Purpose: In super-aging societies, prosthodontists will have a growing role and will need to improve their nutrition knowledge. This study aimed to evaluate the effectiveness of a workshop-based model for increasing d...Purpose: In super-aging societies, prosthodontists will have a growing role and will need to improve their nutrition knowledge. This study aimed to evaluate the effectiveness of a workshop-based model for increasing dysphagia diet awareness among prosthodontists working with head and neck cancer patients. Methods: The study had a post-intervention design and included 10 maxillofacial prosthetic educators from eight countries who participated in a 120-minute workshop focused on theoretical and practical training in nutrition support for patients with dysphagia. Sessions were held in a specialized restaurant in Tokyo and included lectures, observation of Japanese cooking techniques, hands-on preparation of dysphagia-friendly foods, and cross-cultural comparisons. Knowledge, confidence, and practical application were assessed using a post-workshop questionnaire. Descriptive statistics and thematic analysis were used to evaluate outcomes. Results: Seven of the 10 prosthodontists completed the post-intervention questionnaire. All respondents reported overall satisfaction with the workshop. Session content was regarded as easy to understand by 57.14%, appropriate by 28.57%, and easy by 14.29%. Most respondents (85.71%) were “very satisfied” with the instructors’ explanations, and 100% were “very satisfied” with the workshop’s length and structure;71.42% felt they could apply the knowledge in clinical practice, while 28.58% anticipated challenges. The respondents appreciated the workshop’s focus on dysphagia, particularly in elderly patients, and valued the insights into Japanese dysphagia diets and culture. Conclusions: Workshops on nutrition provide an interactive platform for prosthodontists to enhance their knowledge and improve comprehensive patient care, highlighting the importance for prosthodontists to stay updated on developments in nutrition, particularly in dysphagia.展开更多
Amidst the unique challenges faced by rural educators is their sense of decent work influenced by levels of social support,career self-efficacy,and marginalization.To investigate these relationships,we surveyed 435 ru...Amidst the unique challenges faced by rural educators is their sense of decent work influenced by levels of social support,career self-efficacy,and marginalization.To investigate these relationships,we surveyed 435 rural school teachers(females=69.32%,mean years teaching experience=13.6,SD=7.7 years).The Structural Equation Modeling results indicated that social support positively predicts teachers’perceptions of decent work.Career self-efficacy mediated the relationship between social support and a higher sense of decent work,while marginalization mediated the relationship such that lower social support predicted lower perceptions of decent work.Career self-efficacy and marginalization also had a sequential mediation relationship:higher social support enhanced career self-efficacy,which in turn reduced marginalization experiences,ultimately improving teachers’perceptions of decent work.These findings align with the predictions of Social Cognitive Career Theory and the Psychology of Working Theory,demonstrating that environmental supports enhance personal psychological resources,reduce marginalization risks,and promote positive work-related outcomes.The study findings highlight the necessity for education departments to improve rural teachers’perceptions of decent work by providing social support to foster positive work experiences for teachers at high risk for marginalization and diminished career self-efficacy.展开更多
To study the use of a shaft support for the auxiliary shaft of the Xi’anshan Iron Mine,in high-stress strata at a depth between 900 and 1000 m,a new type of mold was developed using the physical similarity model test...To study the use of a shaft support for the auxiliary shaft of the Xi’anshan Iron Mine,in high-stress strata at a depth between 900 and 1000 m,a new type of mold was developed using the physical similarity model test method,based on the similarity theory,and an experimental model of the shaft lining and surrounding rock was poured.Two sets of large-scale destructive tests were conducted on the shaft lining and surrounding rock.The deformation and failure laws of the shaft lining and surrounding rock under high ground stress and their ultimate horizontal bearing capacity characteristics were studied,and the safety support characteristics of the shaft lining under the interaction of the shaft lining and surrounding rock were obtained.An experimental study demonstrated that the axial pressure on the shaft wall directly affected its ultimate horizontal bearing capacity of the shaft wall.In designing the shaft wall,the influence of the axial pressure on the stress state of the concrete should be considered,and the vertical pressure should be modified to optimize the utilization of the three-dimensional compressive strength of the concrete.The reliability of the 400-mm C30 concrete shaft wall at a depth of 1000 m in the actual project was verified,and the ultimate horizontal bearing capacity of the shaft wall was obtained for a depth of 1000 m.展开更多
In order to estimate the readiness, sustainability and support capability of the operational unit, an support simulation concept model of the military equipment is given as viewed from the system engineering modeling ...In order to estimate the readiness, sustainability and support capability of the operational unit, an support simulation concept model of the military equipment is given as viewed from the system engineering modeling and simulation. Simulation test of military aircraft is analyzed in detail, it is composed of the operational mission, function maintenance process and resource modeling.展开更多
