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基于用户为中心原则,构建查新站质量评价的指标体系,将直觉模糊集理论引入查新站质量评价领域,提出基于自适应神经直觉模糊推理系统的查新站评价方法。首先,采用减法聚类确定自适应直觉模糊神经网络的结构;然后利用混合学习算法训练该网络的前件参数和结论参数;最后,通过采集数据对模型进行训练和测试,结果表明采用该方法所建立的评价模型是有效的。
Based on user-centric principle, this paper constructs the index system of quality evaluation of Chaxin station, introduces intuitionistic fuzzy set theory into the quality evaluation of Chaxin station, and proposes the evaluation method of Chaxin station based on adaptive neuro-intuitionistic fuzzy inference system. Firstly, subtractive clustering is used to determine the structure of adaptive intuitionistic fuzzy neural network. Then, the hybrid learning algorithm is used to train the antecedent parameters and conclusion parameters of the network. Finally, the data are used to train and test the model. The results show that using this method The established evaluation model is valid.