关键词: 交互式遗传算法, 误差反向传播神经网络, 代理模型, 评价噪声, 用户疲劳

Abstract: To solve the problem of evaluation noise and user fatigue in the Interactive Genetic Algorithm（IGA）, an error Back?Propagation（BP） neural network user cognitive surrogate model is proposed to improve the performance of IGA. First, because user perceptions are uncertain, a model for noises is built to form the adaptive value with individual dynamic fuzzy interval. Then user cognitive surrogate model based on BP neural network is constructed by historical evaluation information when the user’s cognition is certain and a new adaptive value estimation strategy is presented. By measuring Mean Squared Error（MSE）, the management and update of the agent model are realized. This method is applied to selection system of pattern design with batik style, the results show that it can effectively optimize the quality of adaptive value with individual and reduce user fatigue.

Key words: Interactive Genetic Algorithm（IGA）, error Back?Propagation（BP） neural network, surrogate model, evaluation noise, user fatigue