基于减法聚类的神经网络模型及其应用

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,采用基于减法聚类算法和模糊c均值聚类算法融合,以获得精确的聚类个数和隶属度,建立基于多判据信息融合和模糊技术构成的神经元网络模型,对实际地下开采生产过程进行仿真,结果验证了模型的有效性.

Application of Neural Network Model Based on Subtraction Clustering

Apply the neural network in the general industry model is effective,however,neural network's strength does not match the huge data complex industrial production process's ambitions.Propose fusion algorithm that based on subtraction clustering 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 process,the result confirms that the model is valid.