集群式智能型网络信息自动获取仿真分析  

Simulation Analysis of Automatic Acquisition of Cluster Intelligent Network Information

作　　者：夏晶晶 王飞[1] XIA Jing-jing;WANG Fei(School of Information Engineering,Henan University of Animal Husbandry and Economy,Zhengzhou Henan 450046,China;Zhengzhou University,Zhengzhou Henan 450001,China)

机构地区：[1]河南牧业经济学院信息工程学院,河南郑州450046 [2]郑州大学,河南郑州450001

出　　处：《计算机仿真》2023年第10期385-389,共5页Computer Simulation

摘　　要：为了在短时间内获取更多的有效信息,提出一种集群式智能型网络信息自动获取算法。将最大化网络信息采集量和最小化网络能耗作为目标,建立集群式智能型网络信息自动获取目标函数;在差分进化算法和引力搜索算法的基础上,提出GSADE算法对目标函数求解,完成集群式智能型网络信息的获取;引入肖维涅算法剔除上述信息中存在的误差数据,提高信息质量。实验结果表明,所提算法的网络生命周期长、能耗低、采集的有效信息量大、信息采集时延低,具有良好的信息获取性能。In order to obtain more effective information in a short time,this paper presented an cluster based intelligent network information automatic acquisition algorithm.In order to maximize the network information collection and minimize network energy consumption,we constructed a clustered intelligent network information for automatically capturing objective functions.Based on the differential evolution algorithm and gravitational search algorithm,GSADE algorithm was proposed to solve the objective function,thus completing the acquisition of clustered intelligent network information.Finally,Chauvenet algorithm was adopted to eliminate the error data in the information,thus improving the quality of information.Experimental results show that the proposed algorithm has a long network life and low energy consumption,and can collect large amount of effective information,with low acquisition delay as well as good acquisition performance.

关 键 词：集群式智能型网络 差分进化算法 引力搜索算法 肖维涅算法 信息获取 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]