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针对模糊规则分类中数据边界硬性划分的局限性问题,建立了云-神经网络模型,并提出了基于云-神经网络的模糊规则分类算法.在不影响数据模糊性和随机性的基础上,将数据转化为规则,并利用神经网络的学习能力,进行多属性模糊规则分类.与传统方法相比,该方法在保证数据模糊性和随机性的基础上,提高了模型精度和分类准确率.应用实例表明了该方法的有效性和可行性.
Aimed at the limitation of the rigid partitioning of data boundaries in fuzzy rule classification, a cloud-neural network model is established and a fuzzy rule classification algorithm based on cloud-neural network is proposed.On the basis of not affecting the fuzziness and randomness of data, Data is transformed into rules, and the learning ability of neural network is used to classify multi-attribute fuzzy rules.Compared with the traditional methods, the proposed method improves the model accuracy and the classification accuracy based on the fuzziness and randomness of the data. The example shows the effectiveness and feasibility of the method.