摘要
以陕北某大型焦化生产企业的炭化炉为研究对象,在分析其工艺的基础上,通过对已有研究成果的分析,提出了利用兼具自学习特性与模糊处理能力的模糊神经网络来构建炭化炉产量预测模型,又利用具有聚类处理能力的自组织算法对其进行了优化。使用MATLAB软件对模型进行训练和预测仿真,利用自组织模糊神经网络构建的产量预测模型优于一般的模糊神经网络预测模型,是可信赖的炭化炉产量预测模型。
Put the charring coke of one coking enterprises in northern Shaanxi as research object.Its technology process is studied,and existing research achievement is analysis.The model for prediction of productivity based on the Fuzzy Neural Network,which had the ability of fuzzy processing and self-learning characters,is selected.Then a self-organizing algorithm is applied to optimize the model,which had the superiority of clustering handle capability.The error are analyzed after the training and testing simulation for the two models for prediction of coke productity by MATLAB.Simulation result show that the prediction model of coke for productivity based on had self-organizing algorithm for fuzzy neural networks is better than the normal.
出处
《工业控制计算机》
2014年第7期1-3,8,共4页
Industrial Control Computer
基金
国家自然科学基金(51178373)
陕西省科技统筹创新工程计划项目(2011KTDZ01-05-05)
关键词
炭化炉
模糊神经网络
自组织算法
预测模型
charring coke,fuzzy neural netorks,self-organizing algorithm,prediction model
