Topology optimization of computer communication network based on improved genetic algorithm

IF 2.1 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Journal of Intelligent Systems Pub Date : 2022-01-01 DOI:10.1515/jisys-2022-0050
Hua Ai, Yuhong Fan, Jilei Zhang, K. Ghafoor
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引用次数: 1

Abstract

Abstract The topology optimization of computer communication network is studied based on improved genetic algorithm (GA), a network optimization design model based on the establishment of network reliability maximization under given cost constraints, and the corresponding improved GA is proposed. In this method, the corresponding computer communication network cost model and computer communication network reliability model are established through a specific project, and the genetic intelligence algorithm is used to solve the cost model and computer communication network reliability model, respectively. It has been proved that GA can solve the complex problems of computer working environment better, which is 80% higher than the general algorithm, and can select the optimal scheme pertinently.
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基于改进遗传算法的计算机通信网络拓扑优化
摘要研究了基于改进遗传算法(GA)的计算机通信网络拓扑优化问题,在给定成本约束下建立了基于网络可靠性最大化的网络优化设计模型,并提出了相应的改进遗传算法。该方法通过具体工程建立相应的计算机通信网络成本模型和计算机通信网络可靠性模型,并利用遗传智能算法分别求解成本模型和计算机通信网络可靠性模型。实践证明,遗传算法能较好地解决计算机工作环境中的复杂问题,比一般算法提高80%,并能有针对性地选择最优方案。
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来源期刊
Journal of Intelligent Systems
Journal of Intelligent Systems COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
5.90
自引率
3.30%
发文量
77
审稿时长
51 weeks
期刊介绍: The Journal of Intelligent Systems aims to provide research and review papers, as well as Brief Communications at an interdisciplinary level, with the field of intelligent systems providing the focal point. This field includes areas like artificial intelligence, models and computational theories of human cognition, perception and motivation; brain models, artificial neural nets and neural computing. It covers contributions from the social, human and computer sciences to the analysis and application of information technology.
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