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检索条件"主题词=Clonal selection algorithm"

共 233 条记录，以下是81-90 订阅

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Application of clonal selection algorithm in Construction Site Utilization Planning Optimization

Application of Clonal Selection Algorithm in Construction Si...

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International Conference on Sustainable Design, Engineering and Construction (ICSDEC)

作者： Wang, Xi Deshpande, Abhijeet S. Dadi, Gabriel B. Salman, Baris Univ Kentucky Dept Civil Engn 382 Raymond Bldg Lexington KY 40506 USA Univ Cincinnati Dept Civil & Architectural Engn & Construct Manag 795 Rhodes Hall Cincinnati OH 45220 USA Syracuse Univ Dept Civil & Environm Engn 151H Link Hall Syracuse NY USA

Various algorithms inspired by evolutionary and physical processes have been extensively applied in solving complex construction engineering optimization problems. In this paper, Artificial Immune Systems (AIS), a computational approach inspired by the processes of human immune system, is introduced in terms of its basic mechanisms and its applications in construction engineering. Specifically, clonal selection algorithm (CSA), one of main algorithms that form AIS, is based on clonal selection process of the immune system which includes the selection, hypermutation, and receptor editing processes. We discuss the CSA in detail and present its application in the classic construction optimization problem, construction site utilization planning (CSUP), which is the decision making process for identifying the most optimal layout of temporary facilities designed to support the construction process. When applied to a test case published in research literature, we found that CSA shows a robust capacity to search the solution space effectively and efficiently. (C) 2016 The Authors. Published by Elsevier Ltd.

关键词： Optimization Artificial Immune Systems clonal selection algorithm clonalG

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A clonal selection algorithm Based Optimization of Activated Sludge Process

A Clonal Selection Algorithm Based Optimization of Activated...

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2nd International Conference on Mechatronics and Intelligent Materials (MIM 2012)

作者： Du, Xianjun Hao, Xiaohong Yu, Ping Lanzhou Univ Technol Coll Elect & Informat Engn Lanzhou 730050 Gansu Peoples R China

ISBN: (纸本)9783037853849

A clonal selection algorithm (CSA) was used in this article to the wastewater biological treatment activated sludge process optimization with the lowest operational costs by limiting total substrate discharge mass. A simulation result shows that the method is efficiency, and it also provides a new approach for other optimal control problem.

关键词： clonal selection algorithm optimization activated sludge process wastewater biological treatment

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Improved real-valued clonal selection algorithm based on a novel mutation method

Improved real-valued clonal selection algorithm based on a n...

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International Symposium on Intelligent Signal Processing and Communication Systems

作者： Gong, Maoguo Jiao, Licheng Zhang, Lining Ma, Wenping Xidian Univ Inst Intelligent Informat Proc Xian 710071 Peoples R China

ISBN: (纸本)9781424414468

Chaos theory describes complex motion and the dynamics of nonlinear systems. As a complex nonlinear system, the immune system is chaotic. This paper introduces chaos into the clonal selection algorithm by a novel mutation method, self-adaptive chaotic mutation (SACM). In detail, based on the logistic chaotic sequence, SACM extracts antibody's affinity and distribution to adjust the mutation scale. Compared with the clonal selection algorithm using random mutation and Standard Genetic algorithm, the improved clonal selection algorithm can enhance the precision and stability, and overcome prematurity effectively with a high convergence speed.

关键词： clonal selection algorithm evolutionary computation chaos mutation

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A Generation Method of Immunological Memory in clonal selection algorithm by using Restricted Boltzmann Machines

A Generation Method of Immunological Memory in Clonal Select...

