ADEEL TAHIR, MUHAMMAD ASHRAF, ZAHEER UDDIN, MUHAMMAD SARIM, SYED NASEEM SHAH
{"title":"Numerical modeling and forecasting temperature distribution by neural network and regression analysis","authors":"ADEEL TAHIR, MUHAMMAD ASHRAF, ZAHEER UDDIN, MUHAMMAD SARIM, SYED NASEEM SHAH","doi":"10.54302/mausam.v74i4.5513","DOIUrl":null,"url":null,"abstract":"Environmental changes occur due to various parameters, and global warming is one of those parameters. It is observed that the daily mean temperature has constantly been increasing as time passes. The knowledge of temperature distribution allows us to decide the stuff that strongly depends upon temperature variation. An attempt has been made to model and forecast temperature distributions for 2018-2020. Artificial Neural Network (ANN) and multiple regression analyses have been used to forecast daily mean temperatures for one of Pakistan's cities of Sindh (Nawabshah). Environmental data from 2010 to 2020 has been used to predict daily mean temperature. The statistical errors such as RMSE, MABE and MAPE and coefficient of determination R2 are calculated to check the results' validity. Both models are suitable for predicting temperature distribution; however, ANN gives the best result. Two different regression models (linear & non-linear) are employed for the numerical fitting of temperature data; the non-linear model shows the better fitting.","PeriodicalId":18363,"journal":{"name":"MAUSAM","volume":"153 1","pages":"0"},"PeriodicalIF":0.7000,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"MAUSAM","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.54302/mausam.v74i4.5513","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Environmental changes occur due to various parameters, and global warming is one of those parameters. It is observed that the daily mean temperature has constantly been increasing as time passes. The knowledge of temperature distribution allows us to decide the stuff that strongly depends upon temperature variation. An attempt has been made to model and forecast temperature distributions for 2018-2020. Artificial Neural Network (ANN) and multiple regression analyses have been used to forecast daily mean temperatures for one of Pakistan's cities of Sindh (Nawabshah). Environmental data from 2010 to 2020 has been used to predict daily mean temperature. The statistical errors such as RMSE, MABE and MAPE and coefficient of determination R2 are calculated to check the results' validity. Both models are suitable for predicting temperature distribution; however, ANN gives the best result. Two different regression models (linear & non-linear) are employed for the numerical fitting of temperature data; the non-linear model shows the better fitting.
期刊介绍:
MAUSAM (Formerly Indian Journal of Meteorology, Hydrology & Geophysics), established in January 1950, is the quarterly research
journal brought out by the India Meteorological Department (IMD). MAUSAM is a medium for publication of original scientific
research work. MAUSAM is a premier scientific research journal published in this part of the world in the fields of Meteorology,
Hydrology & Geophysics. The four issues appear in January, April, July & October.