Prediction of PM2.5 and PM10 parameters using artificial neural network: a case study in Kemayoran, Jakarta

Autor:	R M Putra, Martarizal, A M M B Putra
Rok vydání:	2020
Předmět:	History Meteorology Artificial neural network Data Applied Respiratory infection Environmental science Humidity Sun exposure Line (text file) Air quality index Wind speed Computer Science Applications Education
Zdroj:	Journal of Physics: Conference Series. 1528:012036
ISSN:	1742-6596 1742-6588
DOI:	10.1088/1742-6596/1528/1/012036
Popis:	It was recorded that in August 2019 the case of acute respiratory infection in Indonesia had doubled compared to the previous months. This is in line with the increasing levels of PM10 and PM2.5 in several regions in Indonesia. In the end the public is increasingly aware of the importance of air quality information. Prediction of air quality will greatly help the public to anticipate the dangers of declining air quality. The use of Artificial Neural Network can be a solution in making daily air quality forecasts whose parameters are not linear. This research shows that utilization of historical data parameters of temperature, humidity, air pressure, rainfall, sun exposure and wind speed as well as BMKG’s PM10 and PM2.5 data is able to produce forecasting modeling for PM2.5 and PM10 concentrations in the Kemayoran area, Jakarta by utilizing Artificial Neural Network Modeling. The result is success to make prediction of PM2.5 and PM10 and it will be better if more historical data applied.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::35309e98fd20e871ee9d1256cfa1d882 https://doi.org/10.1088/1742-6596/1528/1/012036 Zobrazit plný text záznamu