Computer Science

Computer Science ›› 2024, Vol. 51 ›› Issue (11A): 240300120-6.doi: 10.11896/jsjkx.240300120

• Interdiscipline & Application • Previous Articles     Next Articles

Air Quality Fuzzy Cognitive Map Forecasting Based on Niche Genetic Algorithm

HAN Huijian1,2,3, LIU Kexin1,2, LIN Xue1,2   

  1. 1 School of Computer Science,Shandong University of Finance and Economics,Jinan 250014,China
    2 Shandong Key Laboratory of Digital Media Technology,Jinan 250014,China
    3 Shandong Information Visualization and Computational Economic Technology Research Center,Jinan 250014,China
  • Online:2024-11-16 Published:2024-11-13
  • About author:HAN Huijian,born in 1971,Ph.D,professor,M.S supervisor,is a member of CCF(No.21259S).His main research interests include information management,cognitive intelligence,and visual decision.
    LIU Kexin,bornin 1998,postgraduate.His main research interests include system recognition and forecast.
  • Supported by:
    National Social Science Fundation of China(22BSH020).

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Abstract: Industrialization has led to the rapid growth of global economy,but it has also made environmental pollution more and more serious.Air pollution has become a worldwide hot topic around the world.In this paper,an air quality fuzzy cognitive map forecasting method based on niche genetic algorithm is proposed.This method indicates the relationship of airpollutants and air quality index by using fuzzy cognitive map,and makes the training target moreclose to the global best solution by using modified niche genetic algorithm.The air quality data from 2015 to 2021 is used to train the model,and the model is tested on the 2022 data.Theresult indicates that compared to the traditional genetic algorithm and BP neural network,theproposed method has higher prediction accuracy and better generalization performance,which proves its effectiveness.

Key words: Air quality, Fuzzy cognitive map, Niche genetic algorithm

CLC Number: 

  • TP3-05
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