Research on Node Localization Algorithm in WSN basing Machine Learning
Machine learning uses experience to improve its performance.Using Machine Learing,to locate the nodes in wireless sensor network.The basic idea is that:the network area is divided into several equal portions of small grids,each gird represents a certain class of Machine Learning algorithm.After Machine Learning algorithm has learnt the parameters using the known beacon nodes,it can classify the unknown nodes location classes,and further determine their coordinates.For the SVM OneAgainstOne Location Algorithm,the results of simulation show that it has a high localization accuracy and a better tolerance for the ranging error,while it doesnt require a high beacon node ratio.For the SVM Decision Tree Location Algorithm,the results show that this algorithm is not affected seriously by coverage holes,it is suitable for the network environment of nonuniformity distribution or existing coverage holes.
wireless sensor network node localization support vector machine region classification coverage hole
Qingzhang Chen Yuzheng Chen Congling Fan Fan Yang Peng Wang Yanjing Lei
Department of Computer, Zhejiang University of Technology, Hangzhou Zhejiang, 310023, China
国际会议
太原
英文
43-46
2012-12-08（万方平台首次上网日期，不代表论文的发表时间）