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  2018, Vol. 31 Issue (8): 725-739    DOI: 10.16451/j.cnki.issn1003-6059.201808005
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Haze Prediction Method Combining Co-evolution Artificial Fish Swarm Algorithm and Support Vector Machine
ZUO Jiaojiao1,2, NI Zhiwei1,2, ZHU Xuhui1,2, LI Jingming3, WU Zhangjun1,2
1.School of Management, Hefei University of Technology, Hefei 230009
2.Key Laboratory of Process Optimization and Intelligent Decision-Making of Ministry of Education, Hefei University of Technology, Hefei 230009
3.School of Management Science and Engineering, Anhui University of Finance and Economics, Bengbu 233030

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Abstract  

Aiming at the increasingly serious haze pollution, a haze prediction method combining co-evolution artificial fish swarm algorithm(CEAFSA) and support vector machine(SVM) is proposed. Firstly, an improved artificial fish swarm algorithm is proposed by initializing evenly distributed population using the good point set, and introducing adaptive strategies for visual scope and step and co-evolution strategies among subpopulations. Then, the main parameters of SVM are optimized by co-evolution artificial fish swarm algorithm. Finally, haze prediction model is established by SVM. Experimental results on 10 Benchmark testing functions verify the validity of CEAFSA and the results on 6 UCI datasets demonstrate its high stability and effectiveness.

Key wordsArtificial Fish Swarm Algorithm      Co-evolution      Support Vector Machine(SVM)      Haze Prediction     
Received: 02 March 2018     
ZTFLH: TP 301.6  
Fund:

Supported by National Natural Science Foundation of China(No.91546108,71490725,71521001), Natural Science Foundation of Anhui Province(No.1708085MG169), Humanities and Social Science Research Project of Anhui Provincial Education Department(JS2017AJRW0135)

Corresponding Authors: NI Zhiwei, Ph.D., professor. His research interests include artificial intelligence, machine learning and cloud computing.   
About author:: ZUO Jiaojiao, master student. Her research interests include machine learning and data mining. ZHU Xuhui, Ph.D., lecturer. His resear-ch interests include intelligent computing and machine learning. LI Jingming, Ph.D., lecturer. His resear-ch interests include intelligent computing and data mining. WU Zhangjun, Ph.D., associate professor. His research interests include machine learning and data mining.
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ZUO Jiaojiao
NI Zhiwei
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LI Jingming
WU Zhangjun
Cite this article:   
ZUO Jiaojiao,NI Zhiwei,ZHU Xuhui等. Haze Prediction Method Combining Co-evolution Artificial Fish Swarm Algorithm and Support Vector Machine[J]. , 2018, 31(8): 725-739.
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http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.201808005      OR     http://manu46.magtech.com.cn/Jweb_prai/EN/Y2018/V31/I8/725
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