基于模糊神经元网络的信息融合模型  

Research of Predict Technology Based on Neural Network and Information Fusion

作　　者：刘晓悦[1] 封素敏[1] 

机构地区：[1]河北理工大学计算机与自动控制学院,河北唐山063009

出　　处：《河北理工大学学报（自然科学版）》2008年第3期70-73,82,共5页Journal of Hebei Polytechnic University:Social Science Edition

基　　金：国家自然科学资助项目"煤矿井下电磁兼容性基础研究"(50674093)

摘　　要：神经元网络应用于一般工业过程建模比较有效,但对于对象是庞大数据的复杂的工业生产过程就明显力不从心,提出了基于势场拓扑的层次聚类算法和模糊c均值聚类算法融合,以获得精确的聚类个数和隶属度,基于多判据信息融合和模糊技术构建神经元网络模型,通过对实际地下开采生产过程的仿真,结果验证了模型的有效性。Apply the neural network in the general industry model is effective. However,meural network＇ s strength does not match the huge data complex industrial production process＇ s ambitions. Propose fusion algorithm that based on the topology of the Potential Field algorithm and fuzzy c mean algorithm, obtain the precise clustered number and the membership degree. Construct the neural network model based on multi-criterion information fusion and the fuzzy technology, through the actual simulation on coal mining production procesas, the result confirms that the model is valid.

关 键 词：层次聚类 模糊C均值聚类 模糊神经元网络 信息融合 

分 类 号：TP216.2[自动化与计算机技术—检测技术与自动化装置]