Abstract Accurate aerodynamic models are the basis of flight simulation and control law design. Mathematically modeling unsteady aerodynamics at high angles of attack bears great difficulties in model structure determ...Abstract Accurate aerodynamic models are the basis of flight simulation and control law design. Mathematically modeling unsteady aerodynamics at high angles of attack bears great difficulties in model structure determination and parameter estimation due to little understanding of the flow mechanism. Support vector machines （SVMs） based on statistical learning theory provide a novel tool for nonlinear system modeling. The work presented here examines the feasibility of applying SVMs to high angle.-of-attack unsteady aerodynamic modeling field. Mainly, after a review of SVMs, several issues associated with unsteady aerodynamic modeling by use of SVMs are discussed in detail, such as sele, ction of input variables, selection of output variables and determination of SVM parameters. The least squares SVM （LS-SVM） models are set up from certain dynamic wind tunnel test data of a delta wing and an aircraft configuration, and then used to predict the aerodynamic responses in other tests. The predictions are in good agreement with the test data, which indicates the satisfving learning and generalization performance of LS-SVMs.展开更多
The elastic support/dry friction damper is a type of damper which is used for active vibration control in a rotor system.To establish the analytical model of this type of damper,a two-dimensional friction model-ball/p...The elastic support/dry friction damper is a type of damper which is used for active vibration control in a rotor system.To establish the analytical model of this type of damper,a two-dimensional friction model-ball/plate model was proposed.By using this ball/plate model,a dynamics model of rotor with elastic support/dry friction dampers was established and experimentally verified.Moreover,the damping performance of the elastic support/dry friction damper was studied numerically with respect to some variable parameters.The numerical study shows that the damping performance of the elastic support/dry friction damper is closely related to the stiffness distribution of the rotor-support system,the damper location,the pressing force between the moving and stationary disk,the friction coefficient,the tangential contact stiffness of the contact interface,and the stiffness of the stationary disk.In general,the damper should be located on an elastic support which has a large vibration amplitude in order to achieve a better damping performance,and the more vibration energy in this elastic support concentrates,the better performance of the damper will be.The larger the tangential contact stiffness of the contact interface,and the stiffness of the stationary disk are,the better performance of the damper will be.There will be an optimal value of the friction force at which the damper performs best.展开更多
In this paper we apply the nonlinear time series analysis method to small-time scale traffic measurement data. The prediction-based method is used to determine the embedding dimension of the traffic data. Based on the...In this paper we apply the nonlinear time series analysis method to small-time scale traffic measurement data. The prediction-based method is used to determine the embedding dimension of the traffic data. Based on the reconstructed phase space, the local support vector machine prediction method is used to predict the traffic measurement data, and the BIC-based neighbouring point selection method is used to choose the number of the nearest neighbouring points for the local support vector machine regression model. The experimental results show that the local support vector machine prediction method whose neighbouring points are optimized can effectively predict the small-time scale traffic measurement data and can reproduce the statistical features of real traffic measurements.展开更多
Multi-kernel-based support vector machine （SVM） model structure of nonlinear systems and its specific identification method is proposed, which is composed of a SVM with linear kernel function followed in series by a...Multi-kernel-based support vector machine （SVM） model structure of nonlinear systems and its specific identification method is proposed, which is composed of a SVM with linear kernel function followed in series by a SVM with spline kernel function. With the help of this model, nonlinear model predictive control can be transformed to linear model predictive control, and consequently a unified analytical solution of optimal input of multi-step-ahead predictive control is possible to derive. This algorithm does not require online iterative optimization in order to be suitable for real-time control with less calculation. The simulation results of pH neutralization process and CSTR reactor show the effectiveness and advantages of the presented algorithm.展开更多
