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检索条件"主题词=State transition algorithm"

共 69 条记录，以下是21-30 订阅

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Evaluation of Wireless Sensor Networks Based on state transition algorithm and Fuzzy TOPSIS 34

Evaluation of Wireless Sensor Networks Based on State Transi...

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34th Chinese Control and Decision Conference (CCDC)

作者： Tan, Wan Zhou, Xiaojun Sun, Yan Cent South Univ Sch Automat Changsha 410083 Peoples R China

ISBN: (纸本)9781665478960

Many exsting interval-valued intuitionistic fuzzy multiattribute decision making methods in evaluating wireless sensor networks (WSNs) are baesd on real-valued measures, which may lose divergence information and affect the accuracy of decision making. In this paper, a novel similarity-divergence measure of interval-valued intuitionistic fuzzy values is proposed, which can overcome the drawbacks of real-valued measures, and the rationality of the proposed measure is further proved. The measure is applied to calculate fuzzy similarities of each alternative and a TOPSIS method is developed to obtain the preference order of the alternatives. Considering the different importance of each attribute, a nonlinear optimization model is constructed, and the state transition algorithm (STA) is used to determine the attribute weights. Finally, the proposed method is used to evaluate the designed WSNs. The experimental results verify the effectiveness and superiority of the proposed approach in solving multiattribute decision making problems.

关键词： Wireless sensor network Performance evaluation Similarity-divergence measure Interval-valued intuitionistic fuzzy set state transition algorithm

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A multi-threshold image segmentation approach using state transition algorithm 34

A multi-threshold image segmentation approach using state tr...

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第三十四届中国控制会议

作者： HAN Jie ZHOU Xiaojun YANG Chunhua GUI Weihua School of Information Science and Engineering Central South University

ISBN: (纸本)9781467374439

Thresholding is an important approach for image segmentation and analysis. In this study, the combination of normal distribution functions is used to t the normalized histogram of the original image since each normal distribution function represents a pixel class. On the other hand, state transition algorithm(STA) is a promising method for solving complex optimization problems. By transforming the tting problem into an optimization problem, the STA is used to select the optimal parameters in the tting function. Experimental results of several images show that the proposed approach is ef cient and effective for multilevel thresholding problems. Comparisons with OTSU, PSO and GA also demonstrate that STA not only outperforms computationally ef cient but also provides competitive thresholding results.

关键词： Image segmentation state transition algorithm Multilevel thresholding

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Data-Driven Based state transition algorithm for Dynamic Optimization

Data-Driven Based State Transition Algorithm for Dynamic Opt...

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IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Zhang, Yunxiang Zhou, Xiaojun Yang, Chunhua Cent South Univ Sch Automat Changsha 410083 Peoples R China

ISBN: (纸本)9781728124858

Most evolutionary algorithms solve the optimization problems by iteratively calculating the values of the objective functions. However, such explicit objective functions may not exist in solving many process industry optimization problems, especially when these processes have time varying dynamics, instead costly physical experiments should be conducted to evaluate the fitness values, which hinders the application of evolutionary algorithms. In this paper, a novel dynamic optimization technique based on data-driven state transition algorithm (STA) is investigated to solve the aforementioned issue. Firstly, the control vector parameterization (CVP) method is used to discretize the control variables, and control variable vectors are used to approximate the control trajectories. By means of costly experiments, data pairs are obtained by combining variable vectors and their corresponding fitness. Then, a novel method is proposed to obtain the optimal variable vector based on data-driven STA. By applying it in two well-known dynamic optimization instances, simulation results demonstrate that the proposed approach is able to obtain better optimization results than other methods with a limited budget of exact function evaluations.

关键词： state transition algorithm Dynamic optimization Control vector parametrization Data-driven

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A multi-objective state transition algorithm for continuous optimization 36

A multi-objective state transition algorithm for continuous ...

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第36届中国控制会议

作者： Jiajia Zhou Xiaojun Zhou Chunhua Yang Weihua Gui School of Information Science and Engineering Cental South University

ISBN: (纸本)9781538629185

This paper proposes a new approach called multi-objective state transition algorithm(MOSTA) which incorporates state transition algorithm with the concept of Pareto dominance to solve continuous multi-objective optimization *** on an incumbent best solution,candidate solutions are generated using state transformation operators by sampling,and then the next best solution is chosen from a sorted set consisting of solutions in the first rank and then stored in an ***,MOSTA inherits the distance operator to make solutions uniformly distributed in pareto *** results of several standard benchmark test functions illustrates that this approach is *** using convergence metric and spacing metric for evaluation,it shows fast convergence and solutions could approximate to true pareto front,which indicates that multi-objective state transition algorithm(MOSTA) is a promising approach.

关键词： multi-objective optimization state transition algorithm Pareto dominance

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Dynamic Optimization using Control Vector Parameterization with state transition algorithm 36

Dynamic Optimization using Control Vector Parameterization w...

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第36届中国控制会议

作者： Miao Huang Xiaojun Zhou Chunhua Yang Weihua Gui School of Information Science and Engineering Cental South University

ISBN: (纸本)9781538629185

In real-world applications,a majority of optimization problems belong to dynamic optimization,which involves optimization over time and whose underlying space is *** this paper,a novel dynamic optimization technique based on state transition algorithm(STA) is investigated to solve dynamic optimization problems(DOPs).Firstly,an infinite dynamic optimization problem is converted into a finite nonlinear programming problem(NLP) based on the control vector parameterizations(CVP),in which,instead of discretizing both state and control variables,only the control profiles are approximated by piecewise constant ***,a stochastic global method is proposed to solve the resulting nonlinear programming problem based on state transition *** applying it in two well-known dynamic optimization instances,simulation results show that the proposed approach is able to obtain similar or even better performance indicators compared with other methods in terms of computational cost,solution accuracy and stability.

