Research of Fuzzy Neural Network Model Based on Quantum Clustering

Jie Sun, Sheng-nan Hao
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引用次数: 2

Abstract

Fuzzy neural network can handle non-linear, complex data, but the structure of model determination is an important and difficult issues identified. More complete results can be made .in a short period of time by the optimization network model. To address this issue, this paper presents the fusion of a quantum clustering algorithm and fuzzy c-means clustering algorithm, the fuzzy neural network structure is carried out at different levels data processing. Through the model of mining in complex industrial process, the validity of the model is tested.
基于量子聚类的模糊神经网络模型研究
模糊神经网络可以处理非线性、复杂的数据,但模型结构的确定是识别的一个重要而困难的问题。该优化网络模型可以在较短的时间内得到较完整的结果。针对这一问题,本文提出了一种融合量子聚类算法和模糊c均值聚类算法的方法,利用模糊神经网络结构对不同层次的数据进行处理。通过复杂工业过程中的采矿模型,验证了模型的有效性。
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