检索结果-内蒙古大学图书馆

2nd International Conference on Power, Control and Embedded Systems (ICPCES)

作者： Barisal, A. K. Sahu, N. C. Prusty, R. C. Hota, P. K. Veer Surendra Sai Univ Technol Dept Elect Engn Burla Orissa India ITER Dept Elect Engn Bhubaneswar Orissa India Coll Engn & Technol Bhubaneswar Orissa India

ISBN: (纸本)9781467310499;9781467310475

The Gravitational Search algorithm (GSA) is one of the recent additions to the new heuristic optimization algorithms based on law of gravity and mass interactions has been applied to solve the short term scheduling hydrothermal system. In the proposed algorithm, the searcher agents are collection of masses interact with each other based on the Newtonian gravity and the laws of motion. Hydrothermal scheduling involves the optimization of nonlinear objective function with set of operational and physical constraints. The cascading nature of hydro plants, water transport delay and scheduling time linkage, power balance constraints, variable hourly water discharge limits, reservoir storage limits, operation limits of thermal and hydro units, hydraulic continuity constraint and initial and final reservoir storage limits are fully taken into consideration. The validity and the performance of the proposed approach are demonstrated through a large hydrothermal test system comprising of 54 thermal and 44 hydro plants.

关键词： clonal selection algorithm gravitational search algorithm heuristic algorithm hydrothermal scheduling

来源：评论

学校读者我要写书评

暂无评论

Adaptive Control algorithm Based on Clone selection Optimization

Adaptive Control Algorithm Based on Clone Selection Optimiza...

引用

31st Chinese Control Conference

作者： Hu Jiangqiang Han Min Yin Jianchuan Li Tieshan Wang Hongzhen Li Zeyu Dalian Maritime Univ Nav Coll Dalian 116026 Peoples R China Dalian Univ Technol Sch Elect & Informat Engn Dalian 116024 Peoples R China

ISBN: (纸本)9789881563811

A clonal selection based adaptive control algorithm is developed by applying clonal selection algorithm to the adaptive control problem. For the dynamical uncertainty of both the plant and the environmental disturbance, the adaptive machine of clonal selection dopes out the plant output by a plant model according to the plant inputs, and then evaluates the candidate controllers before selecting the fittest controller to the current plant operating conditions. Thus the actual controller is tuned on-line to adapt the plant and environment. In simulations, a third order nonlinear model was adopted as a cargo ship, a second order linear model as its model, and the PID control law was applied to them. The results show that the proposed controller can adapt well the dynamical plant and the environmental disturbance.

关键词： artificial immunology clonal selection algorithm adaptive control candidate controller

来源：评论

学校读者我要写书评

暂无评论

REALIZING ARTIFICIAL IMMUNE SYSTEM IN A MULTI AGENT SIMULATION ENVIRONMENT AND AN APPLICATION TO TRAVELLING SALESMEN PROBLEM

JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GA...

引用

JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GAZI UNIVERSITY 2012年第4期27卷 901-909页

作者： Baykasoglu, Adil Saltabas, Alper Tasan, A. Serdar Subulan, Kemal Dokuz Eylul Univ Muhendislik Fak Endustri Muhendisligi Bolumu Izmir Turkey

Although many meta-heuristic algorithms were developed for solving combinatorial optimization problems, very few of them were realized in an agent based environment. Especially the algorithms which model dynamics of Artificial Immune Systems (AIS) are population based approaches with adaptability characteristics, therefore AIS can be better realized in an agent based modeling environment. For this purpose first time in the literature a clonal selection algorithm which is an AIS based algorithm is modeled in a multi-agent environment for solving the travelling salesmen problem which is a combinatorial optimization problem. In order to observe the behavior of the algorithm, simulation experiments are carried out on several test problems. Netlogo software is utilized for developing agent based models and simulation tests. Moreover, receptor change process and crossover mechanisms are integrated into the proposed model in order to improve the performance of the classical clonal selection algorithm. It is shown that there is a high potential to obtain good solution by making use of agent oriented approaches which more realistically model the natural phenomenon.

关键词： Agent based modeling and simulation artificial immune system clonal selection algorithm travelling salesmen problem

来源：评论

学校读者我要写书评

暂无评论

A Modified Flexible Bay and Slicing Structure for Unequal Area Facilities

引用

IFAC Proceedings Volumes 2012年第6期45卷 1635-1640页

作者： Berna ULUTAS Eskisehir Osmangazi University Department of Industrial Engineering 26480 Eskisehir TURKEY (Tel: +90-222-2393750

Facility layout problem deals with the arrangement of departments within a given particular area that is usually rectangular. Main objective in these problems is the minimization of the material handling costs between the departments. As the number of departments increases the problem is considered as NP complete. Exact solutions can be obtained only for rather small size problems. Therefore, heuristics are developed to generate near optimal solutions. This study considers departments that have unequal areas and utilize a clonal selection algorithm (CSA) to solve the problem. Departments are assigned to bays that are oriented vertically or horizontally. Twelve different versions of a well known unequal area test problem were studied to evaluate the performance of the algorithm. Eleven results generated better objective function values than the results in the accessible literature and one result obtained the best known value. Further, layouts generated for each test data were interpreted to visually evaluate the results.

关键词： clonal selection algorithm flexible bay structure slicing tree unequal area facility layout

来源：评论

学校读者我要写书评

暂无评论

Solving Job-shop Scheduling Problem by an Improved Genetic algorithm

Solving Job-shop Scheduling Problem by an Improved Genetic A...

