-state responses and sub-model method is introduced to MIMO Hammerstein system. A modified version of artificial bee colony algorithm is proposed to improve the prediction ability of Hammerstein model. Next, a computationally efficient nonlinear model predictive control algorithm(MGPC) is developed to deal with constrained problem of MIMO system. The identification process and performance of MGPC are shown. Numerical results about a polymerization reactor validate the effectiveness of the proposed method and the comparisons show that MGPC has a better performance than QDMC and basic GPC.
文摘Background： Measurements of tree heights and diameters are essential in forest assessment and modelling. Tree heights are used for estimating timber volume, site index and other important variables related to forest growth and yield, succession and carbon budget models. However, the diameter at breast height （dbh） can be more accurately obtained and at lower cost, than total tree height. Hence, generalized height-diameter （h-d） models that predict tree height from dbh, age and other covariates are needed. For a more flexible but biologically plausible estimation of covariate effects we use shape constrained generalized additive models as an extension of existing h-d model approaches. We use causal site parameters such as index of aridity to enhance the generality and causality of the models and to enable predictions under projected changeable climatic conditions. Methods： We develop unconstrained generalized additive models （GAM） and shape constrained generalized additive models （SCAM） for investigating the possible effects of tree-specific parameters such as tree age, relative diameter at breast height, and site-specific parameters such as index of aridity and sum of daily mean temperature during vegetation period, on the h-d relationship of forests in Lower Saxony, Germany. Results： Some of the derived effects, e.g. effects of age, index of aridity and sum of daily mean temperature have significantly non-linear pattern. The need for using SCAM results from the fact that some of the model effects show partially implausible patterns especially at the boundaries of data ranges. The derived model predicts monotonically increasing levels of tree height with increasing age and temperature sum and decreasing aridity and social rank of a tree within a stand, The definition of constraints leads only to marginal or minor decline in the model statistics like AIC An observed structured spatial trend in tree height is modelled via 2-dimensional surface fitting. Conclusions： We demonstrate that the SCAM approach allows optimal regression modelling flexibility similar to the standard GAM but with the additional possibility of defining specific constraints for the model effects. The longitudinal character of the model allows for tree height imputation for the current status of forests but also for future tree height prediction.
基金Project(61374051,61603387)supported by the National Natural Science Foundation of ChinaProjects(20150520112JH,20160414033GH)supported by the Scientific and Technological Development Plan in Jilin Province of ChinaProject(20150102)supported by Opening Funding of State Key Laboratory of Management and Control for Complex Systems,China
文摘A decentralized adaptive neural network sliding mode position/force control scheme is proposed for constrained reconfigurable manipulators. Different from the decentralized control strategy in multi-manipulator cooperation, the proposed decentralized position/force control scheme can be applied to series constrained reconfigurable manipulators. By multiplying each row of Jacobian matrix in the dynamics by contact force vector, the converted joint torque is obtained. Furthermore, using desired information of other joints instead of their actual values, the dynamics can be represented as a set of interconnected subsystems by model decomposition technique. An adaptive neural network controller is introduced to approximate the unknown dynamics of subsystem. The interconnection and the whole error term are removed by employing an adaptive sliding mode term. And then, the Lyapunov stability theory guarantees the stability of the closed-loop system. Finally, two reconfigurable manipulators with different configurations are employed to show the effectiveness of the proposed decentralized position/force control scheme.
