文献类型：期刊文献

英文题名：A new internet of things group search optimizer

作者：Feng, Xiang[1];Liu, Xiaoting[1];Yu, Huiqun[1]

机构：[1]E China Univ Sci & Technol, Dept Comp Sci & Engn, Shanghai 200237, Peoples R China

年份：2016

卷号：29

期号：3

起止页码：535

外文期刊名：INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS

收录：;EI(收录号：20160101744389);WOS:【SCI-EXPANDED(收录号:WOS:000369147500008)】；

基金：This work was supported in part by the National Natural Science Foundation of China under grant nos. 60905043, 61073107, and 61173048; the Innovation Program of Shanghai Municipal Education Commission; and the Fundamental Research Funds for the Central Universities.

语种：英文

外文关键词：Internet of Things group search optimizer; sensor network; binary group search optimizer; leader decision

摘要：The development of the Internet of Things brings new opportunities and challenges for sensor networks. The scale of sensor networks tends to be larger. And the fusion rules need to be intelligent. In this paper, we propose a new Internet of Things group search optimizer (ITGSO) to solve intelligent information fusion problems in the high-dimensional multi-sensor networks. ITGSO is inspired by the latest research achievement about leader decision in Nature and works about social coordination, which mainly consists of three parts: basic group search optimizer, binary group search optimizer, and social decision model. With ITGSO, we need less time to obtain minimum Bayes cost than particle swarm optimization. And information of uncertain social intelligent problems can be fused. In this paper, we give the theoretical basic of ITGSO and proved its validity via mathematical analysis and simulation results. Copyright (c) 2014 John Wiley & Sons, Ltd.