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Optimal Operation and Output Oscillations Reduction of PEMFC by using an intelligent Strategy

INTERNATIONAL JOURNAL OF ELECTROCHEMICAL SCIENCE 2014年第8期9卷 4172-4189页

作者： Sarvi, M. Parpaei, M. Bagheri, H. Kojoori, M. R. Alkaei Imam Khomeini Int Univ Tech & Engn Fac Qazvin Iran

This paper presents a novel maximum power point control of stand-alone proton exchange membrane fuel cell (PEMFC) system using a novel optimization strategy based on the eagle strategy (ES) coupled with cuckoo optimization algorithm (COA) and particle swarm optimization (PSO) in order to track the maximum power point of PEMFC. The proposed method presents a new combination of optimization algorithms. According to this strategy, the advantages of optimization algorithms beside each other lead to reach better results in term of the convergence speed and the accuracy of the optimum operation of the system. Furthermore, the standard deviation of data produced by the proposed method is very lower than other conventional optimization algorithms;PSO and COA algorithms, so it leads to decrease the output power oscillation. To validate these advantages, the proposed tracker applied to the PEMFC system in MATLAB/SIMULINK environment. The simulation results confirm the effectiveness and accuracy of the proposed approach.

关键词： Maximum power point tracking intelligent optimization algorithm PEMFC Particle swarm optimization Cuckoo optimization algorithm

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Coarse and Fine-grained Crossover Free Search based Handover Decision Scheme with ABC Supported

Coarse and Fine-grained Crossover Free Search based Handover...

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第12届分布式计算及其应用国际学术研讨会

作者： WANG Tong WANG Xing-wei HUANG Min College of Information Science and Engineering Northeastern University

To find an optimal handover solution of terminal users under heterogeneous wireless networks, Pareto optimum under Nash equilibrium of users' utility and network provider utility is achieved or approached for the found solution. QoS(quality of service) requirements, user preferences to access network coding schemes, user preferences to access network providers, user handoff history record, costs user willing to pay and the profit of suppliers are considered comprehensively in this paper. With introducing the knowledge of fuzzy mathematics and microeconomics, access networks and terminals are described. With the help of gaming analysis, an intelligent handover decision scheme with ABC(always best connected) supported is proposed by using coarse-grained and fine-grained crossover free search based intelligent optimization algorithm. After carrying out simulation and performance evaluation, the results show that the mechanism proposed in this paper is feasible and effective.

关键词： NGI(next generation Internet) QoS(quality of service) ABC(always best connected) handover decision intelligent optimization algorithm search based on coarsegrained and fine-grained crossover

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Coarse and Fine-grained Crossover Free Search based Handover Decision Scheme with ABC Supported

Coarse and Fine-grained Crossover Free Search based Handover...

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12th International Symposium on Distributed Computing and Applications to Business, Engineering and Science (DCABES)

作者： Wang Tong Wang Xing-wei Huang Min Northeastern Univ Coll Informat Sci & Engn Shenyang Liaoning Provin Peoples R China

ISBN: (纸本)9780769550602

To find an optimal handover solution of terminal users under heterogeneous wireless networks, Pareto optimum under Nash equilibrium of users' utility and network provider utility is achieved or approached for the found solution. QoS (quality of service) requirements, user preferences to access network coding schemes, user preferences to access network providers, user handoff history record, costs user willing to pay and the profit of suppliers are considered comprehensively in this paper. With introducing the knowledge of fuzzy mathematics and microeconomics, access networks and terminals are described. With the help of gaming analysis, an intelligent handover decision scheme with ABC (always best connected) supported is proposed by using coarse-grained and fine-grained crossover free search based intelligent optimization algorithm. After carrying out simulation and performance evaluation, the results show that the mechanism proposed in this paper is feasible and effective.

关键词： NGI (next generation Internet) QoS (quality of service) ABC (always best connected) handover decision intelligent optimization algorithm search based on coarse-grained and fine-grained crossover

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Modeling and Simulation of Swarm Behaviors in Shoal of Fish

Modeling and Simulation of Swarm Behaviors in Shoal of Fish

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International Conference on Sensors, Measurement and intelligent Materials (ICSMIM 2012)

作者： Shen, Yiru Wang, Qiwei Southwest Univ Sci & Technol Mianyang Peoples R China

ISBN: (纸本)9783037856529

Based on the swarm behaviors in shoal of fish, this paper analyzes motion behavior of fish school when fish are foraging. This paper has simulated the pattern of motion behaviors for the fish school quantificationally. Using iterative and updating algorithm, it has modeled the 1-D procedure when fish school gradually approach food. These individual fish that constitute shoal of fish have finite perception and obey simple behavior rules. This paper further adopts modified intelligent optimization algorithm to model the process that individual fish interact with each other, changing position and velocity to gradually be close to food for the 2-D case. Experiment result shows the modified model successfully simulates the swarm behavior in shoal of fish when fish are looking for food, with small relative and absolute error.

