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5th International Symposium on Intelligence Computation and Applications

作者： Li, Xia Liu, Kunqi Ma, Lixiao Li, Huanzhe Shijiazhuang Univ Econ Dept Comp Sci Shijiazhuang 050031 Peoples R China

ISBN: (纸本)9783642164927

This paper proposes a multi-child differential evolutionary agorithm(MCDE), and forms a concurrent-hybrid evolutionary algorithm by integrating the MCDE algorithm and Guotao algorithm based on variable searching subspace(VSSGT) into the culture algorithm framework. Numerical experiment results indicate that the performance of the proposed algorithm is better than that of MCDE, Differential Evolution algorithm(DE) and VSSGT, and better than that of the DE with double trial vectors based on Boltzmann mechanisin.

关键词： Differential evolutionary algorithm Multi-child Differential evolutionary algorithm Guotao algorithm based on variable searching subspace cultural algorithm Concurrent-Hybrid evolutionary algorithm

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Automatic generation control of a hybrid power system in deregulated environment utilizing GA, DE and CA tuned PID controller

Automatic generation control of a hybrid power system in der...

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IEEE Power, Communication and Information Technology Conference

作者： Himanshu Shekhar Biswa Ranjan Kuanr Gargi Konar Niladri Chakraborty Power Engineering Department Jadavpur University

ISBN: (纸本)9781479974566

In recent years the power scenario has gone through a major overhaul with the deregulation of electricity market and introduction of renewable sources into the system. Automatic generation control (AGC) is one of the important ancillary services present in the power system. This work represents an automatic generation control scheme for an interconnected three area hybrid power system in deregulated environment. Proposed scheme utilizes a classical Proportional-Integral-Derivative (PID) controller whose gain parameters K_p, K_i, K_d are tuned by Integral Square Error (ISE) control strategy using Genetic algorithm (GA), cultural algorithm (CA) and Differential Evolution (DE). A comparative study of dynamic response for frequency and tie-line confirms the superiority of cultural algorithm. In this work MATLAB/SIMULINK is used as a simulation tool.

关键词： Automatic generation control Deregulated power system cultural algorithm Differential evolution Hybrid power system

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Neural fuzzy inference systems with knowledge-based cultural differential evolution for nonlinear system control

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INFORMATION SCIENCES 2014年 270卷 154-171页

作者： Chen, Cheng-Hung Yang, Sheng-Yen Natl Formosa Univ Dept Elect Engn Huwei Township 632 Yunlin County Taiwan

This study proposes a knowledge-based cultural differential evolution (KCDE) method for neural fuzzy inference systems (NFIS). cultural algorithms acquire the belief space from the evolving population space and then exploit that information to guide the search. The proposed KCDE method adopts the mutation strategies of differential evolution as knowledge sources to influence the population space. The proposed KCDE method uses these knowledge sources, including normative knowledge, situational knowledge, domain knowledge, history knowledge, and topographic knowledge, to optimize the parameters of the NFIS model to avoid falling in a local optimal solution and to ensure the searching capacity of approximate global optimal solution. Experimental results demonstrate that the proposed NFIS-KCDE method performs well in nonlinear system control problems. (c) 2014 Elsevier Inc. All rights reserved.

关键词： cultural algorithm Differential evolution Neural fuzzy inference system Water bath temperature system Backing up the truck Ball and beam system

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A social intelligent system for multi-objective optimization of classification rules using cultural algorithms

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COMPUTING 2013年第4期95卷 327-350页

