Open AccessForecasting of Air Pollution Index PM2.5 Using Support Vector Machine(SVM)
Author(s) -
Nor Hayati Shafii,
Rosidah Alias,
Nur Fithrinnissaa Zamani,
Nur Fatihah Fauzi
Publication year - 2020
Publication title -
journal of computing research and innovation
Language(s) - English
Resource type - Journals
ISSN - 2600-8793
DOI - 10.24191/jcrinn.v5i3.149
Subject(s) - mean squared error , support vector machine , air quality index , air pollution , statistics , mean absolute error , pollution , radial basis function , kernel (algebra) , environmental pollution , index (typography) , mathematics , environmental science , computer science , machine learning , geography , meteorology , ecology , environmental protection , combinatorics , artificial neural network , world wide web , biology
Air pollution is a current monitored problem in areas with high population density such as big cities. Many regions in Malaysia are facing extreme air quality issues. This situation is caused by several factors such as human behavior, environmental awareness and technological development. Accessing the air pollution index (API) accurately is very important to control its impact on environmental and human health. The work presented here aims to access air pollution index of PM2.5 using Support Vector Machine (SVM) and to compare the accuracy of four different types of the kernel function in Support Vector Machine (SVM). The data used is provided by the Department of Environment (DOE) and it is recorded from two Continuous Air Quality Monitoring Stations (CAQM) located at Tanah Merah and Kota Bharu. The results are analyzed using mean absolute error (MAE) and root mean squared error (RMSE). It is found that the proposed model using Radial Basis Function (RBF) with its parameters of cost and gamma equal to 100 can effectively and accurately forecast the air pollution index with Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) of 0.03868583 and 0.06251793 respectively for API in Kota Bharu and 0.03857308 (MAE) and 0.05895648 (RMSE) for API in Tanah Merah.