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检索条件"主题词=multi-objective genetic algorithm"

共 724 条记录，以下是141-150 订阅

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A multi-objective genetic algorithm Method to Support multi-Agent Negotiations

A Multi-Objective Genetic Algorithm Method to Support Multi-...

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2nd International Conference on Future Information Technology and Management Engineering

作者： Beheshti, R. Rahmani, A. T. Iran Univ Sci & Technol Dept Comp Engn Tehran Iran

ISBN: (纸本)9780769538808

Negotiations are among the most common ways that agents in a multi-agent system use to reach agreements. Because negotiations commonly are multi-lateral and multi-issue, these processes become more difficult. In the real world applications this becomes more important where the autonomous agents involved in a negotiation should reach maximum payoff in minimum time. In this work a new negotiation mechanism is proposed that is based on the multi-objective genetic algorithms. Several measures are defined that can show fitness of an offer in the set of feasible offers that an agent can have in each round of negotiations. The results show that this method can be used in real applications and is competitive with existing approaches.

关键词： Negotiation Autonomous agent multi-objective genetic algorithm

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Applying multi-objective genetic algorithm for Efficient Selection on Program Generation 28

Applying Multi-Objective Genetic Algorithm for Efficient Sel...

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28th Asia-Pacific Software Engineering Conference (APSEC)

作者： Watanabe, Hiroto Matsumoto, Shinsuke Higo, Yoshiki Kusumoto, Shinji Kurabayashi, Toshiyuki Kirinuki, Hiroyuki Tanno, Haruto Osaka Univ Grad Sch Informat Sci & Technol Suita Osaka Japan NTT Corp Tokyo Japan

ISBN: (纸本)9781665437844

Automated program generation (APG) is a concept of automatically making a computer program. Toward this goal, transferring automated program repair (APR) to APG can be considered. APR modifies the buggy input source code to pass all test cases. APG regards empty source code as initially failing all test cases, i.e., containing multiple bugs. Search-based APR repeatedly generates program variants and evaluates them. Many traditional APR systems evaluate the fitness of variants based on the number of passing test cases. However, when source code contains multiple bugs, this fitness function lacks the expressive power of variants. In this paper, we propose the application of a multi-objective genetic algorithm to APR in order to improve efficiency. We also propose a new crossover method that combines two variants with complementary test results, taking advantage of the high expressive power of multi-objective genetic algorithms for evaluation. We tested the effectiveness of the proposed method on competitive programming tasks. The obtained results showed significant differences in the number of successful trials and the required generation time.

关键词： Automated Program Generation Automated Program Repair multi-objective genetic algorithm

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Application of multi-objective genetic algorithm (MOGA) for Design Optimization of Valve Timing at Various Engine Speeds

Application of Multi-objective Genetic Algorithm (MOGA) for ...

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International Conference on Advances in Materials and Processing Technologies (AMPT)

作者： Mohiuddin, A. K. M. Rahman, Md. Ataur Shin, Yap Haw Int Islamic Univ Malaysia IIUM Dept Mech Engn Kuala Lumpur Malaysia

ISBN: (纸本)9783037850534

This paper aims to demonstrate the effectiveness of multi-objective genetic algorithm Optimization and its practical application on the automobile engine valve timing where the variation of performance parameters required for finest tuning to obtain the optimal engine performances. The primary concern is to acquire the clear picture of the implementation of multi-objective genetic algorithm and the essential of variable valve timing effects on the engine performances in various engine speeds. Majority of the research works in this project were in CAE software environment and method to implement optimization to ID engine simulation. The paper conducts robust design optimization of CAMPRO 1.6L (S4PH) engine valve timing at various engine speeds using multi-objective genetic algorithm (MOGA) for the future variable valve timing (VVT) system research and development. This paper involves engine modelling in ID software simulation environment, GT-Power. The GT-Power model is run simultaneously with mode Frontier to perform multi-objective optimization.

关键词： Optimization Valve timing multi-objective genetic algorithm GT-Suite

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Optimization Design and Evaluation of Shift Point for Electric Bus Based on multi-objective genetic algorithm 3

Optimization Design and Evaluation of Shift Point for Electr...

