Man-Machine Interface Evaluation Method of the Power Plant Based on Artificial Neural Network

Many mathematic models have been applied in the man-machine interface (MMI) evaluation field. However, these traditional methods all suffer from the same problem: lack of self-learning ability and fuzzy in the evaluation process. In order to solve these problems, the artificial neural network (ANN) methodology is firstly put forward in the field of MMI evaluation in this paper. The evaluation software based on the radial basis function (RBF) neural network and MATLAB data-base technique is set up and applied in the objective and subjective evaluation on the digital control system console of the power plant. Results of the evaluation example prove that the ANN method for MMI evaluation is reasonable and the evaluation software is applicable.