Soft sensor is widely used in industrial process control. It plays animportant role to improve the quality of product and assure safety in production. The core of softsensor is to construct soft sensing model. A new s...Soft sensor is widely used in industrial process control. It plays animportant role to improve the quality of product and assure safety in production. The core of softsensor is to construct soft sensing model. A new soft sensing modeling method based on supportvector machine (SVM) is proposed. SVM is a new machine learning method based on statistical learningtheory and is powerful for the problem characterized by small sample, nonlinearity, high dimensionand local minima. The proposed methods are applied to the estimation of frozen point of light dieseloil in distillation column. The estimated outputs of soft sensing model based on SVM match the realvalues of frozen point and follow varying trend of frozen point very well. Experiment results showthat SVM provides a new effective method for soft sensing modeling and has promising application inindustrial process applications.展开更多
By applying the system analysis principle and mathematical modeling technique to knowledge expression system for crop cultural management, the fundamental relationships and quantitative algorithms of wheat growth and ...By applying the system analysis principle and mathematical modeling technique to knowledge expression system for crop cultural management, the fundamental relationships and quantitative algorithms of wheat growth and management indices to variety types, ecological environments and production levels were analysed and extracted, and a dynamic knowledge model with temporal and spatial characters for wheat management(WheatKnow)was developed. By adopting the soft component characteristics as non language relevance , re-utilization and portable system maintenance. and by further integrating the wheat growth simulation model(WheatGrow)and intelligent system for wheat management, a comprehensive and digital knowledge model, growth model and component-based decision support system for wheat management(MBDSSWM)was established on the platforms of Visual C++ and Visual Basic. The MBDSSWM realized the effective integration and coupling of the prediction and decision-making functions for digital crop management.展开更多
Common,unsteady aerodynamic modeling methods usually use wind tunnel test data from forced vibration tests to predict stable hysteresis loop.However,these methods ignore the initial unstable process of entering the hy...Common,unsteady aerodynamic modeling methods usually use wind tunnel test data from forced vibration tests to predict stable hysteresis loop.However,these methods ignore the initial unstable process of entering the hysteresis loop that exists in the actual maneuvering process of the aircraft.Here,an excitation input suitable for nonlinear system identification is introduced to model unsteady aerodynamic forces with any motion in the amplitude and frequency ranges based on the Least Squares Support Vector Machines(LS-SVMs).In the selection of the input form,avoiding the use of reduced frequency as a parameter makes the model more universal.After model training is completed,the method is applied to predict the lift coefficient,drag coefficient and pitching moment coefficient of the RAE2822 airfoil,in sine and sweep motions under the conditions of plunging and pitching at Mach number 0.8.The predicted results of the initial unstable process and the final stable process are in close agreement with the Computational Fluid Dynamics(CFD)data,demonstrating the feasibility of the model for nonlinear unsteady aerodynamics modeling and the effectiveness of the input design approach.展开更多
A support vector machine with guadratic polynomial kernel function based nonlinear model multi-step-ahead optimizing predictive controller was presented. A support vector machine based predictive model was established...A support vector machine with guadratic polynomial kernel function based nonlinear model multi-step-ahead optimizing predictive controller was presented. A support vector machine based predictive model was established by black-box identification. And a quadratic objective function with receding horizon was selected to obtain the controller output. By solving a nonlinear optimization problem with equality constraint of model output and boundary constraint of controller output using Nelder-Mead simplex direct search method, a sub-optimal control law was achieved in feature space. The effect of the controller was demonstrated on a recognized benchmark problem and a continuous-stirred tank reactor. The simulation results show that the multi-step-ahead predictive controller can be well applied to nonlinear system, with better performance in following reference trajectory and disturbance-rejection.展开更多
Aiming at solving the problems of machine-learning in fault diagnosis,a diagnosis approach is proposed based on hidden Markov model(HMM)and support vector machine(SVM).HMM usually describes intra-class measure well an...Aiming at solving the problems of machine-learning in fault diagnosis,a diagnosis approach is proposed based on hidden Markov model(HMM)and support vector machine(SVM).HMM usually describes intra-class measure well and is good at dealing with continuous dynamic signals.SVM expresses inter-class difference effectively and has perfect classify ability.This approach is built on the merit of HMM and SVM.Then,the experiment is made in the transmission system of a helicopter.With the features extracted from vibration signals in gearbox,this HMM-SVM based diagnostic approach is trained and used to monitor and diagnose the gearbox's faults.The result shows that this method is better than HMM-based and SVM-based diagnosing methods in higher diagnostic accuracy with small training samples.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
