^ Application of Support Vector Machine and Gene Expression Programming on Tropospheric ozone Prognosticating for Tehran Metropolitan | Structurae
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Application of Support Vector Machine and Gene Expression Programming on Tropospheric ozone Prognosticating for Tehran Metropolitan

Autor(en):

Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: Civil Engineering Journal, , n. 8, v. 3
Seite(n): 557
DOI: 10.28991/cej-030984
Abstrakt:

Air pollution became fatal issue for humanity and all environment and developed countries unanimously allocated vast investments on monitoring and researches about air pollutants. Soft computing as a novel way for pollutants prediction can be used for measurement tools calibration which can coincidently decrease the expenditures and enhance their ability to adapt quickly. In this paper support vector machine (SVM) and gene expression programming (GEP) as two powerful approaches with reliable results in previous studies, used to predict tropospheric ozone in Tehran metropolitan by using the photochemical precursors and meteorological parameters as predictors. In a comparison between the two approaches, the best model of SVM gave superior results as it depicted the RMSE= 0.0774 and R= 0.8459 while these results of gene expression programming, respectively, are 0.0883 and 0.7938. Sensitivity of O3 against photochemical precursors and meteorological parameters and also for every input parameter, has been analysed discreetly and the gained results imply that PM2.5, PM10, temperature, CO and NO₂ are the most effective parameters for O3 values tolerances. For SVM, several kernel tricks used and the best appropriate kernel selected due to its result. Nonetheless, gamma and sin2 values varied for every kernel and in the last radial basis function kernel opted as the best trick in this study. Finally, the best model of both applications revealed, and the resulted models evaluated as reliable and acceptable.

Copyright: © 2018 Vahid Mehdipour, Mahsa Memarianfard
Lizenz:

Dieses Werk wurde unter der Creative-Commons-Lizenz Namensnennung 4.0 International (CC-BY 4.0) veröffentlicht und darf unter den Lizenzbedinungen vervielfältigt, verbreitet, öffentlich zugänglich gemacht, sowie abgewandelt und bearbeitet werden. Dabei muss der Urheber bzw. Rechteinhaber genannt und die Lizenzbedingungen eingehalten werden.

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  • Reference-ID
    10341160
  • Veröffentlicht am:
    14.08.2019
  • Geändert am:
    02.06.2021