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3rd International Conference on Manufacturing Science and Engineering (ICMSE 2012)

作者： Yu, Jinwei Weifang Univ Weifang Shandong Peoples R China

ISBN: (纸本)9783037853702

In the era of lead-free solder joints, nickel palladium gold PCB for its superior reliability and economy, more and more favored by the market, because the coating is added to palladium, SMT technology parameters have to be changed, to get solder joints of high reliability, therefore, analyzed quality factors of affecting solder joint formation of SMT process, rationally designed experiment program, obtained relative experimental data, analysis of larger speciality signal noise ratios and means, obtained optimizing SMT technology parameter for new nickel palladium gold plating, according to optimize results, improving SMT technology parameter, successfully applied nickel palladium gold PCB to SMT process,reduce cost, improve product quality, and achieved good economic benefit.

关键词： NiPdAu PCB SMT experiment parameter optimize

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On-demand optimize design of sound-absorbing porous material based on multi-population genetic algorithm

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E-POLYMERS 2020年第1期20卷 122-132页

作者： Wang, Yonghua Liu, Shengfu Wu, Haiquan Zhang, Chengchun Xu, Jinkai Yu, Huadong Changchun Univ Sci & Technol Minist Educ Key Lab Cross Scale Micro & Nano Mfg Changchun 130022 Peoples R China Jilin Univ Key Lab Bion Engn Minist Educ Changchun 130022 Jilin Peoples R China COMAC Shanghai Aircraft Design & Res Inst Shanghai 200120 Peoples R China

Porous material (PM) shows good sound absorption performance, however, the sound absorbing property of PM with different parameters are greatly different. In order to match the most suitable absorbing materials with the most satisfactory sound-absorbing performance according to the noise spectrum in different practical applications, multi-population genetic algorithm is used in this paper to optimize the parameters of porous sound absorbing structures that are commonly used according to the actual demand of noise reduction and experimental verification. The results shows that the optimization results of multi-population genetic algorithm are obviously better than the standard genetic algorithm in terms of sound absorption performance and sound absorption bandwidth. The average acoustic absorption coefficient of PM can reach above 0.6 in the range of medium frequency, and over 0.8 in the range of high frequency through optimization design. At a mid-to-high frequency environment, the PM has a better sound absorption effect and a wider frequency band than that of micro-perforated plate. However, it has a poor sound absorption effect at low frequency. So it is necessary to select suitable sound absorption material according to the actual noise spectrum.

关键词： multi-population genetic algorithm parameter optimize porous material

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Design and Optimization of Electric Continuous Variable Transmission System for Wind Power Generation

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IEEE TRANSACTIONS ON MAGNETICS 2016年第3期52卷 1-4页

作者： Wang, Yunchong Niu, Shuangxia Fu, W. N. Ho, S. L. Hong Kong Polytech Univ Hong Kong Hong Kong Peoples R China

A novel brushless electric continuous variable transmission (E-CVT) system is presented and optimized. The proposed system offers an alternative solution for a variable-speed constant-frequency operation of the wind turbine application. The key is to eliminate the gearbox and brushes in the machine and this E-CVT system comprises of two rotors and two stators within one machine. This design inherits and integrates the merits of the direct-drive permanent magnet generator and the doubly fed induction generator with the additional benefit of the improved torque density and the need for a low-cost partial-scale converter. The structure, operation principle, and performance are analyzed. Genetic algorithm is employed to optimize the parameters for maximizing its power density. Time-stepping finite-element method is used to analyze the dynamic performance of the proposed system.

关键词： Electric continuous variable transmission (E-CVT) genetic algorithm (GA) parameter optimize wind power

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parameters optimize method based on genetic and Simulated Annealing Algorithms

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INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE 2008年第1期22卷 169-181页

作者： Liu, Jiao-Min Wang, Jing-Hong Hebei Normal Univ Informat Technol Coll Shijiazhuang 050091 Peoples R China Hebei Univ Technol Tianjin 300130 Peoples R China

This paper gives an initial study on the comparison between Genetic Algorithm (GA) and Simulated Annealing Algorithm (SAA). Firstly, a new algorithm is presented. This method combines Genetic Algorithm and Simulated Annealing Algorithm, and it can be used to optimize the three parameters alpha, beta and gamma. It involes the rules that are extracted from Fuzzy Extension Matrix (FEM). These parameters play an important part in the entire process of rule extraction based on FEM. Secondly, it provides some theoretical support to the direct selection of the parameter values through experiments. Lastly, five data sets from the UCI Machine Learning centers are employed in the study. Experimental results and discussions are given.

关键词： parameter optimize fuzzy extension matrix genetic simulated annealing algorithm fuzzy entropy

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parameters optimize method based on genetic and Simulated Annealing Algorithms

Parameters optimize method based on genetic and Simulated An...

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5th International Conference on Machine Learning and Cybernetics

作者： Liu, Jiao-Min Wang, Jing-Hong Hebei Normal Univ Informat Technol Coll Shijiazhuang 050091 Peoples R China Hebei Univ Technol Tianjin 300130 Peoples R China

关键词： parameter optimize fuzzy extension matrix genetic simulated annealing algorithm fuzzy entropy

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Design and Optimization of Electric Continuous Variable Transmission System for Wind Power Generation

Design and Optimization of Electric Continuous Variable Tran...