关键词： state transition algorithm dynamic optimization control vector parameterization

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The Concept on Nonlinear Modelling of Dynamic Objects Based on state transition algorithm and Genetic Programming 1

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16th International Conference on Artificial Intelligence and Soft Computing (ICAISC)

作者： Bartczuk, Lukasz Dziwinski, Piotr Red'ko, Vladimir G. Czestochowa Tech Univ Inst Computat Intelligence Czestochowa Poland Russian Acad Sci Sci Res Inst Syst Anal Moscow Russia

ISBN: (数字)9783319590608

ISBN: (纸本)9783319590608;9783319590592

In this paper a new hybrid method to determine parameters of time-variant non-linear models of dynamic objects is proposed. This method first uses the state transition algorithm to create many local models and then applies genetic programming in order to join and simplify those models. This allows to obtain simply model which is not computationally demanding and has high accuracy.

关键词： Nonlinear modelling state transition algorithm Genetic programming Cooperative coevolution

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On the Order of Operators in the Continuous state transition algorithm 41

On the Order of Operators in the Continuous State Transition...

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第41届中国控制会议

作者： Shuang Fang Xiaojun Zhou Jituo Tian School of Automation Central South University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In order to investigate the influence of the order of operators in the continuous state transition algorithm on its optimization performance,this paper comprehensively considers six kinds of operator orders and four different dimensions of the decision space and carries out experiments on benchmark *** comparing the optimality,the robustness and the convergence speed of the experimental results,it is shown that the order of operators has no obvious effect on the optimization performance of the continuous state transition algorithm in the same dimension ***,it also has good adaptability to the dimension of decision *** means that the state transition algorithm has good robustness to the order of the operators and the potential to deal with high dimensional optimization *** work is not only of great significance for improving the theoretical basis of the state transition algorithm,but also provides some insight for the further evolution of the state transition algorithm.

关键词： state transition algorithm the order of operator optimality robustness convergence speed

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A continuous state transition algorithm with guaranteed optimality 35

A continuous state transition algorithm with guaranteed opti...

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35th Chinese Control and Decision Conference (CCDC)

作者： Zhou, Liwei Zhang, Yuwen Zhou, Xiaojun Cent South Univ Sch Automat Changsha 410083 Peoples R China

ISBN: (纸本)9798350334722

As a constructivism-based intelligent optimization method, the state transition algorithm (STA) has exhibited powerful search ability in optimization. However, in basic STA, it usually sets the maximum number of iterations or function evaluations as the termination condition by experience. If the termination condition is not set well, it may stop at an unpredictable point. In this study, a continuous STA with guaranteed optimality is proposed by altering the termination conditions of the basic STA, without using the maximum number of iterations or function evaluations. It is proved that the modified STA can find a final solution with guaranteed optimality. Experimental results have testified the findings.

关键词： state transition algorithm intelligent optimization continuous optimization optimality termination condition

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A state transition algorithm with Variable Local Candidate Solution Space and its application to Residue Hydrogenation Fractionation Process

A State Transition Algorithm with Variable Local Candidate S...

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Chinese Automation Congress (CAC)

作者： Yi, Kemin Wang, Yalin Sun, Bei Sun Jiazhou Cent South Univ Sch Automat Changsha 410083 Hunan Peoples R China

ISBN: (纸本)9781728176871

Parameter Optimal state transition algorithm (POSTA) is a global metaheuristic method with adaptive parameter adjustment capabilities. However, its fixed local search candidate solution space easily leads to the computational redundancy and the problems that are difficult to jump out of local optimization. Therefore, a novel state transition algorithm with variable local candidate solution space is proposed in this paper, called VLCSSSTA. First, a dynamic logic of distance control is designed to speed up the search, which adaptively changes the size of the candidate solution space. Then, the larger candidate solutions are randomly generated to enhance the ability to jump out of the local optimum. Statistical research results show that the proposed algorithm has better performance than POSTA and some classic optimization algorithms in five benchmark function experiment. Finally, the proposed method is applied to the operation optimization in residue hydrogenation fractionation (RHF). The experimental results also verify the effectiveness of the proposed method.

关键词： state transition algorithm distance control local optimum operation optimization residue hydrogenation fractionation

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A discrete state transition algorithm for the task assignment problem 34

A discrete state transition algorithm for the task assignmen...

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第三十四届中国控制会议

作者： DONG Tianxue ZHOU Xiaojun YANG Chunhua GUI Weihua School of Information Science and Engineering Central South University

ISBN: (纸本)9781467374439

A novel discrete state transition algorithm(STA) is proposed for solving the Task Assignment Problems(TAP) in this study. The commonly used formulation of TAP is reconstructed to transform the constrained optimization problem into an unconstrained one by establishing an one-to-one mapping between a matrix solution of TAP and a vector permutation so that it can be well addressed by the STA. In order to enhance the search ability of original discrete STA, a strategy of second transition is designed to explore more search space. Several experimental tests are given to evaluate the performance of the proposed method,and the results have testified the effectiveness of the improved discrete STA.

关键词： Task assignment problem Integer optimization state transition algorithm Second transition

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