In this paper, we present a novel Support Vector Machine active learning algorithm for effective 3D model retrieval using the concept of relevance feedback. The proposed method learns from the most informative objects...In this paper, we present a novel Support Vector Machine active learning algorithm for effective 3D model retrieval using the concept of relevance feedback. The proposed method learns from the most informative objects which are marked by the user, and then creates a boundary separating the relevant models from irrelevant ones. What it needs is only a small number of 3D models labelled by the user. It can grasp the user＇s semantic knowledge rapidly and accurately. Experimental results showed that the proposed algorithm significantly improves the retrieval effectiveness. Compared with four state-of-the-art query refinement schemes for 3D model retrieval, it provides superior retrieval performance after no more than two rounds of relevance feedback.展开更多
Hydrological models are often linked with other models in cognate sciences to understand the interactions among climate, earth, water, ecosystem, and human society. This paper presents the development and implementati...Hydrological models are often linked with other models in cognate sciences to understand the interactions among climate, earth, water, ecosystem, and human society. This paper presents the development and implementation of a decision support system（DSS） that links the outputs of hydrological models with real-time decision making on social-economic assessments and land use management. Discharge and glacier geometry changes were simulated with hydrological model, water availability in semiarid environments. Irrigation and ecological water were simulated by a new commercial software MIKE HYDRO. Groundwater was simulated by MODFLOW. All the outputs of theses hydrological models were taken as inputs into the DSS in three types of links： regression equations, stationary data inputs, or dynamic data inputs as the models running parallel in the simulation periods. The DSS integrates the hydrological data, geographic data, social and economic statistical data, and establishes the relationships with equations, conditional statements and fuzzy logics. The programming is realized in C＋＋. The DSS has four remarkable features：（1） editable land use maps to assist decision-making;（2） conjunctive use of surface and groundwater resources;（3） interactions among water, earth, ecosystem, and humans; and（4） links with hydrological models. The overall goal of the DSS is to combine the outputs of scientific models, knowledge of experts, and perspectives of stakeholders, into a computer-based system, which allows sustainability impact assessment within regional planning; and to understand ecosystem services and integrate them into land and water management.展开更多
As optimization of parameters affects prediction accuracy and generalization ability of support vector regression(SVR) greatly and the predictive model often mismatches nonlinear system model predictive control,a mult...As optimization of parameters affects prediction accuracy and generalization ability of support vector regression(SVR) greatly and the predictive model often mismatches nonlinear system model predictive control,a multi-step model predictive control based on online SVR(OSVR) optimized by multi-agent particle swarm optimization algorithm(MAPSO) is put forward. By integrating the online learning ability of OSVR, the predictive model can self-correct and adapt to the dynamic changes in nonlinear process well.展开更多
Robustly stable multi-step-ahead model predictive control (MPC) based on parallel support vector machines (SVMs) with linear kernel was proposed. First, an analytical solution of optimal control laws of parallel SVMs ...Robustly stable multi-step-ahead model predictive control (MPC) based on parallel support vector machines (SVMs) with linear kernel was proposed. First, an analytical solution of optimal control laws of parallel SVMs based MPC was derived, and then the necessary and sufficient stability condition for MPC closed loop was given according to SVM model, and finally a method of judging the discrepancy between SVM model and the actual plant was presented, and consequently the constraint sets, which can guarantee that the stability condition is still robust for model/plant mismatch within some given bounds, were obtained by applying small-gain theorem. Simulation experiments show the proposed stability condition and robust constraint sets can provide a convenient way of adjusting controller parameters to ensure a closed-loop with larger stable margin.展开更多
This paper proposed a semi-supervised regression model with co-training algorithm based on support vector machine, which was used for retrieving water quality variables from SPOT 5 remote sensing data. The model consi...This paper proposed a semi-supervised regression model with co-training algorithm based on support vector machine, which was used for retrieving water quality variables from SPOT 5 remote sensing data. The model consisted of two support vector regressors (SVRs). Nonlinear relationship between water quality variables and SPOT 5 spectrum was described by the two SVRs, and semi-supervised co-training algorithm for the SVRs was es-tablished. The model was used for retrieving concentrations of four representative pollution indicators―permangan- ate index (CODmn), ammonia nitrogen (NH3-N), chemical oxygen demand (COD) and dissolved oxygen (DO) of the Weihe River in Shaanxi Province, China. The spatial distribution map for those variables over a part of the Weihe River was also produced. SVR can be used to implement any nonlinear mapping readily, and semi-supervis- ed learning can make use of both labeled and unlabeled samples. By integrating the two SVRs and using semi-supervised learning, we provide an operational method when paired samples are limited. The results show that it is much better than the multiple statistical regression method, and can provide the whole water pollution condi-tions for management fast and can be extended to hyperspectral remote sensing applications.展开更多
