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Artificial Intelligence and Statistical Regression for the Prediction of Temperature over Sukkur Region


Article Information

Title: Artificial Intelligence and Statistical Regression for the Prediction of Temperature over Sukkur Region

Authors: M.Y Tufail, S Gul

Journal: International Journal of Artificial Intelligence and Mathematical Sciences (IJAIMS)

HEC Recognition History
Category From To
Y 2024-10-01 2025-12-31

Publisher: Sindh Madresatul Islam University, Karachi

Country: Pakistan

Year: 2024

Volume: 3

Issue: 2

Language: en

DOI: 10.58921/ijaims.v3i2.125

Keywords: Multiple regressionSupervised Machine LearningUpper part of SindhMathematical modellingArtificial neural network.

Categories

Abstract

This study focuses on forecasting the temperature of the Sukkur region in Sindh, Pakistan, using historical temperature data from four neighboring cities: Kashmore, Shikarpur, Ghotki, and Khairpur. Three different predictive models were developed, based on multiple regression, supervised machine learning, and artificial neural networks (ANN). The results indicate that all three approaches provide highly accurate temperature predictions, with multiple regression and supervised machine learning performing slightly better than the ANN model. The analysis is based on temperature data from 2001 to 2019, and all simulations were conducted using Python 3.9.16 within the Anaconda environment.


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