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20th International Conference on the Computation of Electromagnetic Fields (Compumag)

作者： Wang, Yunchong Niu, Shuangxia Fu, W. N. Ho, S. L. Hong Kong Polytech Univ Hong Kong Hong Kong Peoples R China

关键词： Electric continuous variable transmission (E-CVT) genetic algorithm (GA) parameter optimize wind power

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A ROC Curve Method for Performance Evaluation of Support Vector Machine with Optimization Strategy

A ROC Curve Method for Performance Evaluation of Support Vec...

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International Forum on Computer Science-Technology and Applications

作者： Wang Xu-hui Shu Ping Cao Li Wang Ye CAAC Ctr Aviat Safety Technol Aviat Safety Inst Beijing Peoples R China Nanjing Univ Aeronaut & Astronaut Coll Civil Aviat Nanjing Jiangsu Peoples R China

ISBN: (纸本)9780769539300

Support vector machine is the highlight in machine learning. Also, performance evaluation and parameters selection for SVM model become an important issue to make it practically useful. In this paper, after investigating current evaluation index for pattern recognition, we introduced Receiver Operating Characteristic Curve into the performance evaluation. Area under Receiver Operating Characteristic Curve is applied to the model evaluation, model performance of SVM and RBFN is compared. Also optimal operating point of ROC is adopted to the optimization of SVM within the kernel parameters and penalty factor, and the optimization is performed by seeking of optimal operating point. Pattern recognition experiment with UCI dataset shows that ROC method is an effective approach for performance evaluation and optimization of SVM.

关键词： pattern recognition support vector machine parameter optimize ROC curve

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Attitude control for a quadrotor base on ADRC with GSO parameter optimization 30

Attitude control for a quadrotor base on ADRC with GSO param...

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30th Chinese Control and Decision Conference (CCDC)

作者： Che, Jianfeng Li, Dahua Ji, Yuehui Gao, Qiang Tianjin Univ Technol Tianjin Key Lab Control Theory & Applicat Complic Tianjin 300384 Peoples R China

ISBN: (纸本)9781538612446

A kind of attitude control strategy for the quadrotor based on active disturbance rejection control (ADRC) is proposed in this paper. Firstly, the dynamic model using Newton -Eulerformula of the quadrotor helicopter is developed. Then according to the order of dynamics equations design corresponding ADRC. Subsequently, in consideration of the characteristics of uncertain parameter of ADRC, the Glowworm Swarm Optimization(GSO) is designed to optimize the controller parameters so as to enhance the system performance. Finally, the comparative simulation for attitude of quadrotor is developed to verify the effectiveness of the proposed control strategy. The results of simulations show that the proposed controller possesses strong robustness and high performances.

关键词： Quadrotor Attitude Control ADRC Algorithm GSO Algorithm parameter optimize

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Selection of parameters based on fuzzy extension matrix

Selection of parameters based on fuzzy extension matrix

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5th International Conference on Machine Learning and Cybernetics

作者： Wang, Jing-Hong Liu, Jiao-Min Hebei Normal Univ Informat Technol Coll Shijiazhuang 050091 Peoples R China Hebei Univ Technol Tianjin 300130 Peoples R China

ISBN: (纸本)1424400600

Fuzzy extension matrix (FEM) inductive learning is an important method that generates knowledge from cases. Compared with conventional extension matrix techniques, it is more powerful and practical to handle with ambiguities in classification problems. Rule extraction from Fuzzy extension matrix involves three parameters alpha, beta and gamma. These parameters play an importation role in the entire process of rule extraction based on FEM. They greatly affect the computation of fuzzy entropy and extract rules, however those important parameter value are usually estimated based on users by domain knowledge, personal experience and requirements. This paper introduces an approach to optimization of the three parameters based GA, and provides some theoretical support of directly selection of the parameter values through experiment. The main contributions of this paper are as follows: by combining GA and local search methods, we can get the reasonable parameters. Five data sets from the UCI Machine Learning database are employed in the study. Experimental results and discussions are given.

关键词： extension matrix fuzzy extension matrix fuzzy entropy genetic algorithm parameter optimize

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SELECTION OF parameterS BASED ON FUZZY EXTENSION MATRIX

SELECTION OF PARAMETERS BASED ON FUZZY EXTENSION MATRIX

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2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)

作者： JING-HONG WANG JIAO-MIN LIU Information Technology College Hebei Normal University Shijiazhuang 050091 China Hebei University Hebei University of Technology Tianjin 300130 China

Fuzzy extension matrix (FEM) inductive learning is an important method that generates knowledge from *** with conventional extension matrix techniques, it is more powerful and practical to handle with ambiguities in classification problems. Rule extraction from Fuzzy extension matrix involves three parameters α, β and γ. These parameters play an importation role in the entire process of rule extraction based on FEM. They greatly affect the computation of fuzzy entropy and extract rules, however those important parameter value are usually estimated based on users by domain knowledge, personal experience and requirements. This paper introduces an approach to optimization of the three parameters based GA, and provides some theoretical support of directly selection of the parameter values through experiment. The main contributions of this paper are as follows: by combining GA and local search methods, we can get the reasonable parameters. Five data sets from the UCI Machine Learning database are employed in the study. Experimental results and discussions are given.

关键词： Extension matrix Fuzzy extension matrix Fuzzy entropy Genetic algorithm parameter optimize

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