A new multiple models(MM) approach was proposed to model complex industrial process by using Fuzzy Support Vector Machines(F -SVMs). By applying the proposed approach to a pH neutralization titration experiment, F -SV...A new multiple models(MM) approach was proposed to model complex industrial process by using Fuzzy Support Vector Machines(F -SVMs). By applying the proposed approach to a pH neutralization titration experiment, F -SVMs MM not only provides satisfactory approximation and generalization property, but also achieves superior performance to USOCPN multiple modeling method and single modeling method based on standard SVMs.展开更多
文摘Purpose: In super-aging societies, prosthodontists will have a growing role and will need to improve their nutrition knowledge. This study aimed to evaluate the effectiveness of a workshop-based model for increasing dysphagia diet awareness among prosthodontists working with head and neck cancer patients. Methods: The study had a post-intervention design and included 10 maxillofacial prosthetic educators from eight countries who participated in a 120-minute workshop focused on theoretical and practical training in nutrition support for patients with dysphagia. Sessions were held in a specialized restaurant in Tokyo and included lectures, observation of Japanese cooking techniques, hands-on preparation of dysphagia-friendly foods, and cross-cultural comparisons. Knowledge, confidence, and practical application were assessed using a post-workshop questionnaire. Descriptive statistics and thematic analysis were used to evaluate outcomes. Results: Seven of the 10 prosthodontists completed the post-intervention questionnaire. All respondents reported overall satisfaction with the workshop. Session content was regarded as easy to understand by 57.14%, appropriate by 28.57%, and easy by 14.29%. Most respondents (85.71%) were “very satisfied” with the instructors’ explanations, and 100% were “very satisfied” with the workshop’s length and structure;71.42% felt they could apply the knowledge in clinical practice, while 28.58% anticipated challenges. The respondents appreciated the workshop’s focus on dysphagia, particularly in elderly patients, and valued the insights into Japanese dysphagia diets and culture. Conclusions: Workshops on nutrition provide an interactive platform for prosthodontists to enhance their knowledge and improve comprehensive patient care, highlighting the importance for prosthodontists to stay updated on developments in nutrition, particularly in dysphagia.
文摘Amidst the unique challenges faced by rural educators is their sense of decent work influenced by levels of social support,career self-efficacy,and marginalization.To investigate these relationships,we surveyed 435 rural school teachers(females=69.32%,mean years teaching experience=13.6,SD=7.7 years).The Structural Equation Modeling results indicated that social support positively predicts teachers’perceptions of decent work.Career self-efficacy mediated the relationship between social support and a higher sense of decent work,while marginalization mediated the relationship such that lower social support predicted lower perceptions of decent work.Career self-efficacy and marginalization also had a sequential mediation relationship:higher social support enhanced career self-efficacy,which in turn reduced marginalization experiences,ultimately improving teachers’perceptions of decent work.These findings align with the predictions of Social Cognitive Career Theory and the Psychology of Working Theory,demonstrating that environmental supports enhance personal psychological resources,reduce marginalization risks,and promote positive work-related outcomes.The study findings highlight the necessity for education departments to improve rural teachers’perceptions of decent work by providing social support to foster positive work experiences for teachers at high risk for marginalization and diminished career self-efficacy.
基金supported by the National Key Research and Development Program of China(No.2021YFB 3401500).
文摘To study the use of a shaft support for the auxiliary shaft of the Xi’anshan Iron Mine,in high-stress strata at a depth between 900 and 1000 m,a new type of mold was developed using the physical similarity model test method,based on the similarity theory,and an experimental model of the shaft lining and surrounding rock was poured.Two sets of large-scale destructive tests were conducted on the shaft lining and surrounding rock.The deformation and failure laws of the shaft lining and surrounding rock under high ground stress and their ultimate horizontal bearing capacity characteristics were studied,and the safety support characteristics of the shaft lining under the interaction of the shaft lining and surrounding rock were obtained.An experimental study demonstrated that the axial pressure on the shaft wall directly affected its ultimate horizontal bearing capacity of the shaft wall.In designing the shaft wall,the influence of the axial pressure on the stress state of the concrete should be considered,and the vertical pressure should be modified to optimize the utilization of the three-dimensional compressive strength of the concrete.The reliability of the 400-mm C30 concrete shaft wall at a depth of 1000 m in the actual project was verified,and the ultimate horizontal bearing capacity of the shaft wall was obtained for a depth of 1000 m.
