Paper Title : TIME SERIES ANALYSIS AND FORECASTING OF AIR POLLUTION PARTICULATE MATTER USING SARIMA AND SVM APPROACH

ISSN : 2394-2231
Year of Publication : 2022

10.5281/zenodo.6397338

Authors: Mr.C.Mani M.C.A.,M.Phil.,M.E., S.Arunkumar

         



MLA Style: TIME SERIES ANALYSIS AND FORECASTING OF AIR POLLUTION PARTICULATE MATTER USING SARIMA AND SVM APPROACH " Mr.C.Mani M.C.A.,M.Phil.,M.E., S.Arunkumar " Volume 9 - Issue 2 International Journal of Computer Techniques (IJCT) ,ISSN:2394-2231 , www.ijctjournal.org

APA Style: TIME SERIES ANALYSIS AND FORECASTING OF AIR POLLUTION PARTICULATE MATTER USING SARIMA AND SVM APPROACH " Mr.C.Mani M.C.A.,M.Phil.,M.E., S.Arunkumar " Volume 9 - Issue 2 International Journal of Computer Techniques (IJCT) ,ISSN:2394-2231 , www.ijctjournal.org

Abstract
Air pollution is one of the major environmental challenges in a smart megacity terrain. Real- time monitoring of pollution data enables the metropolitans to dissect the current business situation of the megacity and take their opinions consequently. Deployment of Big data Analytical Tool grounded detectors has vastly changed the dynamics of prognosticating air quality. The quality of the atmospheric terrain is an important condition for the longterm survival of humans on earth. A clean suitable atmospheric terrain is needed for the healthy development of mortal beings. Current development of country’s frugality, transportation and assiduity with the enhancement of urbanization, environmental pollution problems have gradationally come prominent, but this is contrary to people’s vision of pursuing a high- quality life. Now the problem of haze, photochemical problems in the air, and global warming is formerly a crucial issue of global concern. Being exploration has used different machine literacy tools for pollution vaticination; still, relative analysis of these ways is frequently needed to have a better understanding of their processing time for multiple datasets. This design performed the pollution vaticination using sarima retrogression fashion and also SVM bracket approach with a relative study to dissect the stylish model for directly prognosticating the air quality. SVM bracket is performed for pollution estimation using multiple available data sets. The design is designed using R Studio. The rendering language used is R3.4.4.

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Keywords
— Data Mining, Air Pollution, Time Series Analysis, Sarima Model.