Numerical modeling and forecasting temperature distribution by neural network and regression analysis

IF 0.7 4区 地球科学 Q4 METEOROLOGY & ATMOSPHERIC SCIENCES MAUSAM Pub Date : 2023-10-01 DOI:10.54302/mausam.v74i4.5513
ADEEL TAHIR, MUHAMMAD ASHRAF, ZAHEER UDDIN, MUHAMMAD SARIM, SYED NASEEM SHAH
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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.
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采用神经网络和回归分析方法对温度分布进行数值模拟和预测
环境变化是由各种参数引起的,全球变暖就是其中一个参数。可以观察到,随着时间的推移,日平均温度一直在不断上升。温度分布的知识使我们能够决定那些强烈依赖于温度变化的东西。对2018-2020年的温度分布进行了建模和预测。人工神经网络(ANN)和多元回归分析已经被用来预测巴基斯坦信德省(纳瓦布沙)一个城市的日平均气温。2010年至2020年的环境数据被用来预测日平均温度。计算RMSE、MABE、MAPE等统计误差和决定系数R2来检验结果的有效性。两种模型均适用于预测温度分布;然而,人工神经网络给出了最好的结果。两种不同的回归模型(线性&采用非线性方法对温度数据进行数值拟合;非线性模型拟合效果较好。
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来源期刊
MAUSAM
MAUSAM 地学-气象与大气科学
CiteScore
1.20
自引率
0.00%
发文量
1298
审稿时长
6-12 weeks
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.
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