Platform planning is one of the important problems in the command and control(C2) field. Hereto, we analyze the platform planning problem and present nonlinear optimal model aiming at maximizing the task completion qu...Platform planning is one of the important problems in the command and control(C2) field. Hereto, we analyze the platform planning problem and present nonlinear optimal model aiming at maximizing the task completion qualities. Firstly, we take into account the relation among tasks and build the single task nonlinear optimal model with a set of platform constraints. The Lagrange relaxation method and the pruning strategy are used to solve the model. Secondly, this paper presents optimization-based planning algorithms for efficiently allocating platforms to multiple tasks. To achieve the balance of the resource assignments among tasks, the m-best assignment algorithm and the pair-wise exchange(PWE)method are used to maximize multiple tasks completion qualities.Finally, a series of experiments are designed to verify the superiority and effectiveness of the proposed model and algorithms.展开更多
In order to resolve the coordination and optimization of the power network planning effectively, on the basis of introducing the concept of power intelligence center (PIC), the key factor power flow, line investment a...In order to resolve the coordination and optimization of the power network planning effectively, on the basis of introducing the concept of power intelligence center (PIC), the key factor power flow, line investment and load that impact generation sector, transmission sector and dispatching center in PIC were analyzed and a multi-objective coordination optimal model for new power intelligence center (NPIC) was established. To ensure the reliability and coordination of power grid and reduce investment cost, two aspects were optimized. The evolutionary algorithm was introduced to solve optimal power flow problem and the fitness function was improved to ensure the minimum cost of power generation. The gray particle swarm optimization (GPSO) algorithm was used to forecast load accurately, which can ensure the network with high reliability. On this basis, the multi-objective coordination optimal model which was more practical and in line with the need of the electricity market was proposed, then the coordination model was effectively solved through the improved particle swarm optimization algorithm, and the corresponding algorithm was obtained. The optimization of IEEE30 node system shows that the evolutionary algorithm can effectively solve the problem of optimal power flow. The average load forecasting of GPSO is 26.97 MW, which has an error of 0.34 MW compared with the actual load. The algorithm has higher forecasting accuracy. The multi-objective coordination optimal model for NPIC can effectively process the coordination and optimization problem of power network.展开更多
In this article,we present an application of Adaptive Genetic Algorithm Energy Demand Estimation(AGAEDE) optimal model to improve the efficiency of energy demand prediction.The coefficients of the two forms of the mod...In this article,we present an application of Adaptive Genetic Algorithm Energy Demand Estimation(AGAEDE) optimal model to improve the efficiency of energy demand prediction.The coefficients of the two forms of the model(both linear and quadratic) are optimized by AGA using factors,such as GDP,population,urbanization rate,and R&D inputs together with energy consumption structure,that affect demand.Since the spurious regression phenomenon occurs for a wide range of time series analysis in econometrics,we also discuss this problem for the current artificial intelligence model.The simulation results show that the proposed model is more accurate and reliable compared with other existing methods and the China's energy demand will be 5.23 billion TCE in 2020 according to the average results of the AGAEDE optimal model.Further discussion illustrates that there will be great pressure for China to fulfill the planned goal of controlling energy demand set in the National Energy Demand Project(2014—2020).展开更多
The control of total water pollutant amount is an effective method to improve quality of the groundwater, but how to allocate the total amount is an important and difficult work. In this paper, equity and efficiency w...The control of total water pollutant amount is an effective method to improve quality of the groundwater, but how to allocate the total amount is an important and difficult work. In this paper, equity and efficiency were bases of the total amount allocation. Took total amount allocation of the surface water pollutant in a car manufacturing group as an example, the current emissions and unit of output value as the bases for cluster analysis, the target unit was divided into ＂key reduction unit＂ and ＂concern reduction unit＂. Then, allocation scheme of the total amount was prepared. This model for research and improvement of the feasibility for total pollutant amount allocation technique has certain reference value.展开更多
The main objective of this paper is to consider model averaging methods for kriging models.This paper proposes a Mallows model averaging procedure for the orthogonal kriging model and demonstrate the asymptotic optima...The main objective of this paper is to consider model averaging methods for kriging models.This paper proposes a Mallows model averaging procedure for the orthogonal kriging model and demonstrate the asymptotic optimality of the model averaging estimators in terms of mean square error.Simulation studies are conducted to evaluate the performance of the proposed method and compare it with the competitors to demonstrate its superiority.The authors also analyse a real dataset for an illustration.展开更多
