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RETRACTED: Modified hybrid algorithm for process optimization (Retracted article. See vol. 266, pg. 1177, 2015)

APPLIED MATHEMATICS AND COMPUTATION 2014年 232卷 1209-1224页

作者： Elhosseini, Mostafa A. Haikal, Amira Y. Mansoura Univ Fac Engn Comp Eng & Control Syst Dept Mansoura Egypt

The main weak points in using Al optimization techniques are the possibility of being trapped at local minima, being confined to the population space, difficulty to solve heavily nonlinear problems and to make full use of the historical information beside the lack of prediction about the search space. This paper is concerned with a hybrid optimization technique;namely cultural-based genetic algorithm MCBGA for solving multidimensional and nonlinear applications. The feature of proposed MCBGA technique is enhanced using biased initialization and dynamic parameters setting. Also elitism is carried out. The proposed approach has been carried out on pressure vessel design, fed-batch fermentor and continuous Stirred Tank Reactor CSTR test systems as well as Rastrigin, a well known standard workbench. The proposed MCBGA in terms of the diversity of the optimal solutions are obtained and compared to real coded genetic algorithm as well as other optimization techniques reported in the literature such as binary Genetic algorithm (GA), Particle Swarm Optimization (PSO) and its variants. The results obtained using the proposed algorithm are more accurate and the fast convergence is obvious. (c) 2014 Elsevier Inc. All rights reserved.

关键词： culture algorithm CSTR Fed-batch fermentor Genetic algorithm Pressure vessel Rastrigin

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Web service dynamic composition based on decomposition of global QoS constraints

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2013年第9-12期69卷 2247-2260页

作者： Liu, Zhi-Zhong Xue, Xiao Shen, Ji-quan Li, Wen-Rui Henan Polytech Univ Coll Comp Sci & Technol Jiaozuo 454000 Peoples R China Nanjing Xiaozhuang Univ Sch Math & Informat Technol Nanjing 211171 Jiangsu Peoples R China

Virtual enterprise is a temporary network of independent companies or enterprises that can quickly bring together to fulfill a value-added task. With the development of Web service technologies, the enterprise business systems can be encapsulated as Web services. Establishing a virtual enterprise is actually a process of Web service composition. As more and more Web services with the same functionalities and different Quality of Service (QoS) are available, QoS-aware Web service dynamic composition becomes an active research issue. Although several solutions have been provided for this issue, most of these methods based on global optimization, their poor performance render them inappropriate for applications with dynamic and real-time requirements. Moreover, these methods do not consider the commercial agreements and historical contact information between Web services with combination relationship. In this paper, we propose an approach for Web service dynamic composition based on global QoS constraints decomposition. The proposed method consists of three steps: Firstly, global QoS constraints are decomposed into local constraints optimally by a new algorithm named culture Genetic algorithm. Secondly, QoS values determination rules are designed to determine QoS values of candidate services. Thirdly, best Web services that can satisfy the local constraints are selected for each task during the running time. Experimental results show that our approach has better performance in solving the problem of QoS-aware Web service dynamic composition.

关键词： Web service dynamic composition Global QoS constraints decomposition Genetic algorithm culture algorithm

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Short-term optimal operation of Three-gorge and Gezhouba cascade hydropower stations in non-flood season with operation rules from data mining

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Energy Conversion and Management 2013年 65卷 616-627页

作者： Chao Ma Jijian Lian Junna Wang State Key Laboratory of Hydraulic Engineering Simulation and Safety Tianjin University Tianjin 300072 People’s Republic of China China Institute of Water Resources and Hydropower Research Beijing 100038 People’s Republic of China

Information hidden in the characteristics and relationship data of a cascade hydropower stations can be extracted by data-mining approaches to be operation rules and optimization support information. In this paper, with Three-gorge and Gezhouba cascade hydropower stations as an example, two operation rules are proposed due to different operation efficiency of water turbines and tight water volume and hydraulic relationship between two hydropower stations. The rules are applied to improve optimization model with more exact decision and state variables and constraints. They are also used in the population initiation step to develop better individuals with culture algorithm with differential evolution as an optimization method. In the case study, total feasible population and the best solution based on an initial population with an operation rule can be obtained with a shorter computation time than that of a pure random initiated population. Amount of electricity generation in a dispatch period with an operation rule also increases with an average increase rate of 0.025%. For a fixed water discharge process of Three-gorge hydropower station, there is a better rule to decide an operation plan of Gezhouba hydropower station in which total hydraulic head for electricity generation is optimized and distributed with inner-plant economic operation considered.

关键词： Short-term Optimal operation Cascade hydropower stations Operation rule culture algorithm Data mining

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An approach for composite web service selection based on DGQoS

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2011年第9-12期56卷 1167-1179页

作者： Wang, Zhi-Jian Liu, Zhi-Zhong Zhou, Xiao-Feng Lou, Yuan-Sheng Hohai Univ Coll Comp & Informat Engn Nanjing 210098 Peoples R China

Virtual enterprise is a temporary network of independent companies or enterprises that can quickly bring together to fulfill a value-added task. With the development of Web service technologies, the enterprise business systems can be encapsulated as Web services. Establishing a virtual enterprise is actually a process of Web services composition. As more and more Web services are available, many Web services with different quality of service (QoS) can be found for tasks of the composite Web service. Thus, a significant research problem in Web service composition is how to select the correct Web services for tasks such that the composite Web service gives the best overall quality. In this paper, we propose an approach to achieve Web services selection efficiently with excellent comprehensive quality. Firstly, a comprehensive evaluation model based on generic QoS (GQoS) and domain QoS (DQoS) of composite Web service is established. Secondly, a novel optimization algorithm named culture max-min ant system (C-MMAS) is constructed to solve the problem of Web service selection based on DGQoS. Simulations show that when used in Web service selection, C-MMAS is better than ant colony optimization algorithm and MMAS in efficiency.

