%0 Journal Article
%T Complex Maneuverable Events Detection Based On REFNN
%A Wei Chen
%A Ji-zheng Wu
%A Qing Li
%A PengHui Rong
%J Journal of Software
%D 2012
%I Academy Publisher
%R 10.4304/jsw.7.1.81-87
%X In this paper, a method based on REFNN (Rough-Evolution Fuzzy Neural Network) is proposed to deal with such problems as imprecision and poor real-time performance in complex maneuverable events detection. Firstly, the optimal discrete values of continuous attributes are obtained through GA (Genetic Algorithm); secondly, the minimal rule sets from data samples are acquired by using the Rough Set Theory; then, these rules are used to construct the initial scalar values of neural cells in each layer and their relative parameters in the fuzzy neural network; lastly, parameters of the network are acquired by using BP(back propagation) algorithm. The simulation shows the effectiveness of the new method of complex maneuverable events detection based on REFNN; simultaneously REFNN has structure advantages.
%K situation assessment
%K complex maneuverable events
%K events detection
%K REFNN
%U http://ojs.academypublisher.com/index.php/jsw/article/view/6661