The carbon emissions and cost during the construction phase are significant contributors to the oilfield lifecycle.As oilfields enter the late stage,the adaptability of facilities decreases.To achieve sustainable deve...The carbon emissions and cost during the construction phase are significant contributors to the oilfield lifecycle.As oilfields enter the late stage,the adaptability of facilities decreases.To achieve sustainable development,oilfield reconstruction was usually conducted in discrete rather than continuous space.Motivated by economic and sustainability goals,a 3-phase heuristic model for oilfield reconstruction was developed to mine potential locations in continuous space.In phase 1,considering the process characteristics of the oil and gas gathering system,potential locations were mined in continuous space.In phase 2,incorporating comprehensive reconstruction measures,a reconstruction model was established in discrete space.In phase 3,the topology was further adjusted in continuous space.Subsequently,the model was transformed into a single-objective mixed integer linear programming model using the augmented ε-constraint method.Numerical experiments revealed that the small number of potential locations could effectively reduce the reconstruction cost,and the quality of potential locations mined in phase 1 surpassed those generated in random or grid form.Case studies showed that cost and carbon emissions for a new block were reduced by up to 10.45% and 7.21 %,respectively.These reductions were because the potential locations mined in 1P reduced the number of metering stations,and 3P adjusted the locations of metering stations in continuous space to shorten the pipeline length.For an old oilfield,the load and connection ratios of the old metering station increased to 89.7% and 94.9%,respectively,enhancing operation efficiency.Meanwhile,recycling facilitated the diversification of reconstruction measures and yielded a profit of 582,573 ¥,constituting 5.56% of the total cost.This study adopted comprehensive reconstruction measures and tapped into potential reductions in cost and carbon emissions for oilfield reconstruction,offering valuable insights for future oilfield design and construction.展开更多
With the advancement of digital technology,new technologies such as artificial intelligence,big data,and cloud computing have gradually permeated higher education,leading to fundamental changes in teaching and learnin...With the advancement of digital technology,new technologies such as artificial intelligence,big data,and cloud computing have gradually permeated higher education,leading to fundamental changes in teaching and learning methods.Therefore,in the process of reforming and developing higher education,it is essential to take digital technology empowering the optimization of the education industry as a breakthrough,focusing on five key areas:the construction of smart classrooms,the digital integration of teaching resources,the development of personalized learning support systems,the reform of online-offline hybrid teaching,and the intelligentization of educational management.This paper also examines the experiences,challenges,and shortcomings of typical universities in using digital technology to improve teaching quality,optimize resource allocation,and innovate teaching management models.Finally,corresponding countermeasures and suggestions are proposed to facilitate the smooth implementation of digital transformation in higher education institutions.展开更多
An effort to model the dynamic optimal advertising was made with the uncertainty of sales responses in consideration. The problem of dynamic advertising was depicted as a Markov decision process with two state variabl...An effort to model the dynamic optimal advertising was made with the uncertainty of sales responses in consideration. The problem of dynamic advertising was depicted as a Markov decision process with two state variables. When a firm launches an advertising campaign, it may predict the probability that the campaign will obtain the sales réponse. This probability was chosen as one state variable. Cumulative sales volume was chosen as another state variable which varies randomly with advertising. The only decision variable was advertising expenditure. With these variables, a multi-stage Markov decision process model was formulat ed. On the basis of some propositions the model was analyzed. Some analytical results about the optimal strategy have been derived, and their practical implications have been explained.展开更多
In this letter, an improved optimal velocity model was proposed that assumes the effect of relative velocity deceases with the increment of gap between successive cars. Numerical simuation was carried out to test whet...In this letter, an improved optimal velocity model was proposed that assumes the effect of relative velocity deceases with the increment of gap between successive cars. Numerical simuation was carried out to test whether this model could depict the braking process correctly. The simuation results show good agreement with observed data.展开更多
In this paper, the velocity anticipation in the optimal velocity model （OVM） is investigated. The driver adjusts the velocity of his vehicle by the desired headway, which depends on both instantaneous headway and re...In this paper, the velocity anticipation in the optimal velocity model （OVM） is investigated. The driver adjusts the velocity of his vehicle by the desired headway, which depends on both instantaneous headway and relative velocity. The effect of relative velocity is measured by a sensitivity function. A specific form of the sensitivity function is supposed and the involved parameters are determined by the both numerical simulation and empirical data. It is shown that inclusion of velocity anticipation enhances the stability of traffic flow. Numerical simulations show a good agreement with empirical data. This model provides a better description of real traffic, including the acceleration process from standing states and the deceleration process approaching a stopped car.展开更多