作者： Srinivasan, Sujatha Ramakrishnan, Sivakumar Cauvery Coll Women Dept Comp Sci Tiruchirappalli Tamil Nadu India AVVM Sri Pushpam Coll Dept Comp Sci Poondi Tamil Nadu India

cultural algorithms (CA) use social intelligence to solve problems in optimization. The CA is a class of evolutionary computational models inspired from observing the cultural evolutionary process in nature. cultural algorithms employ a basic set of knowledge sources, each related to knowledge observed in various animal species. Knowledge from these sources is then combined to influence the decisions of the individual agents in solving problems. Classification using "IF-THEN" rules comes under descriptive knowledge discovery in data mining and is the most sought out by users since they represent highly comprehensible form of knowledge. The rules have certain properties which make them useful forms of actionable knowledge to the users. The rules are evaluated using these properties represented as objective and subjective measures. The rule properties may be conflicting. Hence discovery of rules with specific properties is considered as a multi-objective optimization problem. In the current study an extended cultural algorithm which applies social intelligence in the data mining domain to present users with a set of rules optimized according to user specified metrics is proposed. Preliminary experimental results using benchmark data sets reveal that the algorithm is promising in producing rules with specific properties.

关键词： Multi-objective optimization Classification rules Evolutionary algorithms Social intelligence cultural algorithm Data mining

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Combining CA and PSO to Solve Flexible Job shop Scheduling Problem

Combining CA and PSO to Solve Flexible Job shop Scheduling P...

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26th Chinese Control and Decision Conference (CCDC)

作者： Zhou Wei Bu Yan-ping Zhou Ye-qing E China Univ Sci & Technol Sch Business Shanghai 200237 Peoples R China

ISBN: (纸本)9781479937066

The flexible job shop scheduling problem (FJSP) is an extension of the classic job shop scheduling problem (JSP), which breaks through the uniqueness of limit resources, allows a procedure in many machines processing and one machine processing many kinds of different types of procedures. It is more practical and complex than JSP. The computational complexity of FjSP is much higher, which disables exact solution methods and makes heuristic approaches more qualified. A hybrid optimization algorithm, CPSO, based on the cultural algorithm and particle swarm optimization algorithm, is proposed in this paper to solve the FJSP. The objective is to minimize makespan. Computational results show that this hybrid method is able to solve efficiently these kinds of problems.

关键词： cultural algorithm particle swarm optimization algorithm flexible job shop scheduling problem makespan

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An evolutionary heuristic algorithm for the assignment problem

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OPSEARCH 2014年第4期51卷 589-602页

作者： Ramadoss, Senthil Kumar Singh, Ajit Pal Mohiddin, Illauddin Kamaluddin Gulam Eritrea Inst Technol Dept Comp Sci Mai Nefhi Eritrea Def Univ Coll Engn Prod Engn Dept Mfg Engn Sect Bishoftu Ethiopia

An implementation of evolutionary heuristic algorithm, which is a specific modified variant of cultural algorithm, with simplified computational procedure is presented here for solving assignment problems. A cultural algorithm consists a population component almost identical to that of the genetic algorithm and, in addition, a knowledge component called the belief space. The major constraint of assignment problems that a single job can be assigned to only one resource and the resource or job that involves the largest and as well as the least cost are availed as the knowledge components to be used to build belief space.

关键词： cultural algorithm Belief space Genetic algorithm Assignment problem Optimization Heuristic algorithm Evolutionary algorithm

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cultural quantum-inspired shuffled frog leaping algorithm for direction finding of non-circular signals

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INTERNATIONAL JOURNAL OF COMPUTING SCIENCE AND MATHEMATICS 2013年第4期4卷 321-331页

作者： Gao, Hongyuan Xu, Congqiang Harbin Engn Univ Coll Informat & Commun Engn 145Nantong St Harbin 150001 Heilongjiang Peoples R China

In order to resolve complex continuous optimisation problem, a cultural quantum-inspired shuffled frog leaping (CQSFL) algorithm is proposed. The proposed CQSFL applies the quantum knowledge strategy and new quantum leaping equations to shuffled frog leaping algorithm, and thus has the advantages of low computational complexity and fast convergence. As a key step of CQSFL algorithm, leaping movement is modelled as guided cultural behaviour and thus may improve the capability of SFLA to find the optimal solution. Then we applied the proposed CQSFL algorithm in direction finding problem of non-circular signals, which is a hot spot in domain of communication. Then, based on CQSFL algorithm and non-circular maximum likelihood (NML) algorithm, a new direction finding method is proposed, which is called CQSFL-NML algorithm. Monte-Carlo simulations have proved that the CQSFL-NML method has good performance for non-coherent and coherent non-circular signals.

