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