太原理工大学学报2017，Vol.48Issue(6)：946-952,7.DOI:10.16355/j.cnki.issn1007-9432tyut.2017.06.012
基于改进分布式极限学习机的电站锅炉NOx排放预测算法
NOx Emission Prediction Algorithm of Power Station Boiler Based on Improved Distributed Extreme Learning Machine
摘要
Abstract
An improved distributed extreme learning machine was proposed to model the NOx emission characteristics of power station boiler.The introduction of distributed type and ridge re-gression theory improved the generalization performance and prediction accuracy of the limit learning algorithm.An improved MapReduce programming framework was adopted to carry out the parallelization of the the proposed algorithm so as to enhance its ability of dealing with mas-sive data.The real operation data provided by a 660MW power station boiler was analyzed and tested on Hadoop cluster.Results show that the proposed model has a better fitting and predic-tive ability for NOx emission,and the proposed algorithm has excellent parallel performance.关键词
NOx排放/海量数据/MapReduce/分布式极限学习机Key words
NOx emission/massive data/MapReduce/distributed extreme learning machine分类
信息技术与安全科学引用本文复制引用
徐晨晨,续欣莹,阎高伟,韩晓霞..基于改进分布式极限学习机的电站锅炉NOx排放预测算法[J].太原理工大学学报,2017,48(6):946-952,7.基金项目
山西省自然科学基金资助项目(2014011018-2) （2014011018-2）
山西省回国留学人员科研资助项目(2015-045) （2015-045）
神经网络协同遗传算法高效筛选镍基甲烷化催化剂研究(21606159) （21606159）