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3rd Conference on Vehicle Control and Intelligence (CVCI)

作者： Lei, Yulong Zhang, Jingxu Li, Xingzhong Zhang, Yuchen Fu, Yao Jilin univ State Key Lab Automot Simulat & Control Changchun Peoples R China Jilin univ Qingdao Automobile Res Inst Changchun Peoples R China

ISBN: (纸本)9781728126845

In this paper, an integrated simulation platform of electric bus based on AVL-Cruise and MATLAB is established to provide simulation basis for optimal design of shift point. By extracting the objective function, design variables and constraint conditions, a mathematical model for solving the shift point problem with multiple objectives is established. The NSGA-II algorithm was used to carry out multi-objective optimization design for the up-stop and down-stop points to obtain the pareto optimal solution. The optimal pareto solution was evaluated and analyzed by fuzzy comprehensive evaluation method, and the optimal results of shift MAP based on three cycle conditions were obtained. This paper evaluates and analyzes the optimal results of shift MAP based on working conditions from four aspects of power performance, economy, driving performance and braking energy recovery.

关键词： electric bus mechanical automatic transmission multi-objective genetic algorithm

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Gene Ranking: A Novel Approach Using multi-objective genetic algorithm 7

Gene Ranking: A Novel Approach Using Multi-Objective Genetic...

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7th International Conference on Reliability, Infocom Technologies and Optimization - Trends and Future Directions (ICRITO)

作者： Das, Priyojit Saha, Sujay Ghosh, Anupam Dey, Kashi Nath Natl Inst Technol Calicut Dept Comp Sci & Engn Kozhikode 673601 Kerala India Heritage Inst Technol Dept Comp Sci & Engn Kolkata 700107 W Bengal India Netaji Subhas Engn Coll Dept Comp Sci & Engn Kolkata 700152 W Bengal India Univ Calcutta Dept Comp Sci & Engn Kolkata 700009 W Bengal India

ISBN: (纸本)9781538646922

In a Gene Co-expression Network, the same or closely related genes are clustered into co-expressed groups. It is necessary to investigate the role that these genes play as far as some complex diseases like cancer are concerned in those networks. Ranking those genes actually discover the significant candidate genes for various types of cancers. There are several gene ranking algorithms proposed so far that produces the top ranked genes according to their importance with respect to a particular cancer disease. In this work, we apply multi-objective genetic algorithm, multi-objective Network GA, on a gene coexpression network to find the top ranked cancer mediating genes. The algorithm is applied to publicly available real-life cancer datasets taken from NCBI (National Centre for Biotechnology Information) biological online repository. The performance of the algorithm is justified by classification using SVM classifier with linear kernel and it is compared with state-of-the-art methods on the basis of percentage of accuracy, precision, recall, and F1-Score.

关键词： Microarray Gene Expression Data genetic algorithm multi-objective genetic algorithm PageRank HITS

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Optimal Design of Robot Wireless Transmission System Based on multi-objective genetic algorithm 5

Optimal Design of Robot Wireless Transmission System Based o...

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5th International Conference on Electromechanical Control Technology and Transportation (ICECTT)

作者： Fu Qi-ye Liu Wei Li You-hong Li Wei-yong Guangdong Aib Polytech Coll Intelligent Engn Coll Guangzhou Peoples R China Guangdong Univ Technol Huali Coll Guangzhou Peoples R China

ISBN: (数字)9781728199283

ISBN: (纸本)9781728199283

Wireless energy transmission technology is the key technology for robots to achieve lightweight, sustainable, and cable-free work. The magnetic coupling resonance wireless charging method, which must consider the impact of the working environment on the wireless energy transmission system, can be equivalent to the mutual inductance coupling circuit due to the eddy current effect of obstacles. In this paper, the transmission system was modeled by the coupled circuit theory, and the voltage gain coefficient transmission equation was derived. The characteristics of the wireless power transmission system under the influence of the eddy current effect was analysed. A coupling circuit for a wireless power transmission system was designed, and the system parameter values were obtained using MATLAB simulation. Through multi-objective genetic algorithm analysis, the parameter design of transmission system was optimized.

关键词： Wireless transmission MATLAB simulation metal obstacles multi-objective genetic algorithm

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A Novel scheme in Audio Watermarking using multi-objective genetic algorithm

A Novel scheme in Audio Watermarking using Multi-Objective G...

