Research on information fusion model based on multi-clustering fuzzy neural networks

Tie-jun Zhang, Duo Chen, Xiaoyue Liu
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Abstract

Aiming at modeling of the complex and large industrial process, this paper proposes the multi-clustering based on the fusion of hierarchical clustering algorithm of field potential topology and fuzzy c-means clustering, on which the structure of fuzzy neural network model is determined. According to the membership degree calculated, the fuzzy neural network model has been configured based on the multi criteria information fusion and fuzzy technology. Simulation results verify the validity of the model, which has some reference value and significance on the coal mining.
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基于多聚类模糊神经网络的信息融合模型研究
针对复杂大型工业过程建模,提出了基于场势拓扑分层聚类算法与模糊c均值聚类融合的多聚类方法,并在此基础上确定了模糊神经网络模型的结构。根据计算出的隶属度,基于多准则信息融合和模糊技术配置了模糊神经网络模型。仿真结果验证了模型的有效性,对煤矿开采具有一定的参考价值和意义。
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