Data Classification in Internet of Things Based on Evolutionary Neural Network

Abstract

Data classification is the foundation for the intelligent identification and management of massive information in the internet of things. To classify the massive data accurately, an evolutionary neural network is presented. The input features and the structure of neural network are evolved simultaneously to consider their joint contribution to the performance of neural network. The sensitivity analysis is performed to guide the evolutionary algorithm to search the optimum solution. It can be seen from the experimental results that the proposed evolutionary algorithm optimized the structure of neural network and eliminate the tedious input features at the same time. The excellent classification accuracy is achieved finally.