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8th International Conference on Mechatronics and Information Technology (ICMIT09)

作者： Majid, Abdul Javed, Tahir Choi, Tae-Sun Pakistan Inst Engn & Appl Sci Dept Informat & Comp Sci Islamabad Pakistan Gwangju Inst Sci & Technol Dept Mechatron Gwangju 500712 South Korea Allama Iqbal Open Univ Dept Comp Sci Islamabad Pakistan

ISBN: (纸本)9780819478115

In this paper, multi-objective genetic algorithm (MOGA) based novel watermarking scheme of audio signal is proposed. Using this MOGA scheme small size images are embedded efficiently as a digital watermark in the discrete wavelet domain of audio signal. The main advantage of proposed scheme is that it automatically selects the intensity of watermark for embedding in audio signal. As a result an optimal tradeoffs is obtained between two contradicting properties i.e. robustness and imperceptibility. The results obtained using the proposed MOGA technique show the embedded watermark is more robustness against common cropping and Gaussian noise attacks.

关键词： Audio Watermarking multi-objective genetic algorithm DWT Domain

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A multi-objective genetic algorithm for Pruning Support Vector Machines

A Multi-Objective Genetic Algorithm for Pruning Support Vect...

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23rd IEEE International Conference on Tools with Artificial Intelligence (ICTAI)

作者： Hady, Mohamed Farouk Abdel Herbawi, Wesam Weber, Michael Schwenker, Friedhelm Univ Ulm Inst Neural Informat Proc Ulm Germany Univ Ulm Inst Media Informat Ulm Germany

ISBN: (纸本)9780769545967

Support vector machines (SVMs) often contain a large number of support vectors which reduce the run-time speeds of decision functions. In addition, this might cause an overfitting effect where the resulting SVM adapts itself to the noise in the training set rather than the true underlying data distribution and will probably fail to correctly classify unseen examples. To obtain more fast and accurate SVMs, many methods have been proposed to prune SVs in trained SVMs. In this paper, we propose a multi-objective genetic algorithm to reduce the complexity of support vector machines as well as to improve generalization accuracy by the reduction of overfitting. Experiments on four benchmark datasets show that the proposed evolutionary approach can effectively reduce the number of support vectors included in the decision functions of SVMs without sacrificing their classification accuracy.

关键词： machine learning data mining Support vector machines multi-objective genetic algorithm

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Optimal Test Points Selection Based on multi-objective genetic algorithm

Optimal Test Points Selection Based on Multi-objective Genet...

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IEEE Circuits and Systems International Conference on Testing and Diagnosis

作者： Zhang, Yong Chen, Xixiang Liu, Guanjun Qiu, Jing Yang, Shuming Natl Univ Def Technol Coll Mechatron Engn & Automat Changsha 410073 Hunan Peoples R China

ISBN: (纸本)9781424425860

A new approach to select an optimal set of test points is proposed. The described method uses fault-wise table and multi-objective genetic algorithm to find the optimal set of test points. First, the fault-wise table is constructed whose entries are measurements associated with faults and test points. The problem of optimal test points selection is transformed to the selection of the columns that isolate the rows of the table. Then, four objectives are described according to practical test requirements. The multi-objective genetic algorithm is explained. Finally, the presented approach is illustrated by a practical example. The results indicate that the proposed method efficiently and accurately rinds the optimal set of test points and is practical for large scale systems.

关键词： Test points selection system testing design for testability multi-objective genetic algorithm

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Design and Optimization of Hybrid Excitation Synchronous Machine Based on multi-objective genetic algorithm

Design and Optimization of Hybrid Excitation Synchronous Mac...

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3rd IEEE Student Conference on Electrical Machines and Systems (SCEMS)

作者： Yang, Zhishuo Zhao, Wenliang Liu, Yan Wang, Xiuhe Kwon, Byung-il Shandong Univ Sch Elect Engn Jinan Peoples R China Hanyang Univ Dept Elect Syst Engn Ansan South Korea

ISBN: (纸本)9781728156224

To improve the electromagnetic performance of conventional hybrid excitation synchronous machine (HESM), a machine optimization method based on multi-objective genetic algorithm (MOGA) is proposed. The key idea is to improve the torque superposition by optimizing the shifting angle of permanent magnet (PM), thus to maximize the average output torque. The multi-objective global optimization method is used to comprehensively improve the torque and reduce the torque ripple and the amount of PMs. The effectiveness of the optimization scheme is verified by the finite element method (FEM), and the results show that the optimized model has higher average output torque and unit PM torque, as well as lower torque ripple when compared with the conventional model.

关键词： finite element method hybrid excitation synchronous machine multi-objective genetic algorithm torque superposition

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