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检索条件"主题词=artificial bee colony algorithm"

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artificial bee colony algorithm Based Interpretation Of Dissolved Gas Analysis

Artificial Bee Colony Algorithm Based Interpretation Of Diss...

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International Conference on Electrical, Electronics, Communication, Computer and Optimization Techniques (ICEECCOT)

作者： Akshatha S Rai C M Maheshan Karnataka Power Transmission Corporation Ltd. Bengaluru Karnataka India University Visvesvaraya Colllege of Engineering K.R. Circle Bengaluru Karnataka India

ISBN: (数字)9781728132617

ISBN: (纸本)9781728132624

Power Transformer being essential and costlier equipment in the power sector, maintaining its healthiness is a crucial task. Condition monitoring of transformers can help in predicting the kinds of fault and prevent the mishap. It can be achieved through Dissolved Gas Analysis. But interpretation of DGA to find the nature of fault that has occurred within transformer is a difficult job. There are many conventional methods like key gas method, Rogers ratio method, Duval triangle etc. These methods may not provide accurate and precise results in desired time. Therefore, modern heuristic methods can be helpful in reducing the computation time. One on such heuristic method is artificial bee colony algorithm. The results of this method are validated by comparing with the Fuzzy Inference System method on the basis of accuracy, precision, specificity and sensitivity.

关键词： artificial bee colony algorithm Gases Oil insulation Oils Power transformer insulation Optimization

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Optimum Design on In-wheel Motor of New Energy Vehicles based on Improved artificial bee colony algorithm 3

Optimum Design on In-wheel Motor of New Energy Vehicles base...

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3rd International Conference on Vision, Image and Signal Processing (ICVISP)

作者： Luo, Jie Zhang, Heshan Yuan, Chun Chongqing Vocat Coll Transportat Chongqing Peoples R China Chongqing Jiaotong Univ Chongqing Peoples R China

ISBN: (纸本)9781450376259

In order to improve the power density of the in-wheel motor and reduce its cost of materials. A multi-objective optimization method of in-wheel motor for electric vehicles (EV) is proposed based on an improved artificial colony algorithm. The new improved artificial colony algorithm is used to implement motor optimizing design with the geometry size and material parameters of motor as variables and the quality, cost and power consumption of the motor as the optimization goal. The results show that compared with conventional artificial colony algorithm, the convergence speed and global search ability of improved artificial colony algorithm is better and the quality, cost and power loss of optimized motor is relatively reduced, and the efficiency is improved.

关键词： Electric wheel out-rotor in-wheel motor artificial bee colony algorithm multi-objective optimization

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artificial bee colony algorithm Based On Self-Adaptive Greedy Strategy 10

Artificial Bee Colony Algorithm Based On Self-Adaptive Greed...

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10th International Conference on Advanced Computational Intelligence (ICACI)

作者： Yang, Zeyu Hu, Haidong Gao, Hao Nanjing Univ Posts & Telecommun Inst Adv Technol Nanjing Jiangsu Peoples R China Beijing Inst Control Engn Beijing Peoples R China

ISBN: (纸本)9781538643624

artificial bee colony algorithm is an effective optimization algorithm. In this paper, a novel artificial bee colony algorithm is developed based on a self-adaptive greedy strategy (SAGABC). Each bee should select whether adopts greedy strategy or not based on its fitness value on each generation. Individuals with worse fitness value update with non-greedy strategy then they have more opportunity to get a better score while individuals with better fitness value update with greedy strategy to speed up convergence. In other word, non-greedy part improves diversity of population which contributes to a better global searching ability. Finally, the experience results demonstrate that the developed method shows a competitive performance compared with traditional ABC and other optimization algorithms on a number of benchmark functions.

关键词： artificial bee colony algorithm greedy selection population diversity self-adaptive

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5D Magnetic Localization for Wireless Capsule Endoscopy Using the Levenberg-Marquardt Method and artificial bee colony algorithm 30

5D Magnetic Localization for Wireless Capsule Endoscopy Usin...