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IEEE International Conference on Systems, Man, and Cybernetics (SMC)

作者： Kamada, Shin Ichimura, Takumi Hiroshima City Univ Grad Sch Informat Sci Dept Intelligent Syst Asa Minami Ku 3-4-1 Ozuka Higashi Hiroshima 7313194 Japan Prefectural Univ Hiroshima Fac Management & Informat Syst Minami Ku Hiroshima 7348559 Japan

ISBN: (纸本)9781479986965

Recently, a high technique of image processing is required to extract the image features in real time. In our research, the tourist subject data are collected from the Mobile Phone based Participatory Sensing (MPPS) system. Each record consists of image files with GPS, geographic location name, user's numerical evaluation, and comments written in natural language at sightseeing spots where a user really visits. In our previous research, the famous landmarks in sightseeing spot can be detected by clonal selection algorithm with Immunological Memory Cell (CSAIM). However, some landmarks was not detected correctly by the previous method because they didn't have enough amount of information for the feature extraction. In order to improve the weakness, we propose the generation method of immunological memory by Restricted Boltzmann Machines. To verify the effectiveness of the method, some experiments for classification of the subjective data are executed by using machine learning tools for Deep Learning.

关键词： Image Analysis clonal selection algorithm Immunological Memory Cells Restricted Boltzmann Machines Deep Learning Smartphone based Participatory Sensing System Knowledge Discovery

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Improved clonal selection algorithm Optimizing Neural Network for Solving Terminal Anti-missile Collaborative Intercepting Assistant Decision-Making Model 1

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Joint Conference of the 16th Asia Simulation Conference / SCS International Autumn Simulation Multi-Conference (AsiaSim/SCS AutumnSim)

作者： Xiao, Jin-ke Li, Wei-min Xiao, Xin-rong Lv, Cheng-zhong Air Force Engn Univ Xian 710051 Peoples R China South China Univ Technol Guangzhou 510640 Guangdong Peoples R China

ISBN: (数字)9789811026669

ISBN: (纸本)9789811026669;9789811026652

Programming terminal high-low collaborative intercepting strategy scientifically and constructing assistant decision-making model with self-determination and intellectualization is one key problem to enhance operational efficiency. Assistant decision-making model has been constructed after analysis on collaborative intercepting principle;then Improved clonal selection algorithm Optimizing Neural Network (IclonalG-NN) is designed to solve the terminal anti-missile collaborative intercepting assistant decision-making model through introducing crossover operator to increase population diversity, introducing modified combination operator to make use of information before crossover and mutation, introducing population update operator into traditional clonalG to optimize Neural Network parameters. Experimental simulation confirms the superiority and practicability of assistant decision-making model solved by IclonalG-NN.

关键词： Terminal anti-missile system Collaborative intercepting Assistant decision-making clonal selection algorithm Neural network

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Determination of Slot Parameters of Band-Notched Ultra Wideband Antenna Using clonal selection algorithm 6

Determination of Slot Parameters of Band-Notched Ultra Wideb...

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6th International Conference on Computational Intelligence and Communication Networks

作者： Devi, R. Neog, Dipak Kr Dhemaji Coll Dept Elect Dhemaji Assam India

ISBN: (纸本)9781479969296

In this paper, a clonal selection algorithm based method is presented for the optimization of slot parameters embedded on ultra-wideband antennas to notch-out frequency bands to prevent interference between ultra wideband (UWB) systems and existing wireless systems. The method is applicable for both half-wavelength and quarter-wavelength slot-resonators. The effects of substrate properties are included in the proposed work. The method is validated by comparing the computed values with experimental values reported earlier. It shows very good agreement.

关键词： Notched resonant frequency clonal selection algorithm half-wavelength slot quarter-wavelength slot ultra wideband

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Design of clonal selection algorithm based PSS for Damping Power System Oscillations 1

Design of Clonal Selection Algorithm based PSS for Damping P...

