计量学报Issue(3)：251-255,5.DOI:10.3969/j.issn.1000-1158.2015.03.07
汽轮机热耗率多模型建模方法研究
lnvestigation on Multi-model Modeling Method of Steam Turbine Heat Rate
摘要
Abstract
Taking into account the problem that the heat rate of steam turbine is difficult to accurately calculate,a novel heat rate multi-model soft measurement methodology based on kernel fuzzy c-means and shuffled frog-leaping algorithm optimized least squares support vector machine(LS-SVM is proposed),which is employed to calculate the heat rate under different working conditions. This method applies kernel fuzzy c-means algorithm clustering heat rate data. Taking the mean error of 5-fold cross-validation as fitness value of parameters selection for LS-SVM,LS-SVM based on SFLA is trained and established local model for each cluster,and then the model output is obtained by the switch way,so as to realize the heat rate multi-model method. Compared with the single LS-SVM model and BP network heat rate prediction model,the multi-model has a higher prediction accuracy and better generalization ability.关键词
计量学/汽轮机热耗率/混合蛙跳算法/多模型建模/最小二乘支持向量机/核模糊c均值Key words
Metrology/Heat rate of steam turbine/Shuffled frog-leaping algorithm/Multi-model modeling/Least square support vector machine/Kernel fuzzy c-means algorithm分类
信息技术与安全科学引用本文复制引用
牛培峰,刘超,李国强,马云飞,陈贵林,张先臣..汽轮机热耗率多模型建模方法研究[J].计量学报,2015,(3):251-255,5.基金项目
国家自然科学基金（60774028）；河北省自然科学基金 （）