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30th IEEE Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

作者： Suveren, Memduh Kanaan, Muzaffer Erciyes Univ Dept Mechatron Engn Kayseri Turkey

ISBN: (纸本)9781538693582

In this study, magnetic positioning process is performed by WCE method which is mostly preferred in recent years. In order to make 5D magnetic positioning possible, two different algorithms were used to solve nonlinear mathematical dipole equations;artificial bee colony algorithm and Levenberg-Marquardt method. In case of using both algorithms separately and hybrid, performance comparison was made and the effect of noise on positioning error was investigated. As a result, we obtained a position error of less than 0.65 mm and orientation error of less than 0.8 degrees in the absence of noise and in case of noise addition, we had an average position error of 6.45 mm and a 9% angle error.

关键词： Wireless Capsule Endoscopy In Body Localization artificial bee colony algorithm Levenberg-Marquardt Method

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Indoor Emergency Evacuation Model Based on artificial bee colony algorithm 10

Indoor Emergency Evacuation Model Based on Artificial Bee Co...

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10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems - Technology and Applications (IDAACS)

作者： Zong, Xinlu Du, Jiayuan Liu, Wei Zhang, Lu Huang, Qian Hubei Univ Technol Coll Comp Sci Wuhan Peoples R China

ISBN: (纸本)9781728140698

In order to quickly and efficiently simulate the crowd movement process under the evacuation scene, so as to reduce the casualties in emergency evacuation, this article proposes an indoor emergency evacuation model based on the improved artificial swarm algorithm. In this article, the cellular automata (CA) model is used to establish the evacuation environment, and then the artificial bee colony (ABC) algorithm is used to simulate the crowd evacuation. However, due to too many obstacles existing in the neighboring cells of some position, the individual in that position have to wait. If the distance equation is used to calculate the fitness, it may cause other individuals to choose these positions as new position and repeat the same mistake above. To reduce the occurrence of such cases, we improve the fitness function of the ABC algorithm. In the fitness function, the factors of attraction and repulsion force in social force model are introduced. And on the basis of the ABC algorithm, we propose the visual employed bee. The visual employed bee leads the onlooker bee to evacuate, so as to improve the efficiency of evacuation. The research results of this article can provide ideas for evacuation modeling and useful guidance for formulating evacuation strategies to reduce evacuation time and disaster losses.

关键词： artificial bee colony algorithm cellular automaton model evacuation visual employed bee fitness function

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Airborne radar sub array partitioning method based on artificial bee colony algorithm 3

Airborne radar sub array partitioning method based on artifi...

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IEEE 3rd Information Technology, Networking, Electronic and Automation Control Conference (ITNEC)

作者： Zhang, Ze Su, Wentao Zhou, Kaifu Air Force Early Warning Acad Wuhan Hubei Peoples R China

ISBN: (纸本)9781538662434

Aiming at the problem of large amount of space-time adaptive processing technology for airborne early warning radar, a sub-array partitioning method based on artificial bee colony algorithm is proposed. The method uses the maximal improvement factor of the sub-array level as the optimization criterion, and uses the artificial bee colony algorithm to search for the optimal sub-matrix division method. Firstly, the basic principle of sub-array division is introduced, and then the sub-array division method of airborne early warning radar based on artificial bee colony algorithm is given in detail. The simulation analysis shows that compared with the traditional sub-matrix weighting method and the sub-array partitioning method based on genetic algorithm, the performance of the proposed space-time two-dimensional frequency response graph and improvement factor is significantly improved, and the actual performance of the current airborne early warning radar is improved. Engineering application has great reference value.

关键词： sub array division airborne early warning radar artificial bee colony algorithm

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Unmanned Aerial Vehicles Fleet Control via artificial bee colony algorithm 4

Unmanned Aerial Vehicles Fleet Control via Artificial Bee Co...

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4th Conference on Control and Fault Tolerant Systems (SysTol)

作者： Saied, Majd Slim, Malak Mazeh, Hussein Francis, Clovis Shraim, Hassan Lebanese Univ Fac Engn Res Sci Ctr Engn Hadath Lebanon

ISBN: (纸本)9781728103808

This paper considers a distributed planner method for multiple unmanned aerial vehicles (UAV), based on a leaderless approach, using an artificial bee colony (ABC) optimization algorithm. The ABC algorithm is a metaheuristic optimization method inspired by the intelligent behavior of the honeybee swarm. The proposed ABC, implemented on each UAV independently, is used to compute velocity profiles that avoid obstacles and collisions between the UAVs while ensuring the fleet formation control and the target tracking. The proposed algorithm is demonstrated by simulations on Matlab/Simulink in different scenarios.