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International Conference on Smart Electric Grid (ISEG)

作者： Naresh, G. Raju, M. Ramalinga Narasimham, S. V. L. Pragati Engn Coll Elect & Elect Engn Surampalem Andhra Pradesh India JNTUK Univ Coll Engn Kakinada Elect & Elect Engn Kakinada Andhra Pradesh India JNTUK Foreign Univ Relat Kakinada Andhra Pradesh India JNTUH Sch Informat Technol Comp Sci & Engn Hyderabad Andhra Pradesh India

ISBN: (纸本)9781479941049

Power System Stabilizers (PSS) are incorporated in the excitation system to enhance the damping of low frequency oscillations. In this paper, the design of multiple PSS in a multi-machine power system (MMPS) using clonal selection algorithm (CSA) has been proposed. The design problem of the PSS has been formulated as an optimization problem and CSA has been employed to search for optimal controller parameters. It has been shown that the stability performance of the system can be improved by minimizing the eigenvalue based objective function comprising of the damping factor and the damping ratio of the poorly damped electromechanical modes. Eigenvalue analysis and nonlinear simulation results have also been presented for various loading conditions and system configurations to show the effectiveness and robustness of the proposed controllers and their ability to provide efficient damping of low frequency oscillations.

关键词： Damping clonal selection algorithm Power System Stabilizer Multi-machine Power System

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Combining clonal selection algorithm and gene expression programming for time series prediction

Combining clonal selection algorithm and gene expression pro...

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3rd IEEE Intelligent Data Acquisition and Advanced Computing Systems

作者： Litvinenko, V. I. Bidyuk, P. I. Bardachov, J. N. Sherstjuk, V. G. Fefelov, A. A. Natl Tech Univ Ukraine Inst Appl Syst Anal Kiev Ukraine

ISBN: (纸本)9780780394452

Dynamic system identification algorithm is developed using the basic mechanisms of clonal selection and idea of a new, evolutionary computing paradigm - gene expression programming. On the basis of the algorithm developed a computer based system, is proposed for making decisions relevant to forecasting of single variable and multivariate lime series. The results of computing experiments achieved with the system developed show high quality of short and medium period forecasts.

关键词： artificial immune systems clonal selection algorithm gene expression programming time series

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Chaotic Immune clonal selection algorithm and Its Application

Chaotic Immune Clonal Selection Algorithm and Its Applicatio...

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2nd International Symposium on Knowledge Acquisition and Modeling

作者： Dai, Hongwei Li, Cunhua Huaihai Inst Technol Sch Comp Engn Lianyungang Jiangsu Peoples R China

ISBN: (纸本)9780769538884

Immune clonal selection algorithm (ICSA), based on the clonal selection theory proposed by Burnet, has gained much attention in the last decade. ICSA can exploit and explore the solution space in parallel and effectively. However, antibody random initialization and premature convergence are two problems of ICSA. To solve these problems, chaotic initialization mechanism and quantum interference mechanism are introduced into ICSA. Simulation results based on the traveling salesman problems have demonstrated the efficiency and robustness of the novel clonal selection algorithm.

关键词： clonal selection algorithm chaotic initialization quantum crossover hybrid

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Research of Hybrid Biogeography Based Optimization and clonal selection algorithm for Numerical Optimization

Research of Hybrid Biogeography Based Optimization and Clona...

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2nd International Conference on Swarm Intelligence (ICSI)

作者： Qu, Zheng Mo, Hongwei Harbin Engn Univ Automat Coll Harbin 150001 Peoples R China

ISBN: (纸本)9783642215155

The interest of hybridizing different nature inspired algorithms has been growing in recent years. As a relatively new algorithm in this field, Biogeography Based Optimization(BBO) shows great potential in solving numerical optimization problems and some practical problems like TSP. In this paper, we proposed an algorithm which combines Biogeography Based Optimization (BBO) and clonal selection algorithm (BBOCSA). Several benchmark functions are used for comparison among the hybrid and other nature inspired algorithms (BBO, CSA, PSO and GA). Simulation results show that clone selection can enhance the ability of exploration of BBO and the proposed hybrid algorithm has better performance than the other algorithms on some benchmarks.

关键词： Biogeography based optimization clonal selection algorithm Optimization

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