Associated dynamic performance of the clamping force control valve used in continuously variable transmission （CVT） is optimized. Firstly, the structure and working principle of the valve are analyzed, and then a dy...Associated dynamic performance of the clamping force control valve used in continuously variable transmission （CVT） is optimized. Firstly, the structure and working principle of the valve are analyzed, and then a dynamic model is set up by means of mechanism analysis. For the purpose of checking the validity of the modeling method, a prototype workpiece of the valve is manufactured for comparison test, and its simulation result follows the experimental result quite well. An associated performance index is founded considering the response time, overshoot and saving energy, and five structural parameters are selected to adjust for deriving the optimal associated performance index. The optimization problem is solved by the genetic algorithm （GA） with necessary constraints. Finally, the properties of the optimized valve are compared with those of the prototype workpiece, and the results prove that the dynamic performance indexes of the optimized valve are much better than those of the prototype workpiece.展开更多
The class of bi-directional optimal velocity models can describe the bi-directional looking effect that usually exists in the reality and is even enhanced with the development of the connected vehicle technologies. It...The class of bi-directional optimal velocity models can describe the bi-directional looking effect that usually exists in the reality and is even enhanced with the development of the connected vehicle technologies. Its combined string stability condition can be obtained through the method of the ring-road based string stability analysis. However, the partial string stability about traffic fluctuation propagated backward or forward was neglected, which will be analyzed in detail in this work by the method of transfer function and its H∞ norm from the viewpoint of control theory. Then, through comparing the conditions of combined and partial string stabilities, their relationships can make traffic flow be divided into three distinguishable regions, displaying various combined and partial string stability performance. Finally, the numerical experiments verify the theoretical results and find that the final displaying string stability or instability performance results from the accumulated and offset effects of traffic fluctuations propagated from different directions.展开更多
Low pressure chemical vapor deposition(LPCVD) is one of the most important processes during semiconductor manufacturing.However,the spatial distribution of internal temperature and extremely few samples makes it hard ...Low pressure chemical vapor deposition(LPCVD) is one of the most important processes during semiconductor manufacturing.However,the spatial distribution of internal temperature and extremely few samples makes it hard to build a good-quality model of this batch process.Besides,due to the properties of this process,the reliability of the model must be taken into consideration when optimizing the MVs.In this work,an optimal design strategy based on the self-learning Gaussian process model(GPM) is proposed to control this kind of spatial batch process.The GPM is utilized as the internal model to predict the thicknesses of thin films on all spatial-distributed wafers using the limited data.Unlike the conventional model based design,the uncertainties of predictions provided by GPM are taken into consideration to guide the optimal design of manipulated variables so that the designing can be more prudent Besides,the GPM is also actively enhanced using as little data as possible based on the predictive uncertainties.The effectiveness of the proposed strategy is successfully demonstrated in an LPCVD process.展开更多
The 7-DOF model of a full vehicle with an active suspension is developed in this paper.The model is written into the state equation style.Actuator forces are treated as inputs in the state equations.Based on the basic...The 7-DOF model of a full vehicle with an active suspension is developed in this paper.The model is written into the state equation style.Actuator forces are treated as inputs in the state equations.Based on the basic optimal control theory,the optimal gains for the control system are figured out.So an optimal controller is developed and implemented using Matlab/Simulink,where the Riccati equation with coupling terms is deduced using the Hamilton equation.The all state feedback is chosen for the controller.The gains for all vehicle variables are traded off so that majority of indexes were up to optimal.The active suspension with optimal control is simulated in frequency domain and time domain separately,and compared with a passive suspension.Throughout all the simulation results,the optimal controller developed in this paper works well in the majority of instances.In all,the comfort and ride performance of the vehicle are improved under the active suspension with optimal control.展开更多
In this paper, we study the optimal financing problem in the dual model. We introduce a value function which considers both the expected present value of the dividends payout minus the equity issuance and a penalty at...In this paper, we study the optimal financing problem in the dual model. We introduce a value function which considers both the expected present value of the dividends payout minus the equity issuance and a penalty at ruin. In order to get the optimal strategy,two categories of suboptimal models are constructed and studied. Based on these two suboptimal models, we identify the value function and the optimal strategy in the general optimal problem.展开更多