基金supported by the Norwegian Institute of Bioeconomy Research(NIBIO)
文摘Background： Generalized height-diameter curves based on a re-parameterized version of the Korf function for Norway spruce （Piceo abies （L.） Karst.）, Scots pine （Pinus sylvestris L.） and silver birch （Betula pendula Roth） in Norwa are presented. The Norwegian National Forest Inventory （NFI） is used as data base for estimating the model parameters. The derived models are developed to enable spatially explicit and site sensitive tree height imputatio in forest inventories as well as future tree height predictions in growth and yield scenario simulations. Methods： Generalized additive mixed models （gamm） are employed to detect and quantify potentially non-linear effects of predictor variables. In doing so the quadratic mean diameter serves as longitudinal covariate since stand ag as measured in the NFI, shows only a weak correlation with a stands developmental status in Norwegian forests. Additionally the models can be locally calibrated by predicting random effects if measured height-diameter pairs are available. Based on the model selection of non-constraint models, shape constraint additive models （scare） were fit tc incorporate expert knowledge and intrinsic relationships by enforcing certain effect patterns like monotonicity. Results： Model comparisons demonstrate that the shape constraints lead to only marginal differences in statistical characteristics but ensure reasonable model predictions. Under constant constraints the developed models predict increasing tree heights with decreasing altitude, increasing soil depth and increasing competition pressure of a tree. / two-dimensional spatially structured effect of UTM-coordinates accounts for the potential effects of large scale spatial correlated covariates, which were not at our disposal. The main result of modelling the spatially structured effect is lower tree height prediction for coastal sites and with increasing latitude. The quadratic mean diameter affects both the level and the slope of the height-diameter curve and both effects are positive. Conclusions： In this investigation it is assumed that model effects in additive modelling of height-diameter curves which are unfeasible and too wiggly from an expert point of view are a result of quantitatively or qualitatively limited data bases. However, this problem can be regarded not to be specific to our investigation but more general since growth and yield data that are balanced over the whole data range with respect to all combinations of predictor variables are exceptional cases. Hence, scare may provide methodological improvements in several applications by combining the flexibility of additive models with expert knowledge.
文摘Electromechanical actuators are widely used in many industrial applications. There are usually some constraints existing in a designed system. This paper proposes a simple method to design constrained controllers for electromechanical actuators. The controllers merge the ideas exploited in internal model control and model predictive control. They are designed using the standard control system structure with unity negative feedback. The structure of the controllers is relatively simple as well as the design process. The output constraint handling mechanism is based on prediction of the control plant behavior many time steps ahead. The mechanism increases control performance and safety of the control plant. The benefits offered by the proposed controllers have been demonstrated in real-life experiments carried out in control systems of two electromechanical actuators： a DC motor and an electrohydraulic actuator.
基金the National Natural Science Foundation of China (No. U2037204)the 111 Project (No. B17034)+1 种基金Innovative Research Team Development Program of Ministry of Education of China (No. IRT17R83)the National Natural Science Foundation of China (No. 52005375)
文摘Tapered ring with thin wall and three high ribs(TRTWTHR),showing complicated geometry(wall thickness is less than 4 mm and rib height exceeds 20 mm),is extensively utilized to fabricate the critical structural parts of aerospace equipment such as spacecraft cabin,rocket body and fuel tank because of light weight and high carrying capacity.How to fabricate TRTWTHR with high performance is a critical problem that aerospace area needs to solve.In this work,constraining ring rolling(CRR)technique is first adopted to form TRTWTHR.However.unreasonable metal streamlines(UMS)and uncoordinated growth of three ribs easily occur in CRR of TRTWTHR,which makes the forming quality of TRTWTHR difficult to be controlled.Faced with this difficulty,an analytical model that can predict UMS and the height of three ribs in CRR of TRTWTHR is established so as to guide the process design of CRR.Subsequently,the reliability of the established analytical model and the feasibility of CRR of TRTWTHR are confirmed by FE simulation and experiment.Then,using the established analytical model,the window of UMS occurring relevant to the tapered angle of TRTWTHR and the location of the rib of middle end is developed.Finally,three uncoordinated growth modes among three ribs are found when the width of three ribs is identical and UMS do not occur,and the mechanisms of three uncoordinated growth modes are revealed.
