Artificial Intelligence and Statistical Regression for the Prediction of Temperature over Sukkur Region
Keywords:
Upper part of Sindh, Mathematical modelling, Supervised machine learning, Multiple regression, Artificial neural network.
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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[8] Schmidt, S., Kemfert, C., Ho¨ppe, P., Regional Environmental Change, 10, 13, 2010.
[9] Griffiths, GM., Chambers, LE., Haylock, MR., Manton, M.J., Nicholls, N., Baek, H-J., Choi, Y., Della-Marta, P.M., Gosai, A., Iga, N et al., International Journal of Climatology: A Journal of the Royal Meteorological Society, 25, 1301, 2005.
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[11] Goswami, K., Hazarika, J., Patowary, A., International Journal of Advanced Research in Computer Science, 8, 2017.
[12] Wang, Z., Mujib A. M., Journal of Physics: Conference Series. 910, 012020, 2017.
[13] Chang, V., Knowledge-Based Systems, 127, 29, 2017.
[14] Sergei, S., Bogomolov, A., Ronzhin, A., Mathematics, 9,2920, 2021.
[15] Lobell, D.B., Burke, M. B., Agricultural and forest meteorology, 150,1443, 2010. Pakistan Bureau of Statistics Islamabad, 2017.
[16] Pakistan Bureau of Statistics., 2017.
[17] Pakistan, G.O., Pakistan bureau of statistics, 2017.
[18] Jameel, A., Mahmood, A., Jafri, S.A.A., Pakistan Journal of Meteorology, 2, 2005.
[19] Levenberg, K., Quarterly of applied mathematics, 2, 164, 1944.
[20] Bjo¨rck, A˚., Handbook of numerical analysis, 1, 465, 1990.
[21] Abdi, H., others., Encyclopedia of measurement and statistics, 1, 530, 2007.
[22] Yuvaraj, R., The Scientific World Journal, 2020, 2020.
[23] Liu, P.G., Tsai, J., Lai, H., Tsai, D., Li, L., Atmospheric Environment, 79, 225, 2013.
[24] Tahir, A., Ashraf, M., Akhter, M., Uddin, Z., Sarim, M., Global NEST Journal, 23, 519, 2021.
[25] Godfrey, K., New England Journal of Medicine, 313, 1629, 1985.
[26] Sara, L., Journal of the Korean Statistical Society, 51, 25, 2022.
[27] Zhu, H., Zhang, R., Liu, Y., Ding, H., Journal of the Korean Statistical Society, 51, 1041, 2022.
[28] