Attribute reduction in the rough set theory is an important feature selection method, but finding a minimum attribute reduction has been proven to be a non-deterministic polynomial （NP）-hard problem. Therefore, it i...Attribute reduction in the rough set theory is an important feature selection method, but finding a minimum attribute reduction has been proven to be a non-deterministic polynomial （NP）-hard problem. Therefore, it is necessary to investigate some fast and effective approximate algorithms. A novel and enhanced quantum-inspired shuffled frog leaping based minimum attribute reduction algorithm （QSFLAR） is proposed. Evolutionary frogs are represented by multi-state quantum bits, and both quantum rotation gate and quantum mutation operators are used to exploit the mechanisms of frog population diversity and convergence to the global optimum. The decomposed attribute subsets are co-evolved by the elitist frogs with a quantum-inspired shuffled frog leaping algorithm. The experimental results validate the better feasibility and effectiveness of QSFLAR, comparing with some representa- tive algorithms. Therefore, QSFLAR can be considered as a more competitive algorithm on the efficiency and accuracy for minimum attribute reduction.展开更多
Region partition(RP) is the key technique to the finite element parallel computing(FEPC),and its performance has a decisive influence on the entire process of analysis and computation.The performance evaluation index ...Region partition(RP) is the key technique to the finite element parallel computing(FEPC),and its performance has a decisive influence on the entire process of analysis and computation.The performance evaluation index of RP method for the three-dimensional finite element model(FEM) has been given.By taking the electric field of aluminum reduction cell(ARC) as the research object,the performance of two classical RP methods,which are Al-NASRA and NGUYEN partition(ANP) algorithm and the multi-level partition(MLP) method,has been analyzed and compared.The comparison results indicate a sound performance of ANP algorithm,but to large-scale models,the computing time of ANP algorithm increases notably.This is because the ANP algorithm determines only one node based on the minimum weight and just adds the elements connected to the node into the sub-region during each iteration.To obtain the satisfied speed and the precision,an improved dynamic self-adaptive ANP(DSA-ANP) algorithm has been proposed.With consideration of model scale,complexity and sub-RP stage,the improved algorithm adaptively determines the number of nodes and selects those nodes with small enough weight,and then dynamically adds these connected elements.The proposed algorithm has been applied to the finite element analysis(FEA) of the electric field simulation of ARC.Compared with the traditional ANP algorithm,the computational efficiency of the proposed algorithm has been shortened approximately from 260 s to 13 s.This proves the superiority of the improved algorithm on computing time performance.展开更多
This work presents a fuzzy based methodology for distribution system feeder reconfiguration considering DSTATCOM with an objective of minimizing real power loss and operating cost. Installation costs of DSTATCOM devic...This work presents a fuzzy based methodology for distribution system feeder reconfiguration considering DSTATCOM with an objective of minimizing real power loss and operating cost. Installation costs of DSTATCOM devices and the cost of system operation, namely, energy loss cost due to both reconfiguration and DSTATCOM placement, are combined to form the objective function to be minimized. The distribution system tie switches, DSTATCOM location and size have been optimally determined to obtain an appropriate operational condition. In the proposed approach, the fuzzy membership function of loss sensitivity is used for the selection of weak nodes in the power system for the placement of DSTATCOM and the optimal parameter settings of the DFACTS device along with optimal selection of tie switches in reconfiguration process are governed by genetic algorithm(GA). Simulation results on IEEE 33-bus and IEEE 69-bus test systems concluded that the combinatorial method using DSTATCOM and reconfiguration is preferable to reduce power losses to 34.44% for 33-bus system and to 45.43% for 69-bus system.展开更多
A new method of model reduction combining the genetic algorithm（GA） with the Routh approximation method is presented. It is suggested that a high-order system can be approximated by a low-order model with a time del...A new method of model reduction combining the genetic algorithm（GA） with the Routh approximation method is presented. It is suggested that a high-order system can be approximated by a low-order model with a time delay. The denominator parameters of the reduced-order model are determined by the Routh approximation method, then the numerator parameters and time delay are identified by the GAL. The reduced-order models obtained by the proposed method will always be stable if the original system is stable and produce a good approximation to the original system in both the frequency domain and time domain. Two numerical examples show that the method is cornputationally simple and efficient.展开更多
A computationally efficient soft-output detector with lattice-reduction （LR） for the multiple-input multiple-output （MIMO） systems is proposed. In the proposed scheme, the sorted QR de- composition is applied on t...A computationally efficient soft-output detector with lattice-reduction （LR） for the multiple-input multiple-output （MIMO） systems is proposed. In the proposed scheme, the sorted QR de- composition is applied on the lattice-reduced equivalent channel to obtain the tree structure. With the aid of the boundary control, the stack algorithm searches a small part of the whole search tree to generate a handful of candidate lists in the reduced lattice. The proposed soft-output algorithm achieves near-optimal perfor- mance in a coded MIMO system and the associated computational complexity is substantially lower than that of previously proposed methods.展开更多
A cost-based selective maintenance decision-making method was presented.The purpose of this method was to find an optimal choice of maintenance actions to be performed on a selected group of machines for manufacturing...A cost-based selective maintenance decision-making method was presented.The purpose of this method was to find an optimal choice of maintenance actions to be performed on a selected group of machines for manufacturing systems.The arithmetic reduction of intensity model was introduced to describe the influence on machine failure intensity by different maintenance actions (preventive maintenance,minimal repair and overhaul).In the meantime,a resolution algorithm combining the greedy heuristic rules with genetic algorithm was provided.Finally,a case study of the maintenance decision-making problem of automobile workshop was given.Furthermore,the case study demonstrates the practicability of this method.展开更多
In this paper, H∞ optimal model reduction for singular fast subsystems will be inves-tigated. First, error system is established to measure the error magnitude between the original andreduced systems, and it is demon...In this paper, H∞ optimal model reduction for singular fast subsystems will be inves-tigated. First, error system is established to measure the error magnitude between the original andreduced systems, and it is demonstrated that the new feature for model reduction of singular systemsis to make H∞ norm of the error system finite and minimal. The necessary and su?cient conditionis derived for the existence of the H∞ suboptimal model reduction problem. Next, we give an exactand practicable algorithm to get the parameters of the reduced subsystems by applying the matrixtheory. Meanwhile, the reduced system may be also impulsive. The advantages of the proposedalgorithm are that it is more ?exible in a straight-forward way without much extra computation, andthe order of the reduced systems is as minimal as possible. Finally, one illustrative example is givento illustrate the e?ectiveness of the proposed model reduction approach.展开更多
针对多目标工艺规划与车间调度集成问题(multi-objective integrated process planning and scheduling,MOIPPS),以最小化完工时间和生产能耗最低为优化目标,提出了一种考虑全局和局部最优的改进混合优化算法。通过分析集成系统工艺设...针对多目标工艺规划与车间调度集成问题(multi-objective integrated process planning and scheduling,MOIPPS),以最小化完工时间和生产能耗最低为优化目标,提出了一种考虑全局和局部最优的改进混合优化算法。通过分析集成系统工艺设计和生产调度两个问题的区别与联系,搭建了多目标问题模型和解决框架。针对两阶段集成问题提出混合优化算法,对工艺阶段采用全局搜索算法,为集成系统提供多种工艺加工方案,保证集成算法的全局搜索性能;针对调度阶段设计一种改进禁忌搜索算法,通过交叉与随机抽样扩大解的分布范围,使用邻域禁忌搜索使得算法快速收敛,并采用Pareto非支配排序获得全局最优解。实验对比分析,验证了所提算法在求解多目标工艺规划与车间调度集成问题的高效性和稳定性。展开更多
在雷达通信一体化领域,设计出既能实现雷达探测功能又能实现通信信息传输功能的同波形信号是至关重要的一个环节。针对在雷达信号脉冲内对通信信息调制后自相关性能低的问题,提出一种高频带利用率以及低自相关旁瓣的基于非线性调频(NLFM...在雷达通信一体化领域,设计出既能实现雷达探测功能又能实现通信信息传输功能的同波形信号是至关重要的一个环节。针对在雷达信号脉冲内对通信信息调制后自相关性能低的问题,提出一种高频带利用率以及低自相关旁瓣的基于非线性调频(NLFM)信号的雷达通信一体化信号形式。将NLFM信号作为16阶正交幅度调制(16QAM)信号的载波,建立NLFM-16QAM雷达通信一体化信号模型,分析该信号的模糊函数以及相关的雷达与通信性能。在此基础上,针对所提出的NLFM-16QAM信号因其通信基带信号的随机性使雷达功能受到影响,从而降低了运动目标探测性能这一问题,将一体化系统的接收端作出改进,提出小波包降噪联合自然梯度算法对NLFM-16QAM信号进行接收处理。仿真结果表明,所提信号的频带利用率明显高于低阶调制的雷达通信一体化信号的频带利用率,在自相关性能方面,所提信号比16QAM-LFM信号的积分旁瓣比降低了23.07 d B,峰值旁瓣比降低了26.08 d B,NLFM-16QAM信号在经过改进接收端的联合算法处理后,运动目标的检测结果获得显著改善。展开更多
基金supported by the National Natural Science Foundation of China(6113900261171132)+4 种基金the Funding of Jiangsu Innovation Program for Graduate Education(CXZZ11 0219)the Natural Science Foundation of Jiangsu Education Department(12KJB520013)the Applying Study Foundation of Nantong(BK2011062)the Open Project Program of State Key Laboratory for Novel Software Technology,Nanjing University(KFKT2012B28)the Natural Science Pre-Research Foundation of Nantong University(12ZY016)
文摘Attribute reduction in the rough set theory is an important feature selection method, but finding a minimum attribute reduction has been proven to be a non-deterministic polynomial （NP）-hard problem. Therefore, it is necessary to investigate some fast and effective approximate algorithms. A novel and enhanced quantum-inspired shuffled frog leaping based minimum attribute reduction algorithm （QSFLAR） is proposed. Evolutionary frogs are represented by multi-state quantum bits, and both quantum rotation gate and quantum mutation operators are used to exploit the mechanisms of frog population diversity and convergence to the global optimum. The decomposed attribute subsets are co-evolved by the elitist frogs with a quantum-inspired shuffled frog leaping algorithm. The experimental results validate the better feasibility and effectiveness of QSFLAR, comparing with some representa- tive algorithms. Therefore, QSFLAR can be considered as a more competitive algorithm on the efficiency and accuracy for minimum attribute reduction.
基金Project(61273187)supported by the National Natural Science Foundation of ChinaProject(61321003)supported by the Foundation for Innovative Research Groups of the National Natural Science Foundation of China
文摘Region partition(RP) is the key technique to the finite element parallel computing(FEPC),and its performance has a decisive influence on the entire process of analysis and computation.The performance evaluation index of RP method for the three-dimensional finite element model(FEM) has been given.By taking the electric field of aluminum reduction cell(ARC) as the research object,the performance of two classical RP methods,which are Al-NASRA and NGUYEN partition(ANP) algorithm and the multi-level partition(MLP) method,has been analyzed and compared.The comparison results indicate a sound performance of ANP algorithm,but to large-scale models,the computing time of ANP algorithm increases notably.This is because the ANP algorithm determines only one node based on the minimum weight and just adds the elements connected to the node into the sub-region during each iteration.To obtain the satisfied speed and the precision,an improved dynamic self-adaptive ANP(DSA-ANP) algorithm has been proposed.With consideration of model scale,complexity and sub-RP stage,the improved algorithm adaptively determines the number of nodes and selects those nodes with small enough weight,and then dynamically adds these connected elements.The proposed algorithm has been applied to the finite element analysis(FEA) of the electric field simulation of ARC.Compared with the traditional ANP algorithm,the computational efficiency of the proposed algorithm has been shortened approximately from 260 s to 13 s.This proves the superiority of the improved algorithm on computing time performance.
基金supported by Borujerd Branch,Islamic Azad University Iran
文摘This work presents a fuzzy based methodology for distribution system feeder reconfiguration considering DSTATCOM with an objective of minimizing real power loss and operating cost. Installation costs of DSTATCOM devices and the cost of system operation, namely, energy loss cost due to both reconfiguration and DSTATCOM placement, are combined to form the objective function to be minimized. The distribution system tie switches, DSTATCOM location and size have been optimally determined to obtain an appropriate operational condition. In the proposed approach, the fuzzy membership function of loss sensitivity is used for the selection of weak nodes in the power system for the placement of DSTATCOM and the optimal parameter settings of the DFACTS device along with optimal selection of tie switches in reconfiguration process are governed by genetic algorithm(GA). Simulation results on IEEE 33-bus and IEEE 69-bus test systems concluded that the combinatorial method using DSTATCOM and reconfiguration is preferable to reduce power losses to 34.44% for 33-bus system and to 45.43% for 69-bus system.
文摘A new method of model reduction combining the genetic algorithm（GA） with the Routh approximation method is presented. It is suggested that a high-order system can be approximated by a low-order model with a time delay. The denominator parameters of the reduced-order model are determined by the Routh approximation method, then the numerator parameters and time delay are identified by the GAL. The reduced-order models obtained by the proposed method will always be stable if the original system is stable and produce a good approximation to the original system in both the frequency domain and time domain. Two numerical examples show that the method is cornputationally simple and efficient.
文摘A computationally efficient soft-output detector with lattice-reduction （LR） for the multiple-input multiple-output （MIMO） systems is proposed. In the proposed scheme, the sorted QR de- composition is applied on the lattice-reduced equivalent channel to obtain the tree structure. With the aid of the boundary control, the stack algorithm searches a small part of the whole search tree to generate a handful of candidate lists in the reduced lattice. The proposed soft-output algorithm achieves near-optimal perfor- mance in a coded MIMO system and the associated computational complexity is substantially lower than that of previously proposed methods.
基金Project(51105141,51275191)supported by the National Natural Science Foundation of ChinaProject(2009AA043301)supported by the National High Technology Research and Development Program of ChinaProject(2012TS073)supported by the Fundamental Research Funds for the Central University of HUST,China
文摘A cost-based selective maintenance decision-making method was presented.The purpose of this method was to find an optimal choice of maintenance actions to be performed on a selected group of machines for manufacturing systems.The arithmetic reduction of intensity model was introduced to describe the influence on machine failure intensity by different maintenance actions (preventive maintenance,minimal repair and overhaul).In the meantime,a resolution algorithm combining the greedy heuristic rules with genetic algorithm was provided.Finally,a case study of the maintenance decision-making problem of automobile workshop was given.Furthermore,the case study demonstrates the practicability of this method.
文摘In this paper, H∞ optimal model reduction for singular fast subsystems will be inves-tigated. First, error system is established to measure the error magnitude between the original andreduced systems, and it is demonstrated that the new feature for model reduction of singular systemsis to make H∞ norm of the error system finite and minimal. The necessary and su?cient conditionis derived for the existence of the H∞ suboptimal model reduction problem. Next, we give an exactand practicable algorithm to get the parameters of the reduced subsystems by applying the matrixtheory. Meanwhile, the reduced system may be also impulsive. The advantages of the proposedalgorithm are that it is more ?exible in a straight-forward way without much extra computation, andthe order of the reduced systems is as minimal as possible. Finally, one illustrative example is givento illustrate the e?ectiveness of the proposed model reduction approach.
文摘针对多目标工艺规划与车间调度集成问题(multi-objective integrated process planning and scheduling,MOIPPS),以最小化完工时间和生产能耗最低为优化目标,提出了一种考虑全局和局部最优的改进混合优化算法。通过分析集成系统工艺设计和生产调度两个问题的区别与联系,搭建了多目标问题模型和解决框架。针对两阶段集成问题提出混合优化算法,对工艺阶段采用全局搜索算法,为集成系统提供多种工艺加工方案,保证集成算法的全局搜索性能;针对调度阶段设计一种改进禁忌搜索算法,通过交叉与随机抽样扩大解的分布范围,使用邻域禁忌搜索使得算法快速收敛,并采用Pareto非支配排序获得全局最优解。实验对比分析,验证了所提算法在求解多目标工艺规划与车间调度集成问题的高效性和稳定性。
文摘在雷达通信一体化领域,设计出既能实现雷达探测功能又能实现通信信息传输功能的同波形信号是至关重要的一个环节。针对在雷达信号脉冲内对通信信息调制后自相关性能低的问题,提出一种高频带利用率以及低自相关旁瓣的基于非线性调频(NLFM)信号的雷达通信一体化信号形式。将NLFM信号作为16阶正交幅度调制(16QAM)信号的载波,建立NLFM-16QAM雷达通信一体化信号模型,分析该信号的模糊函数以及相关的雷达与通信性能。在此基础上,针对所提出的NLFM-16QAM信号因其通信基带信号的随机性使雷达功能受到影响,从而降低了运动目标探测性能这一问题,将一体化系统的接收端作出改进,提出小波包降噪联合自然梯度算法对NLFM-16QAM信号进行接收处理。仿真结果表明,所提信号的频带利用率明显高于低阶调制的雷达通信一体化信号的频带利用率,在自相关性能方面,所提信号比16QAM-LFM信号的积分旁瓣比降低了23.07 d B,峰值旁瓣比降低了26.08 d B,NLFM-16QAM信号在经过改进接收端的联合算法处理后,运动目标的检测结果获得显著改善。