文摘In order to estimate the readiness, sustainability and support capability of the operational unit, an support simulation concept model of the military equipment is given as viewed from the system engineering modeling and simulation. Simulation test of military aircraft is analyzed in detail, it is composed of the operational mission, function maintenance process and resource modeling.
文摘Abstract Accurate aerodynamic models are the basis of flight simulation and control law design. Mathematically modeling unsteady aerodynamics at high angles of attack bears great difficulties in model structure determination and parameter estimation due to little understanding of the flow mechanism. Support vector machines （SVMs） based on statistical learning theory provide a novel tool for nonlinear system modeling. The work presented here examines the feasibility of applying SVMs to high angle.-of-attack unsteady aerodynamic modeling field. Mainly, after a review of SVMs, several issues associated with unsteady aerodynamic modeling by use of SVMs are discussed in detail, such as sele, ction of input variables, selection of output variables and determination of SVM parameters. The least squares SVM （LS-SVM） models are set up from certain dynamic wind tunnel test data of a delta wing and an aircraft configuration, and then used to predict the aerodynamic responses in other tests. The predictions are in good agreement with the test data, which indicates the satisfving learning and generalization performance of LS-SVMs.
基金supported by the National Natural Science Foundation of China(No.51405393)
文摘The elastic support/dry friction damper is a type of damper which is used for active vibration control in a rotor system.To establish the analytical model of this type of damper,a two-dimensional friction model-ball/plate model was proposed.By using this ball/plate model,a dynamics model of rotor with elastic support/dry friction dampers was established and experimentally verified.Moreover,the damping performance of the elastic support/dry friction damper was studied numerically with respect to some variable parameters.The numerical study shows that the damping performance of the elastic support/dry friction damper is closely related to the stiffness distribution of the rotor-support system,the damper location,the pressing force between the moving and stationary disk,the friction coefficient,the tangential contact stiffness of the contact interface,and the stiffness of the stationary disk.In general,the damper should be located on an elastic support which has a large vibration amplitude in order to achieve a better damping performance,and the more vibration energy in this elastic support concentrates,the better performance of the damper will be.The larger the tangential contact stiffness of the contact interface,and the stiffness of the stationary disk are,the better performance of the damper will be.There will be an optimal value of the friction force at which the damper performs best.
基金Project supported by the National Natural Science Foundation of China (Grant No 60573065)the Natural Science Foundation of Shandong Province,China (Grant No Y2007G33)the Key Subject Research Foundation of Shandong Province,China(Grant No XTD0708)
文摘In this paper we apply the nonlinear time series analysis method to small-time scale traffic measurement data. The prediction-based method is used to determine the embedding dimension of the traffic data. Based on the reconstructed phase space, the local support vector machine prediction method is used to predict the traffic measurement data, and the BIC-based neighbouring point selection method is used to choose the number of the nearest neighbouring points for the local support vector machine regression model. The experimental results show that the local support vector machine prediction method whose neighbouring points are optimized can effectively predict the small-time scale traffic measurement data and can reproduce the statistical features of real traffic measurements.
基金Supported by the State Key Development Program for Basic Research of China （No.2002CB312200） and the National Natural Science Foundation of China （No.60574019）.
文摘Multi-kernel-based support vector machine （SVM） model structure of nonlinear systems and its specific identification method is proposed, which is composed of a SVM with linear kernel function followed in series by a SVM with spline kernel function. With the help of this model, nonlinear model predictive control can be transformed to linear model predictive control, and consequently a unified analytical solution of optimal input of multi-step-ahead predictive control is possible to derive. This algorithm does not require online iterative optimization in order to be suitable for real-time control with less calculation. The simulation results of pH neutralization process and CSTR reactor show the effectiveness and advantages of the presented algorithm.
基金This project is supported by Special Foundation for Major State Basic Research of China (No.G1998030415).
文摘Soft sensor is widely used in industrial process control. It plays animportant role to improve the quality of product and assure safety in production. The core of softsensor is to construct soft sensing model. A new soft sensing modeling method based on supportvector machine (SVM) is proposed. SVM is a new machine learning method based on statistical learningtheory and is powerful for the problem characterized by small sample, nonlinearity, high dimensionand local minima. The proposed methods are applied to the estimation of frozen point of light dieseloil in distillation column. The estimated outputs of soft sensing model based on SVM match the realvalues of frozen point and follow varying trend of frozen point very well. Experiment results showthat SVM provides a new effective method for soft sensing modeling and has promising application inindustrial process applications.
