Abstract: Influences of artificial neural network,s(ANN) parameters including number of hidden layers and nodes, initial weights, initial biases and the determination methods of the training set to the accuracy of system identification, based on the experiment data of the exemplified system, are analyzed. Based on MATLAB toolbox, nest of programming method，which considers the interaction among the parameters and can help gain optimal parameters of ANN, is presented. In addition, a method that converts a multi-input system to a one-input system and then establishes its model using ANN is also presented. According to these methods, model of the exemplified system is established and satisfactory result is obtained.

Key words: System identification accuracy Influence and analysis Determination method, Artificial neural network, Parameters