A new coupled map car-following model in this paper is proposed by considering the influence of the difference of the estimated optimal speed based on the coupled map(CM)car-following model under V2X environment.The s...A new coupled map car-following model in this paper is proposed by considering the influence of the difference of the estimated optimal speed based on the coupled map(CM)car-following model under V2X environment.The stability of the new model is analyzed by applying the control theory,and the conditions are obtained for the stability of the traffic system.And the two scenes of vehicle stopping once and four times have been simulated.The simulation results show that the control term considered with optimal estimation of speed difference can effectively improve the stability of vehicle running and reduce CO_(2) emissions in the CM car-following model.展开更多
As the large-scale development of wind farms(WFs)progresses,the connection ofWFs to the regional power grid is evolving from the conventional receiving power grid to the sending power grid with a high proportion of wi...As the large-scale development of wind farms(WFs)progresses,the connection ofWFs to the regional power grid is evolving from the conventional receiving power grid to the sending power grid with a high proportion of wind power(WP).Due to the randomness of WP output,higher requirements are put forward for the voltage stability of each node of the regional power grid,and various reactive power compensation devices(RPCDs)need to be rationally configured to meet the stable operation requirements of the system.This paper proposes an optimal configuration method for multi-type RPCDs in regional power grids with a high proportion of WP.The RPCDs are located according to the proposed static voltage stability index(VSI)and dynamicVSI based on dynamic voltage drop area,and the optimal configuration model of RPCDs is constructed with the lowest construction cost as the objective function to determine the installed capacity of various RPCDs.Finally,the corresponding regional power grid model for intensive access to WFs is constructed on the simulation platform to verify the effectiveness of the proposed method.展开更多
Selecting the optimal one from similar schemes is a paramount work in equipment design.In consideration of similarity of schemes and repetition of characteristic indices,the theory of set pair analysis(SPA)is proposed...Selecting the optimal one from similar schemes is a paramount work in equipment design.In consideration of similarity of schemes and repetition of characteristic indices,the theory of set pair analysis(SPA)is proposed,and then an optimal selection model is established.In order to improve the accuracy and flexibility,the model is modified by the contribution degree.At last,this model has been validated by an example,and the result demonstrates the method is feasible and valuable for practical usage.展开更多
The mixed model of improved exponential and power function and unequal interval gray GM(1,1)model have poor accuracy in predicting the maximum pull-out load of anchor bolts.An optimal combination model was derived usi...The mixed model of improved exponential and power function and unequal interval gray GM(1,1)model have poor accuracy in predicting the maximum pull-out load of anchor bolts.An optimal combination model was derived using the optimally weighted combination theory and the minimum sum of logarithmic squared errors as the objective function.Two typical anchor bolt pull-out engineering cases were selected to compare the performance of the proposed model with those of existing ones.Results showed that the optimal combination model was suitable not only for the slow P-s curve but also for the steep P-s curve.Its accuracy and stable reliability,as well as its prediction capability classification,were better than those of the other prediction models.Therefore,the optimal combination model is an effective processing method for predicting the maximum pull-out load of anchor bolts according to measured data.展开更多
With the increasing focus on sustainable development goals,the critical role of reverse logistics in supply chains is becoming more evident.Reverse logistics not only enables resource recovery and reuse but also reduc...With the increasing focus on sustainable development goals,the critical role of reverse logistics in supply chains is becoming more evident.Reverse logistics not only enables resource recovery and reuse but also reduces environmental pollution and enhances economic efficiency.However,existing models face significant challenges related to recovery efficiency,cost control,and supply chain coordination.To address these challenges,this study proposes strategies to improve recovery and reuse efficiency,optimize logistics processes,enhance information sharing and collaboration,and encourage active participation from both businesses and consumers.These measures aim to improve the overall efficiency of reverse logistics and support the achievement of sustainable development goals.展开更多
基金supported by the National Natural Science Foundation of China(61573017 61703425)+2 种基金the Aeronautical Science Fund(20175796014)the Shaanxi Province Natural Science Foundation Research Project(2016JQ6062 2017JM6062)
文摘Platform planning is one of the important problems in the command and control(C2) field. Hereto, we analyze the platform planning problem and present nonlinear optimal model aiming at maximizing the task completion qualities. Firstly, we take into account the relation among tasks and build the single task nonlinear optimal model with a set of platform constraints. The Lagrange relaxation method and the pruning strategy are used to solve the model. Secondly, this paper presents optimization-based planning algorithms for efficiently allocating platforms to multiple tasks. To achieve the balance of the resource assignments among tasks, the m-best assignment algorithm and the pair-wise exchange(PWE)method are used to maximize multiple tasks completion qualities.Finally, a series of experiments are designed to verify the superiority and effectiveness of the proposed model and algorithms.
基金Project (70671039) supported by the National Natural Science Foundation of China
文摘In order to resolve the coordination and optimization of the power network planning effectively, on the basis of introducing the concept of power intelligence center (PIC), the key factor power flow, line investment and load that impact generation sector, transmission sector and dispatching center in PIC were analyzed and a multi-objective coordination optimal model for new power intelligence center (NPIC) was established. To ensure the reliability and coordination of power grid and reduce investment cost, two aspects were optimized. The evolutionary algorithm was introduced to solve optimal power flow problem and the fitness function was improved to ensure the minimum cost of power generation. The gray particle swarm optimization (GPSO) algorithm was used to forecast load accurately, which can ensure the network with high reliability. On this basis, the multi-objective coordination optimal model which was more practical and in line with the need of the electricity market was proposed, then the coordination model was effectively solved through the improved particle swarm optimization algorithm, and the corresponding algorithm was obtained. The optimization of IEEE30 node system shows that the evolutionary algorithm can effectively solve the problem of optimal power flow. The average load forecasting of GPSO is 26.97 MW, which has an error of 0.34 MW compared with the actual load. The algorithm has higher forecasting accuracy. The multi-objective coordination optimal model for NPIC can effectively process the coordination and optimization problem of power network.
基金supported by the Fundamental Research Funds for the Central Universities[Grant No.JBK1507159]
文摘In this article,we present an application of Adaptive Genetic Algorithm Energy Demand Estimation(AGAEDE) optimal model to improve the efficiency of energy demand prediction.The coefficients of the two forms of the model(both linear and quadratic) are optimized by AGA using factors,such as GDP,population,urbanization rate,and R&D inputs together with energy consumption structure,that affect demand.Since the spurious regression phenomenon occurs for a wide range of time series analysis in econometrics,we also discuss this problem for the current artificial intelligence model.The simulation results show that the proposed model is more accurate and reliable compared with other existing methods and the China's energy demand will be 5.23 billion TCE in 2020 according to the average results of the AGAEDE optimal model.Further discussion illustrates that there will be great pressure for China to fulfill the planned goal of controlling energy demand set in the National Energy Demand Project(2014—2020).
基金Supported by Science and Technology Key Special Item of the National Water Body Pollution Control and Treatment (2008ZX07208-006-01)
文摘The control of total water pollutant amount is an effective method to improve quality of the groundwater, but how to allocate the total amount is an important and difficult work. In this paper, equity and efficiency were bases of the total amount allocation. Took total amount allocation of the surface water pollutant in a car manufacturing group as an example, the current emissions and unit of output value as the bases for cluster analysis, the target unit was divided into ＂key reduction unit＂ and ＂concern reduction unit＂. Then, allocation scheme of the total amount was prepared. This model for research and improvement of the feasibility for total pollutant amount allocation technique has certain reference value.
基金supported by the National Natural Science Foundation of China under Grant No.11871294。
文摘The main objective of this paper is to consider model averaging methods for kriging models.This paper proposes a Mallows model averaging procedure for the orthogonal kriging model and demonstrate the asymptotic optimality of the model averaging estimators in terms of mean square error.Simulation studies are conducted to evaluate the performance of the proposed method and compare it with the competitors to demonstrate its superiority.The authors also analyse a real dataset for an illustration.
基金supported by the National Natural Science Foundation of China (Grant No.52174065)the National Natural Science Foundation of China (Grant No.52304071)+1 种基金China University of Petroleum,Beijing (Grant No.ZX20220040)MOE Key Laboratory of Petroleum Engineering (China University of Petroleum,No.2462024PTJS002)。
文摘The carbon emissions and cost during the construction phase are significant contributors to the oilfield lifecycle.As oilfields enter the late stage,the adaptability of facilities decreases.To achieve sustainable development,oilfield reconstruction was usually conducted in discrete rather than continuous space.Motivated by economic and sustainability goals,a 3-phase heuristic model for oilfield reconstruction was developed to mine potential locations in continuous space.In phase 1,considering the process characteristics of the oil and gas gathering system,potential locations were mined in continuous space.In phase 2,incorporating comprehensive reconstruction measures,a reconstruction model was established in discrete space.In phase 3,the topology was further adjusted in continuous space.Subsequently,the model was transformed into a single-objective mixed integer linear programming model using the augmented ε-constraint method.Numerical experiments revealed that the small number of potential locations could effectively reduce the reconstruction cost,and the quality of potential locations mined in phase 1 surpassed those generated in random or grid form.Case studies showed that cost and carbon emissions for a new block were reduced by up to 10.45% and 7.21 %,respectively.These reductions were because the potential locations mined in 1P reduced the number of metering stations,and 3P adjusted the locations of metering stations in continuous space to shorten the pipeline length.For an old oilfield,the load and connection ratios of the old metering station increased to 89.7% and 94.9%,respectively,enhancing operation efficiency.Meanwhile,recycling facilitated the diversification of reconstruction measures and yielded a profit of 582,573 ¥,constituting 5.56% of the total cost.This study adopted comprehensive reconstruction measures and tapped into potential reductions in cost and carbon emissions for oilfield reconstruction,offering valuable insights for future oilfield design and construction.
文摘With the advancement of digital technology,new technologies such as artificial intelligence,big data,and cloud computing have gradually permeated higher education,leading to fundamental changes in teaching and learning methods.Therefore,in the process of reforming and developing higher education,it is essential to take digital technology empowering the optimization of the education industry as a breakthrough,focusing on five key areas:the construction of smart classrooms,the digital integration of teaching resources,the development of personalized learning support systems,the reform of online-offline hybrid teaching,and the intelligentization of educational management.This paper also examines the experiences,challenges,and shortcomings of typical universities in using digital technology to improve teaching quality,optimize resource allocation,and innovate teaching management models.Finally,corresponding countermeasures and suggestions are proposed to facilitate the smooth implementation of digital transformation in higher education institutions.
基金This work was supported by the National Natural Science Foundation(No.70271021).
文摘An effort to model the dynamic optimal advertising was made with the uncertainty of sales responses in consideration. The problem of dynamic advertising was depicted as a Markov decision process with two state variables. When a firm launches an advertising campaign, it may predict the probability that the campaign will obtain the sales réponse. This probability was chosen as one state variable. Cumulative sales volume was chosen as another state variable which varies randomly with advertising. The only decision variable was advertising expenditure. With these variables, a multi-stage Markov decision process model was formulat ed. On the basis of some propositions the model was analyzed. Some analytical results about the optimal strategy have been derived, and their practical implications have been explained.
文摘In this letter, an improved optimal velocity model was proposed that assumes the effect of relative velocity deceases with the increment of gap between successive cars. Numerical simuation was carried out to test whether this model could depict the braking process correctly. The simuation results show good agreement with observed data.
