{"title":"一种无线传感器网络可靠性优化算法","authors":"Qiuming Zhang, Jing Luo","doi":"10.3991/IJOE.V14I06.8704","DOIUrl":null,"url":null,"abstract":"Aiming at the reliability optimization algorithm based on wireless sensor network, a data fusion algorithm based on extreme learning machine for wireless sensor network was proposed according to the temporal spatial correlation in data collection process. After analyzing the principles, design ideas and implementation steps of extreme learning machine algorithm, the performance and results were compared with traditional BP algorithm, LEACH algorithm and RBF algorithm in simulation environment. The simulation results showed that the data fusion optimization algorithm based on the limit learning machine for wireless sensor network was reliable. It improved the efficiency of fusion and the comprehensive reliability of the network. Thus, it can prolong the life cycle and reduce the total energy consumption of the network.","PeriodicalId":387853,"journal":{"name":"Int. J. Online Eng.","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Reliability Optimization Algorithm for Wireless Sensor Network\",\"authors\":\"Qiuming Zhang, Jing Luo\",\"doi\":\"10.3991/IJOE.V14I06.8704\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Aiming at the reliability optimization algorithm based on wireless sensor network, a data fusion algorithm based on extreme learning machine for wireless sensor network was proposed according to the temporal spatial correlation in data collection process. After analyzing the principles, design ideas and implementation steps of extreme learning machine algorithm, the performance and results were compared with traditional BP algorithm, LEACH algorithm and RBF algorithm in simulation environment. The simulation results showed that the data fusion optimization algorithm based on the limit learning machine for wireless sensor network was reliable. It improved the efficiency of fusion and the comprehensive reliability of the network. Thus, it can prolong the life cycle and reduce the total energy consumption of the network.\",\"PeriodicalId\":387853,\"journal\":{\"name\":\"Int. J. Online Eng.\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-06-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Int. J. Online Eng.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3991/IJOE.V14I06.8704\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Online Eng.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3991/IJOE.V14I06.8704","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Reliability Optimization Algorithm for Wireless Sensor Network
Aiming at the reliability optimization algorithm based on wireless sensor network, a data fusion algorithm based on extreme learning machine for wireless sensor network was proposed according to the temporal spatial correlation in data collection process. After analyzing the principles, design ideas and implementation steps of extreme learning machine algorithm, the performance and results were compared with traditional BP algorithm, LEACH algorithm and RBF algorithm in simulation environment. The simulation results showed that the data fusion optimization algorithm based on the limit learning machine for wireless sensor network was reliable. It improved the efficiency of fusion and the comprehensive reliability of the network. Thus, it can prolong the life cycle and reduce the total energy consumption of the network.