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Modeling of air pollutants using least square support vector regression, multivariate adaptive regression spline, and M5 model tree models

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Abstract

This study investigates the applicability of three different soft computing methods, least square support vector regression (LSSVR), multivariate adaptive regression splines (MARS), and M5 Model Tree (M5-Tree), in forecasting SO2 concentration. These models were applied to monthly data obtained from Janakpuri, Nizamuddin, and Shahzadabad, located in Delhi, India. The models were compared with each other using the cross validation method with respect to root mean square error, mean absolute error, and correlation coefficient. According to the comparison, LSSVR provided better accuracy than the other models, while the MARS model was found to be the second best model in forecasting monthly SO2 concentration. Results indicated that the applied models gave better forecasting accuracy in Janakpuri station than the other stations. The results were also compared with previous studies and satisfactory results were obtained from three methods in modeling SO2 concentrations.

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Acknowledgements

The authors are thankful to the Central Pollution Control Board (CPCB), Government of India, for providing the research data and Dr. B. R. Ambedkar National Institute of Technology, Jalandhar (Government of India) and IKG Punjab Technical University (Government of Punjab) for providing research facilities. The second author is also thankful to Prof. Rashmi Bhardwaj, Guru Gobind Singh Indraprastha University, for her motivation and astute guidance. The third author (KS) is grateful to the Director, CSIR-NPL.

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Authors and Affiliations

  1. Center for Interdisciplinary Research, International Black Sea University, Tbilisi, Georgia

    Ozgur Kisi

  2. Department of Mathematics, IKG Punjab Technical University, Jalandhar -, Kapurthala, India

    Kulwinder Singh Parmar

  3. Apex level and Industrial Metrology Division, CSIR-National Physical Laboratory, Delhi, India

    Kirti Soni

  4. Engineering Faculty, Civil Engineering Department, Karatay University, Konya, Turkey

    Vahdettin Demir

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  1. Ozgur Kisi
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  2. Kulwinder Singh Parmar
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  4. Vahdettin Demir
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Correspondence to Ozgur Kisi or Kulwinder Singh Parmar.

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Kisi, O., Parmar, K.S., Soni, K. et al. Modeling of air pollutants using least square support vector regression, multivariate adaptive regression spline, and M5 model tree models. Air Qual Atmos Health 10, 873–883 (2017). https://doi.org/10.1007/s11869-017-0477-9

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  • DOI: https://doi.org/10.1007/s11869-017-0477-9

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