关键词： shuffled frog leaping algorithm cultural algorithm direction finding quantum computation non-circular signals

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A Social Metrics Based Process Model on Complex Social System

A Social Metrics Based Process Model on Complex Social Syste...

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IEEE Congress on Evolutionary Computation (CEC)

作者： Che, Xiangdong Reynolds, Robert G. Eastern Michigan Univ Coll Technol Ypsilanti MI 48197 USA Wayne State Univ Dept Comp Sci Detroit MI 48202 USA

ISBN: (纸本)9781479914883

In previous work, we investigated the performance of cultural algorithms (CA) over the complete range of system complexities in a benchmarked environment. In this paper the goal is to discover whether there is a similar internal process going on in CA problem solving, regardless of the complexity of the problem. We are to monitor the "vital signs" of a cultural system during the problem solving process to determine whether it was on track or not and infer the complexity class of a social system based on its "vital signs". We first demonstrate how the learning curve for a cultural System is supported by the interaction of the knowledge sources. Next a circulatory system metaphor is used to describe how the exploratory knowledge sources generate new information that is distributed to the agents via the Social Fabric network. We then conclude that the Social Metrics are able to indicate the progress of the problem solving in terms of its ability to periodically lower the innovation cost for the performance of a knowledge source which allows the influenced population to expand and explore new solution possibilities as seen in the dispersion metric. Hence we present the possibility to assess the complexity of a system's environment by looking at the Social Metrics.

关键词： cultural algorithm Complex Systems Optimization problem solving process

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Design and Implementation on cultural algorithm in Unit Commitment Optimization

Design and Implementation on Cultural Algorithm in Unit Comm...

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8th World Congress on Intelligent Control and Automation (WCICA)

作者： Zhou, Mu-Xun Wang, Zheng-Chu Luo, Yun-Xia Wang, Wan-Liang Taizhou Univ Sch Phys & Elect Engn Taizhou Zhejiang Peoples R China Taizhou Univ Sch Mech Engn Taizhou Zhejiang Peoples R China Zhejiang Coll Water Conservancy & Hydropower Dept Elect Engn Hangzhou Zhejiang Peoples R China Zhejiang Univ Technol Sch Comp Sci & Software Hangzhou Zhejiang Peoples R China

ISBN: (纸本)9781424467129

The paper develops research of feasibility and validity of Culture algorithm (CA) in unit commitment optimization. The mathematic model of the optimization problem is established. Realization method of CA is presented, including design of population space and culture space, design of acceptance function and influence function, and design of evolution strategies for two spaces. Solving steps of CA is realized, and Optimization calculation program based on MATLAB language is compiled. The results of example shows that CA, s perfect advantage is faster speed and better convergence performance, which is viable and efficient for unit commitment optimization.

关键词： cultural algorithm Unit Commitment Optimization Population Space Culture Space Acceptance Function Influence Function

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A Philosophy Illustration of cultural algorithm and Particle Swarm Optimization

A Philosophy Illustration of Cultural Algorithm and Particle...

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8th World Congress on Intelligent Control and Automation (WCICA)

作者： Si, Chengyong Li, Wenqi Wang, Lei Wang, Xihuai Tongji Univ Coll Elect & Informat Engn Shanghai 200092 Peoples R China Tongji Univ Analog Devices Technol Shanghai Inc Shanghai 200092 Peoples R China Shanghai Maritime Univ Coll Logist Engn Shanghai 200092 Peoples R China

ISBN: (纸本)9781424467129

Swarm intelligence algorithm as a new bionics evolutionary algorithm has attracted many researchers' attention for its simplicity, efficiency and easy realization. This paper tries to explain the basic principle of cultural algorithm and Particle Swarm Optimization from the standpoint of philosophy, and later some examples of function optimization are used to illustrate it, which provides a new way for the research of swarm intelligence algorithm.

关键词： cultural algorithm particle swarm optimization philosophy function optimization

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