基金supported by the National Natural Science Foundation of China(Nos.61690210,61690213,12002383)。
文摘This paper addresses an uncertain nonlinear control system problem with complex state constraints and mismatched uncertainties.A novel Gaussian Mixture Model(GMM)based adaptive PID-Nonsingular Terminal Sliding Mode Control(NTSMC)(GMM-adaptive-PID-NTSMC)method is proposed.It is achieved by combining a GMM based adaptive potential function with a novel switching surface of PID-NTSMC.Next,the stability of the closed-loop system is proved.The main contribution of this paper is that the GMM method is applied to obtain the analytic description of the complex bounded state constraints,ensuring that the states'constraints are not violated with GMM-based adaptive potential function.The developed potential function can consider the influence of uncertainties.More importantly,the GMM-adaptive-PID-NTSMC can be generalized to control a more representative class of uncertain nonlinear systems with constrained states and mismatched uncertainties.In addition,the proposed controller enhances the robustness,and requires less control cost and reduces the steady state error with respect to the Artificial Potential Function based Nonsingular Terminal Sliding Mode Control(APF-NTSMC),GMM-NTSMC and GMM-adaptive-NTSMC.At last,numerical simulation is performed to validate the superior performance of the proposed controller.
基金Supported by National Natural Science Foundation of P. R. China (60474051, 60534020)Development Program of Shanghai Science and Technology Department (04DZ11008)the Program for New Century Excellent Talents in Universities of P. R. China (NCET)
文摘Aiming at a class of nonlinear systems with multiple equilibrium points, we present a dual-mode model predictive control algorithm with extended terminal constraint set combined with control invariant set and gain schedule. Local LQR control laws and the corresponding maximum control invariant sets can be designed for finite equilibrium points. It is guaranteed that control invariant sets are overlapped each other. The union of the control invariant sets is treated as the terminal constraint set of predictive control. The feasibility and stability of the novel dual-mode model predictive control are investigated with both variable and fixed horizon. Because of the introduction of extended terminal constrained set, the feasibility of optimization can be guaranteed with short prediction horizon. In this way, the size of the optimization problem is reduced so it is computationally efficient. Finally, a simulation example illustrating the algorithm is presented.
基金supported by the National Key R&D Program of China (Grant No.2022YFC3003401)the National Natural Science Foundation of China (Grant Nos.42041006 and 42377137).
文摘To efficiently predict the mechanical parameters of granular soil based on its random micro-structure,this study proposed a novel approach combining numerical simulation and machine learning algorithms.Initially,3500 simulations of one-dimensional compression tests on coarse-grained sand using the three-dimensional(3D)discrete element method(DEM)were conducted to construct a database.In this process,the positions of the particles were randomly altered,and the particle assemblages changed.Interestingly,besides confirming the influence of particle size distribution parameters,the stress-strain curves differed despite an identical gradation size statistic when the particle position varied.Subsequently,the obtained data were partitioned into training,validation,and testing datasets at a 7:2:1 ratio.To convert the DEM model into a multi-dimensional matrix that computers can recognize,the 3D DEM models were first sliced to extract multi-layer two-dimensional(2D)cross-sectional data.Redundant information was then eliminated via gray processing,and the data were stacked to form a new 3D matrix representing the granular soil’s fabric.Subsequently,utilizing the Python language and Pytorch framework,a 3D convolutional neural networks(CNNs)model was developed to establish the relationship between the constrained modulus obtained from DEM simulations and the soil’s fabric.The mean squared error(MSE)function was utilized to assess the loss value during the training process.When the learning rate(LR)fell within the range of 10-5e10-1,and the batch sizes(BSs)were 4,8,16,32,and 64,the loss value stabilized after 100 training epochs in the training and validation dataset.For BS?32 and LR?10-3,the loss reached a minimum.In the testing set,a comparative evaluation of the predicted constrained modulus from the 3D CNNs versus the simulated modulus obtained via DEM reveals a minimum mean absolute percentage error(MAPE)of 4.43%under the optimized condition,demonstrating the accuracy of this approach.Thus,by combining DEM and CNNs,the variation of soil’s mechanical characteristics related to its random fabric would be efficiently evaluated by directly tracking the particle assemblages.