关键词： swarm behavior iterative and updating algorithm intelligent optimization algorithm

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Research on Intelligence optimization of Web Service Composition for QoS

Research on Intelligence Optimization of Web Service Composi...

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3rd International Conference on Information Computing and Applications (ICICA 2012)

作者： Li, Jianjun Yu, Bin Chen, Wuping Zhengzhou Informat Sci & Technol Inst Zhengzhou 450004 Peoples R China

ISBN: (纸本)9783642340406

With quality of service as the restraint, in accordance with the features of service composition, this paper proposes an intelligent optimization algorithm for Web service composition. By combining a wide search range of shuffled frog leaping algorithm and high accuracy of particle swarm optimization algorithm, this algorithm can find the best one from a lot of service composition schemes. Simulation results show that the algorithm designed by this paper can overcome the low accuracy of shuffled frog leaping algorithm and instability of particle swarm optimization algorithm, and can find the better service composition scheme in all cases.

关键词： Web Service Composition Shuffled Frog Leaping algorithm Particle Swarm optimization algorithm intelligent optimization algorithm Quality of Service

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Optimal Search Mechanism Analysis of Light Ray optimization algorithm

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Journal of Mathematical Research with Applications 2012年第5期32卷 530-542页

作者： Jihong SHEN1,Jialian LI2,,Bin WEI1 1.College of Science,Harbin Engineering University,Heilongjiang 150001,P.R.China 2.College of Automation,Harbin Engineering University,Heilongjiang 150001,P.R.China College of Science Harbin Engineering University Heilongjiang 150001 College of Automation Harbin Engineering University Heilongjiang 150001

Based on Fermat's principle and the automatic optimization mechanism in the propagation process of light,an optimal searching algorithm named light ray optimization is presented,where the laws of refraction and reflection of light rays are integrated into searching process of *** this algorithm,coordinate space is assumed to be the space that is full of media with different refractivities,then the space is divided by grids,and finally the searching path is assumed to be the propagation path of light *** the law of refraction,the search direction is deflected to the direction that makes the value of objective function *** the law of reflection,the search direction is changed,which makes the search continue when it cannot keep going with *** the function values of objective problems are used and there is no artificial rule in light ray optimization,so it is simple and easy to *** analysis and the results of numerical experiments show that the algorithm is feasible and effective.

关键词： Fermat’s principle intelligent optimization algorithm light ray optimization optimal search mechanism.

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Simulation of Assembly Tolerance and Characteristics of High Pressure Common Rail Injector

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INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS 2011年第6期4卷 1282-1289页

作者： Lu, Jiping Tang, Shuiyuan Zhou, Yong Hong, Jing Jian, Zhonghua Beijing Inst Technol Sch Mech Engn Beijing 100081 Peoples R China CNGC ShanXi Diesel Engine Ind CO LTD Datong 037036 Peoples R China China N Ind Grp Co Inst Sci & Technol Beijing 100089 Peoples R China

Fuel injector is the key part of a high-pressure common rail fuel injection system. Its manufacturing precision and assembly quality affect system's property and performance. According to the characteristics and demands of assembly of the fuel injector, an intelligent optimization algorithm is proposed to resolve the problem of assembly sequence planning. Based on geometric modeling, assembly dimension chain of the injector control chamber is established, and the relationship between assembly tolerance and volume change of control chamber is analyzed. The optimization model of the assembly is established. The impact of assembly tolerance on injector's performance is simulated according to the optimization algorithm. The simulation result shows that quantity of injection fuel changes correspondingly with the change of assembly tolerance, while injection rate and pressure do not change significantly, and the response rate of needle considerably slow. Similarly, the leakage rate of fuel in control chamber is calculated, indicating that the assembly tolerance has obvious impact on fuel leakage and its rate. The study illuminates that injector's assembly tolerance has prominent effect on injection.

