An Application of the Combination of Ant Colony Algorithm and Neural Network
Based on complementary strategies, a new AI method, the hybrid of ant colony algorithm and neural network, was put forward to solve the fault diagnosis of diesel engine. The ant colony algorithm is used to simplify attribute parameters reflecting operating conditions of diesel engine and in which unnecessary attributes are eliminated. According to the reduction result, the fault diagnosis system based on RBF neural network was produced. Through the comparison of fault classification effect, it is shown that the new method reduces the dimension of input to neural network, raises the training efficiency and the fault classification accuracy.
ant colony algorithm fault diagnosis diesel engine ANN.
Yan-bin Qu Yang Zhang
College of Information Science and Engineering Harbin Institute of Technology at Weihai Weihai, Shandong Province, 264209, China
国际会议
2006 IEEE International Conference on Information Acquisition
山东威海
英文
1067-1070
2006-08-20（万方平台首次上网日期，不代表论文的发表时间）