基金supported by the National Basic Research Program of China (Grant No.2006CB705500)the National Natural Science Foundation of China (Grant Nos.10532060, 10672098)
文摘In this paper, the velocity anticipation in the optimal velocity model （OVM） is investigated. The driver adjusts the velocity of his vehicle by the desired headway, which depends on both instantaneous headway and relative velocity. The effect of relative velocity is measured by a sensitivity function. A specific form of the sensitivity function is supposed and the involved parameters are determined by the both numerical simulation and empirical data. It is shown that inclusion of velocity anticipation enhances the stability of traffic flow. Numerical simulations show a good agreement with empirical data. This model provides a better description of real traffic, including the acceleration process from standing states and the deceleration process approaching a stopped car.
基金Key Science-Technology Foundation of Hunan Province, China (No. 05GK2007).
文摘Associated dynamic performance of the clamping force control valve used in continuously variable transmission （CVT） is optimized. Firstly, the structure and working principle of the valve are analyzed, and then a dynamic model is set up by means of mechanism analysis. For the purpose of checking the validity of the modeling method, a prototype workpiece of the valve is manufactured for comparison test, and its simulation result follows the experimental result quite well. An associated performance index is founded considering the response time, overshoot and saving energy, and five structural parameters are selected to adjust for deriving the optimal associated performance index. The optimization problem is solved by the genetic algorithm （GA） with necessary constraints. Finally, the properties of the optimized valve are compared with those of the prototype workpiece, and the results prove that the dynamic performance indexes of the optimized valve are much better than those of the prototype workpiece.
基金Projects(51108465,71371192)supported by the National Natural Science Foundation of ChinaProject(2014M552165)supported by China Postdoctoral Science FoundationProject(20113187851460)supported by Technology Project of the Ministry of Transport of China
文摘The class of bi-directional optimal velocity models can describe the bi-directional looking effect that usually exists in the reality and is even enhanced with the development of the connected vehicle technologies. Its combined string stability condition can be obtained through the method of the ring-road based string stability analysis. However, the partial string stability about traffic fluctuation propagated backward or forward was neglected, which will be analyzed in detail in this work by the method of transfer function and its H∞ norm from the viewpoint of control theory. Then, through comparing the conditions of combined and partial string stabilities, their relationships can make traffic flow be divided into three distinguishable regions, displaying various combined and partial string stability performance. Finally, the numerical experiments verify the theoretical results and find that the final displaying string stability or instability performance results from the accumulated and offset effects of traffic fluctuations propagated from different directions.
基金Supported by the National High Technology Research and Development Program of China(2014AA041803)the National Natural Science Foundation of China(61320106009)
文摘Low pressure chemical vapor deposition(LPCVD) is one of the most important processes during semiconductor manufacturing.However,the spatial distribution of internal temperature and extremely few samples makes it hard to build a good-quality model of this batch process.Besides,due to the properties of this process,the reliability of the model must be taken into consideration when optimizing the MVs.In this work,an optimal design strategy based on the self-learning Gaussian process model(GPM) is proposed to control this kind of spatial batch process.The GPM is utilized as the internal model to predict the thicknesses of thin films on all spatial-distributed wafers using the limited data.Unlike the conventional model based design,the uncertainties of predictions provided by GPM are taken into consideration to guide the optimal design of manipulated variables so that the designing can be more prudent Besides,the GPM is also actively enhanced using as little data as possible based on the predictive uncertainties.The effectiveness of the proposed strategy is successfully demonstrated in an LPCVD process.
文摘The 7-DOF model of a full vehicle with an active suspension is developed in this paper.The model is written into the state equation style.Actuator forces are treated as inputs in the state equations.Based on the basic optimal control theory,the optimal gains for the control system are figured out.So an optimal controller is developed and implemented using Matlab/Simulink,where the Riccati equation with coupling terms is deduced using the Hamilton equation.The all state feedback is chosen for the controller.The gains for all vehicle variables are traded off so that majority of indexes were up to optimal.The active suspension with optimal control is simulated in frequency domain and time domain separately,and compared with a passive suspension.Throughout all the simulation results,the optimal controller developed in this paper works well in the majority of instances.In all,the comfort and ride performance of the vehicle are improved under the active suspension with optimal control.
