基于效用函数逼近的绿色产品评价方法

提出了采用逼近绿色产品效用函数的评价方法。首先选取产品样本，然后采用函数逼近方法建立评价模型。依据人工神经网络逼近函数的计算条件， 建立了基于BP神经网络和径向基函数神经网络的绿色产品评价模型以电冰箱为例，建立评价指标体系，收集了相关的评价样本，分别对BP神经网络和径向基函数神经网络进行了训练和仿真。该方法的计算不需要各指标的权重，可对绿色产品序数和基数效用函数进行逼近，实现了绿色产品非线性效用函数的评价。

EVALUATIONON APPROXIMATION TO UTILITY FUNCTION OF GREEN PRODUCT

An evaluation method of green product is set up, which is based on function approximation. It is to select product samples, then to use methods of function approximation and set up model. According to condition on the function approximation of artificial neural network, an evaluation model of green product based on artificial neural network is set up. An instance of refrigerator is given. After establishing the structure of it's evaluating index and collecting related evaluating samples, BP and RBF neural networks are respectively trained and simulated. Those models, which don't need weighting, can fulfill approximation to ordinal-number utility function and cardinal-number utility function, and realize evaluation of the non-linear utility function of green product.