关键词： assembly tolerance intelligent optimization algorithm high pressure common rail simulation

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An optimal method for prediction and adjustment on byproduct gas holder in steel industry

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EXPERT SYSTEMS WITH APPLICATIONS 2011年第4期38卷 4588-4599页

作者： Zhang, Xiaoping Zhao, Jun Wang, Wei Cong, Liqun Feng, Weimin Dalian Univ Technol Res Ctr Informat & Control Dalian Peoples R China Shanghai Baosigh Software Co Ltd Shanghai Peoples R China

To maintain the balance of byproduct gas holder is an important task in optimal scheduling of byproduct energy in steel industry. However, this is often influenced by many factors and is difficult to obtain a precise mechanism model for analysis. In this paper, an optimal method for prediction and adjustment on byproduct gas holder is proposed. Considering the different operation styles of gasholders, both single and multiple gasholders level prediction models are established by machine learning methodology. And, a hybrid parameter optimization algorithm is developed to optimize the model for high prediction accuracy. Then, based on the predicted gasholder level, the optimal adjustment amount is calculated by a novel reasoning method to sustain the gasholder within safety zone. This method has been verified in the Energy Center of Baosteel, China. The results demonstrate that the proposed approach can precisely predict and adjust gasholders and provide a remarkable guidance for reasonable scheduling of byproduct gases. (C) 2010 Elsevier Ltd. All rights reserved.

关键词： Optimal scheduling of byproduct gases Gasholder level prediction Machine learning intelligent optimization algorithm

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Comparison of intelligent optimization algorithms for Crack Shape Reconstruction from ECT Signals

Comparison of Intelligent Optimization Algorithms for Crack ...

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IEEE International Conference on Mechatronics and Automation

作者： Zhang, Siquan Yang, Hefa Shanghai Univ Engn Sci Coll Air Transportat Shanghai Peoples R China Guangzhou Civil Aviat Coll Dept Mech Engn Guangzhou Peoples R China

ISBN: (纸本)9781424426928

intelligent optimization is a vibrant area of investigation, with some of the widely known and used approaches being Genetic algorithm, Ant Colony optimization and Particle Swarm optimization algorithm. An inversion] algorithm for the reconstruction of natural crack shape from eddy current testing signals is developed by using an artificial neural network based forward model and intelligent inversion algorithm. The true crack shapes and the measured eddy current testing signals are used to train the neural network. The parameters of the algorithms are modified, their effectiveness on crack shape inversion problem are compared and discussed. The reconstructed results verified the efficiency of neural network based forward model and the promising of intelligent optimization algorithms in crack shape inversion.

关键词： Eddy current testing Artificial neural network intelligent optimization algorithm Crack shape reconstruction

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Study on Optimal Scheduling Model and Technology Based on RPSO for Small Hydropower Sustainability

Study on Optimal Scheduling Model and Technology Based on RP...

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International Conference on Sustainable Power Generation and Supply

作者： Luo Yunxia Wang Wanliang Zhou Muxun Zhejiang Water Conservancy & Hydropower Coll Dept Elect Engn Hangzhou 310018 Peoples R China Zhejiang Univ Technol Coll Software Engn Hangzhou 310018 Peoples R China Taizhou Univ Coll Phys & Elect Engn Taizhou 317000 Peoples R China

ISBN: (纸本)9781424449347

In order to reduce the local environment impact, the improved methods of optimal scheduling small hydropower are discussed and the sustainability optimal scheduling models which composed of optimal objectives and constraints are presented. The controlled reservoir releases for hydropower generation which based on float coding is used as the decision variable of the model and the reserved minimum flow and reservoir water level as special constraints. The controlled reservoir water level compared with maximal energy output during the period of dispatching is considered as objective. An improved PSO, resilient particle swarm optimization (RPSO), is adopted to the optimization. In RPSO, the velocity of a particle is not dependent on the size of distance between the individual and the optimal particle but only dependent on its direction. An adaptive scheme is adopted to adjust the magnitude of the velocity resiliently. A simulation operation of RPSO Mat lab program for a factual small hydropower plant show that the sustainability optimum scheduling models and the technology based RPSO is viable and efficient. RPSO performance was compared with PSO and APSO on the same case, the results show that RPSO performed better.

关键词： intelligent optimization algorithm optimal scheduling optimal scheduling model optimal scheduling technology PSO reservoirs operation RPSO small hydropower sustainability water project management

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