基金supported by the National Natural Science Foundation of China(30030090)the National 863 Program,China(2001AA115420,2001AA245041).
文摘By applying the system analysis principle and mathematical modeling technique to knowledge expression system for crop cultural management, the fundamental relationships and quantitative algorithms of wheat growth and management indices to variety types, ecological environments and production levels were analysed and extracted, and a dynamic knowledge model with temporal and spatial characters for wheat management(WheatKnow)was developed. By adopting the soft component characteristics as non language relevance , re-utilization and portable system maintenance. and by further integrating the wheat growth simulation model(WheatGrow)and intelligent system for wheat management, a comprehensive and digital knowledge model, growth model and component-based decision support system for wheat management(MBDSSWM)was established on the platforms of Visual C++ and Visual Basic. The MBDSSWM realized the effective integration and coupling of the prediction and decision-making functions for digital crop management.
文摘Common,unsteady aerodynamic modeling methods usually use wind tunnel test data from forced vibration tests to predict stable hysteresis loop.However,these methods ignore the initial unstable process of entering the hysteresis loop that exists in the actual maneuvering process of the aircraft.Here,an excitation input suitable for nonlinear system identification is introduced to model unsteady aerodynamic forces with any motion in the amplitude and frequency ranges based on the Least Squares Support Vector Machines(LS-SVMs).In the selection of the input form,avoiding the use of reduced frequency as a parameter makes the model more universal.After model training is completed,the method is applied to predict the lift coefficient,drag coefficient and pitching moment coefficient of the RAE2822 airfoil,in sine and sweep motions under the conditions of plunging and pitching at Mach number 0.8.The predicted results of the initial unstable process and the final stable process are in close agreement with the Computational Fluid Dynamics(CFD)data,demonstrating the feasibility of the model for nonlinear unsteady aerodynamics modeling and the effectiveness of the input design approach.
文摘A support vector machine with guadratic polynomial kernel function based nonlinear model multi-step-ahead optimizing predictive controller was presented. A support vector machine based predictive model was established by black-box identification. And a quadratic objective function with receding horizon was selected to obtain the controller output. By solving a nonlinear optimization problem with equality constraint of model output and boundary constraint of controller output using Nelder-Mead simplex direct search method, a sub-optimal control law was achieved in feature space. The effect of the controller was demonstrated on a recognized benchmark problem and a continuous-stirred tank reactor. The simulation results show that the multi-step-ahead predictive controller can be well applied to nonlinear system, with better performance in following reference trajectory and disturbance-rejection.
基金This project is supported by National Natural Science Foundation of China(No.50375153).
文摘Aiming at solving the problems of machine-learning in fault diagnosis,a diagnosis approach is proposed based on hidden Markov model(HMM)and support vector machine(SVM).HMM usually describes intra-class measure well and is good at dealing with continuous dynamic signals.SVM expresses inter-class difference effectively and has perfect classify ability.This approach is built on the merit of HMM and SVM.Then,the experiment is made in the transmission system of a helicopter.With the features extracted from vibration signals in gearbox,this HMM-SVM based diagnostic approach is trained and used to monitor and diagnose the gearbox's faults.The result shows that this method is better than HMM-based and SVM-based diagnosing methods in higher diagnostic accuracy with small training samples.
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.
基金the National Basic Research Program (973) of China (No. 2004CB719401)the National Research Foundation for the Doctoral Program of Higher Education of China (No.20060003060)
文摘In this paper, we present a novel Support Vector Machine active learning algorithm for effective 3D model retrieval using the concept of relevance feedback. The proposed method learns from the most informative objects which are marked by the user, and then creates a boundary separating the relevant models from irrelevant ones. What it needs is only a small number of 3D models labelled by the user. It can grasp the user＇s semantic knowledge rapidly and accurately. Experimental results showed that the proposed algorithm significantly improves the retrieval effectiveness. Compared with four state-of-the-art query refinement schemes for 3D model retrieval, it provides superior retrieval performance after no more than two rounds of relevance feedback.