引用

International Conference on Precision Engineering and Non-Traditional Maching (PENTM 2011)

作者： Yang Yanli Ke Weiwei Shenzhen Univ Coll Software Shenzhen 518060 Guangdong Peoples R China

ISBN: (纸本)9783037853184

An improved genetic algorithm is proposed by introducing selection operation and crossover operation, which overcomes the limitations of the traditional genetic algorithm, avoids the local optimum, improves its convergence rate and the diversity of population, and solves the problems of population prematurity and slow convergence rate in the basic genetic algorithm. Simulation results show that compared with other improved genetic algorithms, the proposed algorithm is better in finding global optimal and convergent rate.

关键词： Job shop schedule problem Genetic algorithm clonal selection algorithm

来源：评论

学校读者我要写书评

暂无评论

Quantitative Evaluation of Human-Reliability Based on Fuzzy-clonal selection

引用

IEEE TRANSACTIONS ON RELIABILITY 2011年第3期60卷 517-527页

作者： Wang, Ansi Luo, Yi Tu, Guangyu Liu, Pei Huazhong Univ Sci & Technol HUST Elect Power Secur & High Key Lab Dept Elect Engn Wuhan 430074 Peoples R China

Human reliability analysis (HRA) is necessary for system safety assessment as well as equipment reliability analysis. The cognitive reliability and error analysis method (CREAM) as a representative HRA method provides nine common performance conditions (CPCs) to represent the contextual conditions under which a given action is performed. With a scarcity of empirical data, a high uncertainty in analyzing results is produced by subjective judgment. To obtain more objective and effective HRA results, this paper presents an optimized quantification method to evaluate the human error probability (HEP) according to CREAM, and its linguistic variables. The starting point for the quantification is an introduced fuzzy version of CREAM. However, many fuzzy rules are redundant, and occupy extensive computing time. The clonal selection algorithm combined with the fuzzy model is proposed to optimize the rule set. The evaluation method using the fuzzy-clonal selection algorithm is aimed to support possible applications for prospective and retrospective studies in the domain of safety assessment of power systems. The simulations are carried out on four presumed contexts, and a practical power system. The conclusions illuminate the feasibility of the proposed quantitative method.

关键词： clonal selection algorithm cognitive reliability and error analysis method common performance conditions human error probability human reliability analysis power system

来源：评论

学校读者我要写书评

暂无评论

An improved clonal selection algorithm and its application to traveling salesman problems

引用

IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES 2007年第12期E90A卷 2930-2938页

作者： Gao, Shangce Tang, Zheng Dai, Hongwei Zhang, Jianchen Toyama Univ Fac Engn Toyama 9308555 Japan Tele Elect Supply Serv Co Ltd Takaoka Toyama 9391119 Japan

The clonal selection algorithm (CS), inspired by the basic features of adaptive immune response to antigenic stimulus, can exploit and explore the solution space parallelly and effectively. However, antibody initialization and premature convergence are two problems of CS. To overcome these two problems, we propose a chaotic distance-based clonal selection algorithm (CDCS). In this novel algorithm, we introduce a chaotic initialization mechanism and a distance-based somatic hypermutation to improve the performance of CS. The proposed algorithm is also verified for numerous benchmark traveling salesman problems. Experimental results show that the improved algorithm proposed in this paper provides better performance when compared to other metaheuristics.

关键词： clonal selection algorithm distance-based somatic hypermutation traveling salesman problem chaotic affinity

来源：评论

学校读者我要写书评

暂无评论

Position only pattern nulling of linear antenna array by using a clonal selection algorithm (clonalG)

引用

ELECTRICAL ENGINEERING 2007年第2期90卷 147-153页

作者： Guney, Kerim Babayigit, B. Akdagli, A. Erciyes Univ Dept Elect & Elect Engn TR-38039 Kayseri Turkey Erciyes Univ Dept Comp Engn TR-38039 Kayseri Turkey

In this paper, a clonal selection algorithm (clonalG) based on clonal selection principle of immune system has been used for null steering in the antenna radiation pattern by controlling only the element positions of a linear array. Numerical examples of Chebyshev pattern with the single, multiple and broad nulls imposed at the directions of interference are given to show the accuracy and flexibility of the clonalG. The sensitivity of the achieved patterns due to small variations of the element positions is also investigated by truncating the element positions.

关键词： pattern nulling linear antenna array evolutionary optimization clonal selection algorithm

来源：评论

学校读者我要写书评

暂无评论

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

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

引用

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

来源：评论

学校读者我要写书评

暂无评论

Reliable Server Assignment in Networks Using Nature Inspired Metaheuristics

引用

IEEE TRANSACTIONS ON RELIABILITY 2011年第2期60卷 381-393页

作者： Konak, Abdullah Kulturel-Konak, Sadan Penn State Berks Informat Sci & Technol Reading PA 19610 USA Penn State Berks Management Informat Syst Reading PA 19610 USA

In this paper, a reliable server assignment problem in networks is defined as determining a deployment of identical servers to maximize a measure of service availability, and solved using nature-inspired metaheuristic approaches, namely Ant Colony Optimization, Particle Swarm Optimization, and clonal selection Principle of Artificial Immune Systems. In networks, the communication between a client and a server might be interrupted because the server itself is offline or unreachable as a result of catastrophic network failures. Therefore, it is very important to deploy servers at critical network nodes so that the reliability of the system is maximized. A new reliability measure, called critical service rate, is defined to evaluate alternative server assignments with respect to the network's ability to provide services in the case of catastrophic component failures. The structure of the optimal server assignments is studied, and the performances of three nature inspired metaheuristics are investigated in a rigorous experimental study. Based on the computational studies, their advantages and disadvantages are discussed.

关键词： Ant colony optimization clonal selection algorithm particle swarm optimization reliable network design reliable server assignment

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：