关键词： Trajectory artificial bee colony algorithm Unmanned aerial vehicles Cost function Matlab Decentralized control

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Acceleration Harmonic Estimation using an Approach based artificial bee colony algorithm: A Hydraulic Shaking Table Application 27

Acceleration Harmonic Estimation using an Approach based Art...

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27th Signal Processing and Communications Applications Conference (SIU)

作者： Kockanat, Serdar Cumhuriyet Univ Elekt Elekt Muhendisligi Sivas Turkey

ISBN: (纸本)9781728119045

In this study, a harmonic estimation approach based artificial bee colony algorithm is proposed to identify and reduce the harmonic distortion caused by electrical and mechanical parts in the hydraulic shaking table. Reducing harmonic distortion and increasing acceleration in the hydraulic shaking table depend on modeling and cancelling of disruptive harmonics. Therefore, it is important to develop fast and accurate harmonic estimation applications. The proposed harmonic estimation approach was applied to the literature problems and the results were compared.

关键词： artificial bee colony algorithm hydraulic shaking table harmonic estimation

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An Adaptive Multi-population artificial bee colony algorithm for Multi-objective Flexible Job Shop Scheduling Problem 31

An Adaptive Multi-population Artificial Bee Colony Algorithm...

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31st Chinese Control And Decision Conference (CCDC)

作者： Cao, Yang Shi, Haibo Northeastern Univ Coll Informat Sci & Engn Shenyang 110819 Liaoning Peoples R China Chinese Acad Sci Shenyang Inst Automat Shenyang 110016 Liaoning Peoples R China Chinese Acad Sci Inst Robot & Intelligent Mfg Shenyang 110016 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China Chinese Acad Sci Key Lab Network Control Syst Shenyang 110016 Liaoning Peoples R China Shenyang Jianzhu Univ Informat & Control Engn Fac Shenyang 110168 Liaoning Peoples R China

ISBN: (纸本)9781728101057

In this paper, we propose a novel artificial bee colony algorithm for solving the multi-objective flexible job shop scheduling problem. In this algorithm, the whole population is divided into multiple subpopulations at each generation, and the size of each subpopulation is adaptively adjusted based on the information derived from its search results. Furthermore, the two mutation strategies implemented in the differential evolution algorithm are embedded in the proposed algorithm to facilitate the exchange of information in each subpopulation and between different subpopulations, respectively. Experimental results on the well-known benchmark multi-objective problems show that the improvements of the strategies are positive and that the proposed algorithm is better than or at least competitive to some previous multi-objective evolutionary algorithms.

关键词： multi-objective flexible job shop scheduling problem artificial bee colony algorithm multiple subpopulation

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BnbeeEpi: An Approach of Epistasis Mining Based on artificial bee colony algorithm Optimizing Bayesian Network

BnBeeEpi: An Approach of Epistasis Mining Based on Artificia...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Yang, Chen Gao, Hui Yang, Xuan Huang, Suiyu Kan, Yulong Liu, Jianxiao Huazhong Agr Univ Hubei Key Lab Agr Bioinformat Coll Informat Wuhan Peoples R China

ISBN: (纸本)9781728118673

Mining epistatic gene locus which influence complex disease has great research significance. Bayesian network (BN) has been widely used in many researches of epistasis mining. However, Bayesian network methods have disadvantages of being easily trapped into local optimum, low learning efficiency and not being able to handle large-scale network. In this work, we propose an epistasis mining approach based on artificial bee colony algorithm optimizing Bayesian network (BnbeeEpi). We apply artificial bee colony algorithm into the heuristic search strategy of Bayesian network, and then use two kinds of BN scoring functions (BIC and MIT) to calculate the network fitness value to avoid overfitting and reduce false positive rate. Moreover, we introduce decomposable BIC scoring to solve the large-scale network learning problem. Finally, we compare BnbeeEpi with current popular epistasis mining algorithms by using both simulated and real datasets. Experiment results show that omb-Fast has very short running time with its accuracy is as good as other methods, and BnbeeEpi has better F1-score and lower false positive rate compared to others.

关键词： Epistasis artificial bee colony algorithm Bayesian Network Markov Blanket

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