NDLI: Application of support vector machine and ant colony algorithm in optimization of coal ash fusion temperature

Content Provider	IEEE Xplore Digital Library
Author	Fang Gao Pu Han Yong-Jie Zhai Li-Xia Chen
Copyright Year	2011
Description	Author affiliation: College of Electric and Information Engineering, Hebei University, Baoding, Hebei 071002, China (Li-Xia Chen) \|\| College of Control and Computer Engineering, North China Electric Power University, Baoding, Hebei 071003, China (Fang Gao; Pu Han; Yong-Jie Zhai)
Abstract	The model of coal ash fusion temperature was made by support vector machine. An improved ant colony algorithm for solving continuous space optimization problems was proposed. The parameters of support vector machine were optimized by the improved ant colony algorithm. And it was also used to make a global optimization to find the suitable chemical compositions of coal ash corresponding to the maximum and minimum ash fusion temperature. The results indicate that the maximum and average relative predicting errors of the model are 2.02% and 0.56% respectively. The optimization results show that the chemical compositions of the coal ash are consistent with that in practice. And not only the convergence rate but also the convergence performance was improved.
Starting Page	666
Ending Page	672
File Size	852164
Page Count	7
File Format	PDF
ISBN	9781457703058
ISSN	21601348
e-ISBN	9781457703089
DOI	10.1109/ICMLC.2011.6016759
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-07-10
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Ash Coal Optimization Support vector machines Cities and towns Training Predictive models Mutation Coal ash fusion temperature Support vector machine Ant colony algorithm
Content Type	Text
Resource Type	Article

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