基金supported by German-Sino bilateral collaboration research project SuMaRiO funded by the German Federal Ministry of Education and Researchthe support of NSFC-UNEP Project (41361140361): Ecological Responses to Climatic Change and Land-cover Change in Arid and Semiarid Central Asia during the Past 500 Years
文摘Hydrological models are often linked with other models in cognate sciences to understand the interactions among climate, earth, water, ecosystem, and human society. This paper presents the development and implementation of a decision support system（DSS） that links the outputs of hydrological models with real-time decision making on social-economic assessments and land use management. Discharge and glacier geometry changes were simulated with hydrological model, water availability in semiarid environments. Irrigation and ecological water were simulated by a new commercial software MIKE HYDRO. Groundwater was simulated by MODFLOW. All the outputs of theses hydrological models were taken as inputs into the DSS in three types of links： regression equations, stationary data inputs, or dynamic data inputs as the models running parallel in the simulation periods. The DSS integrates the hydrological data, geographic data, social and economic statistical data, and establishes the relationships with equations, conditional statements and fuzzy logics. The programming is realized in C＋＋. The DSS has four remarkable features：（1） editable land use maps to assist decision-making;（2） conjunctive use of surface and groundwater resources;（3） interactions among water, earth, ecosystem, and humans; and（4） links with hydrological models. The overall goal of the DSS is to combine the outputs of scientific models, knowledge of experts, and perspectives of stakeholders, into a computer-based system, which allows sustainability impact assessment within regional planning; and to understand ecosystem services and integrate them into land and water management.
基金the National Natural Science Foundation of China(No.60905066)the Natural Science Foundation of Chongqing(No.cstc2018jcyjA0667)
文摘As optimization of parameters affects prediction accuracy and generalization ability of support vector regression(SVR) greatly and the predictive model often mismatches nonlinear system model predictive control,a multi-step model predictive control based on online SVR(OSVR) optimized by multi-agent particle swarm optimization algorithm(MAPSO) is put forward. By integrating the online learning ability of OSVR, the predictive model can self-correct and adapt to the dynamic changes in nonlinear process well.
基金Project(2002CB312200) supported by the National Key Fundamental Research and Development Program of China project(60574019) supported by the National Natural Science Foundation of China
文摘Robustly stable multi-step-ahead model predictive control (MPC) based on parallel support vector machines (SVMs) with linear kernel was proposed. First, an analytical solution of optimal control laws of parallel SVMs based MPC was derived, and then the necessary and sufficient stability condition for MPC closed loop was given according to SVM model, and finally a method of judging the discrepancy between SVM model and the actual plant was presented, and consequently the constraint sets, which can guarantee that the stability condition is still robust for model/plant mismatch within some given bounds, were obtained by applying small-gain theorem. Simulation experiments show the proposed stability condition and robust constraint sets can provide a convenient way of adjusting controller parameters to ensure a closed-loop with larger stable margin.
基金Under the auspices of National Natural Science Foundation of China (No. 40671133)Fundamental Research Funds for the Central Universities (No. GK200902015)
文摘This paper proposed a semi-supervised regression model with co-training algorithm based on support vector machine, which was used for retrieving water quality variables from SPOT 5 remote sensing data. The model consisted of two support vector regressors (SVRs). Nonlinear relationship between water quality variables and SPOT 5 spectrum was described by the two SVRs, and semi-supervised co-training algorithm for the SVRs was es-tablished. The model was used for retrieving concentrations of four representative pollution indicators―permangan- ate index (CODmn), ammonia nitrogen (NH3-N), chemical oxygen demand (COD) and dissolved oxygen (DO) of the Weihe River in Shaanxi Province, China. The spatial distribution map for those variables over a part of the Weihe River was also produced. SVR can be used to implement any nonlinear mapping readily, and semi-supervis- ed learning can make use of both labeled and unlabeled samples. By integrating the two SVRs and using semi-supervised learning, we provide an operational method when paired samples are limited. The results show that it is much better than the multiple statistical regression method, and can provide the whole water pollution condi-tions for management fast and can be extended to hyperspectral remote sensing applications.
基金National High Technology Research andDevelopment Program of China( Project 863 G2 0 0 1AA413 13 0
文摘A new multiple models(MM) approach was proposed to model complex industrial process by using Fuzzy Support Vector Machines(F -SVMs). By applying the proposed approach to a pH neutralization titration experiment, F -SVMs MM not only provides satisfactory approximation and generalization property, but also achieves superior performance to USOCPN multiple modeling method and single modeling method based on standard SVMs.
