title: Least Square Fast Learning Network for modeling the combustion efficiency of a 300WM coal-fired boiler.
abstract: This paper presents a novel artificial neural network with a very fast learning speed, all of whose weights and biases are determined by the twice Least Square method, so it is called Least Square Fast Learning Network (LSFLN). In addition, there is another difference from conventional neural networks, which is that the output neurons of LSFLN not only receive the information from the hidden layer neurons, but also receive the external information itself directly from the input neurons. In order to test the validity of LSFLN, it is applied to 6 classical regression applications, and also employed to build the functional relation between the combustion efficiency and operating parameters of a 300WM coal-fired boiler. Experimental results show that, compared with other methods, LSFLN with very less hidden neurons could achieve much better regression precision and generalization ability at a much faster learning speed.
authors.affiliation: Key Lab of Industrial Computer Control Engineering of Hebei Province, Yanshan University, Qinhuangdao 066004, China; National Engineering Research Center for Equipment and Technology of Cold Strip Rolling, Qinhuangdao 066004, China. Electronic address: zhihuiyuang@163.com.
authors.forename: Guoqiang
authors.initials: G
authors.lastname: Li
authors.affiliation: Key Lab of Industrial Computer Control Engineering of Hebei Province, Yanshan University, Qinhuangdao 066004, China; National Engineering Research Center for Equipment and Technology of Cold Strip Rolling, Qinhuangdao 066004, China.
authors.forename: Peifeng
authors.initials: P
authors.lastname: Niu
authors.affiliation: Key Lab of Industrial Computer Control Engineering of Hebei Province, Yanshan University, Qinhuangdao 066004, China.
authors.forename: Huaibao
authors.initials: H
authors.lastname: Wang
authors.affiliation: Key Lab of Industrial Computer Control Engineering of Hebei Province, Yanshan University, Qinhuangdao 066004, China; National Engineering Research Center for Equipment and Technology of Cold Strip Rolling, Qinhuangdao 066004, China.
authors.forename: Yongchao
authors.initials: Y
authors.lastname: Liu
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003031:Coal; D003198:Computer Simulation; D016018:Least-Squares Analysis; D016571:Neural Networks, Computer; D012044:Regression Analysis; D013997:Time Factors
chemical_list: D003031:Coal
keywords: Artificial neural network; Coal-fired boiler; Least Square Fast Learning Network; Least square