关键词： Virtual enterprise Quality of service Composite web service Max-min ant system culture algorithm

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Modified cultural-based genetic algorithm for process optimization

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AIN SHAMS ENGINEERING JOURNAL 2011年第3-4期2卷 173-182页

作者： Haikal, Amira El-Hosseni, Mostafa Mansoura Univ Fac Engn Dept Syst & Comp Engn Mansoura Egypt Kafrelsheikh Univ Fac Engn Dept Elect Kafr Al Sheikh Egypt

The main weak points in using AI optimization technique are the possibility of being trapped at local minima, being confined to the population space, difficulty to solve heavily nonlinear problems and to make full use of the historical information beside the lack of prediction about the search space. In this paper, a hybrid optimization technique;namely culture-based genetic algorithm is proposed and tested against three multidimensional and highly nonlinear real world applications. This method proved to overcome most of these problems and the results showed that the proposed algorithm gives excellent performance for pressure vessel design and fed-batch fermentor problems. (C) 2011 Ain Shams University. Production and hosting by Elsevier B.V. All rights reserved.

关键词： culture algorithm CSTR Fed-batch fermentor Genetic algorithm Pressure vessel

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Urban power network substation optimal planning based on Geographic culture algorithm

Urban power network substation optimal planning based on Geo...

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IPEC 2007 Meeting

作者： Liu, Jun Gao, Haibo Zhang, Jianghua Dai, Bo North China Elect Power Univ Baoding Peoples R China

ISBN: (纸本)9789810594237

A novel intelligent algorithm, refined Geographic culture algorithm (GCA), is presented to handle optimal urban power planning about substation locating and sizing. culture algorithm consists of population space and belief space. The cultural algorithm is different with other integer optimization algorithm, since it is systematic, guidance, population space and belief space promote mutually by communication. GCA adopts the differential evolution algorithm (DE) as population space and proposes four kinds of strategies to constitute the belief space according to the urban power network characteristic. GCA is tested by a realistic planning project and compared with particle swarm optimization (PSO) to verify the effectiveness and feasibility.

关键词： urban power network planning of substation locating and sizing differential evolution algorithm culture algorithm GIS

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Urban Power Network Substation Optimal Planning Based on Geographic culture algorithm

Urban Power Network Substation Optimal Planning Based on Geo...

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2007 International Power Engineering Conference (IPEC2007), vol.2

作者： Jun LIU Haibo GAO Jianghua ZHANG Bo Dai North China Electric Power University China

关键词： Urban power network Planning of substation locating and sizing Differential evolution algorithm culture algorithm GIS

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The Study of SVM Optimized by culture Particle Swarm Optimization on Predicting Financial Distress

The Study of SVM Optimized by Culture Particle Swarm Optimiz...

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International Conference on Industrial Engineering and Engineering Management

作者： Zhou, Jianguo Bai, Tao Tian, Jiming Zhang, Aiguang N China Elect Power Univ Sch Business Adm Baoding 071003 Hebei Peoples R China

ISBN: (纸本)9781424426294

In this paper, we applied culture Particle Swarm Optimization algorithm (CPSO) to optimize the parameters of SVM. Utilizing the colony aptitude of particle swarm and the ability of conserving the evolving Knowledge of the culture algorithm, this CPSO algorithm constructed the population space based on particle swarm and the knowledge space. The two spaces evolved independently, at the same time, the population space continuously transferred the evolving knowledge to the knowledge space, and then the knowledge space to achieve global optimization. Additionally, the proposed CPSO-SVM model was test on the prediction of financial distress of listed companies in China. Then we compared the accuracies of CPSO-SVM with other models (Standard SVM, PSO-SVM and PSO-BPN). Experimental results showed that CPSO-SVM performed the best prediction accuracy and generalization.

关键词： Financial Distress culture algorithm Particle Swarm Optimization Support Vector Machine

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The Study of SVM Optimized by culture Particle Swarm Optimization on Predicting Financial Distress

The Study of SVM Optimized by Culture Particle Swarm Optimiz...

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IEEE International Conference on Automation and Logistics

作者： Zhou, Jianguo Bai, Tao Tian, Jiming Zhang, Aiguang N China Elect Power Univ Sch Business Adm Baoding 071003 Hebei Peoples R China

ISBN: (纸本)9781424425020

In the analysis of predicting financial distress based on Support Vector Machine (SVM), the two parameters of SVM, c and sigma, which its value have important effect on the predicting accuracy, must be predetermined carefully. In order to solve this problem, this paper proposed a new culture Particle Swarm Optimization algorithm (CPSO) to optimize the parameters of SVM. Utilizing the colony aptitude of particle swarm and the ability of conserving the evolving knowledge of the culture algorithm, this CPSO algorithm constructed the population space based on particle swarm and the knowledge space. The two spaces evolved independently, at the same time, the population space continuously transferred the evolving knowledge to the knowledge space, and then the knowledge space to achieve global optimization. Additionally, the proposed CPSO-SVM model that can automated to determine the optimal values of SVM parameters was test on the prediction of financial distress of listed companies in China. Then we compared the accuracies of CPSO-SVM with other models (Standard SVM, PSO-SVM and PSO-BPN). Experimental results showed that CPSO-SVM performed the best prediction accuracy and generalization, implying that the hybrid of CPSO with traditional SVM can serve as a promising alternative for predicting financial distress.

关键词： Financial Distress culture algorithm Particle Swarm Optimization Support Vector Machine

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