基金Supported by the National Natural Science Foundation of China(Grant No.11361007)the Guangxi Natural Science Foundation(Grant No.2014GXNSFCA118001)+3 种基金the Fostering Project of Dominant Discipline and Talent Team of Shandong Provincial Higher Education Institutionsthe Fostering Project of Dominant Discipline and Talent Team of SDUFEProject of Shandong Provincial Higher Educational Science and Technology Program(Grant Nos.J15LI01J17KA163)
文摘In this paper, we study the optimal financing problem in the dual model. We introduce a value function which considers both the expected present value of the dividends payout minus the equity issuance and a penalty at ruin. In order to get the optimal strategy,two categories of suboptimal models are constructed and studied. Based on these two suboptimal models, we identify the value function and the optimal strategy in the general optimal problem.
基金supported by the National Natural Science Foundation of China(Grant Nos.61963008,61673168,11762004,and 12047567)the Natural Science Foundation of Guangxi Zhuang Autonomous Region,China(Grant No.2018GXNSFAA281274)+2 种基金Guangxi Innovation-Driven Development Special Fund Project(Grant No.GUIKEAA19254034-3)the Doctor Scientific Research Startup Project Foundation of Guangxi Normal University,China(Grant No.2018BQ007)the Science and Technology Project of Zhenjiang City,Jiangsu Province,China(Grant No.GY2020019)。
文摘A new coupled map car-following model in this paper is proposed by considering the influence of the difference of the estimated optimal speed based on the coupled map(CM)car-following model under V2X environment.The stability of the new model is analyzed by applying the control theory,and the conditions are obtained for the stability of the traffic system.And the two scenes of vehicle stopping once and four times have been simulated.The simulation results show that the control term considered with optimal estimation of speed difference can effectively improve the stability of vehicle running and reduce CO_(2) emissions in the CM car-following model.
基金supported by the Science and Technology Project of State Grid Corporation Headquarters(No.5100-202323008A-1-1-ZN).
文摘As the large-scale development of wind farms(WFs)progresses,the connection ofWFs to the regional power grid is evolving from the conventional receiving power grid to the sending power grid with a high proportion of wind power(WP).Due to the randomness of WP output,higher requirements are put forward for the voltage stability of each node of the regional power grid,and various reactive power compensation devices(RPCDs)need to be rationally configured to meet the stable operation requirements of the system.This paper proposes an optimal configuration method for multi-type RPCDs in regional power grids with a high proportion of WP.The RPCDs are located according to the proposed static voltage stability index(VSI)and dynamicVSI based on dynamic voltage drop area,and the optimal configuration model of RPCDs is constructed with the lowest construction cost as the objective function to determine the installed capacity of various RPCDs.Finally,the corresponding regional power grid model for intensive access to WFs is constructed on the simulation platform to verify the effectiveness of the proposed method.
文摘Selecting the optimal one from similar schemes is a paramount work in equipment design.In consideration of similarity of schemes and repetition of characteristic indices,the theory of set pair analysis(SPA)is proposed,and then an optimal selection model is established.In order to improve the accuracy and flexibility,the model is modified by the contribution degree.At last,this model has been validated by an example,and the result demonstrates the method is feasible and valuable for practical usage.
基金The National Natural Science Foundation of China(No.51778485).
文摘The mixed model of improved exponential and power function and unequal interval gray GM(1,1)model have poor accuracy in predicting the maximum pull-out load of anchor bolts.An optimal combination model was derived using the optimally weighted combination theory and the minimum sum of logarithmic squared errors as the objective function.Two typical anchor bolt pull-out engineering cases were selected to compare the performance of the proposed model with those of existing ones.Results showed that the optimal combination model was suitable not only for the slow P-s curve but also for the steep P-s curve.Its accuracy and stable reliability,as well as its prediction capability classification,were better than those of the other prediction models.Therefore,the optimal combination model is an effective processing method for predicting the maximum pull-out load of anchor bolts according to measured data.
文摘With the increasing focus on sustainable development goals,the critical role of reverse logistics in supply chains is becoming more evident.Reverse logistics not only enables resource recovery and reuse but also reduces environmental pollution and enhances economic efficiency.However,existing models face significant challenges related to recovery efficiency,cost control,and supply chain coordination.To address these challenges,this study proposes strategies to improve recovery and reuse efficiency,optimize logistics processes,enhance information sharing and collaboration,and encourage active participation from both businesses and consumers.These measures aim to improve the overall efficiency of reverse logistics and support the achievement of sustainable development goals.
