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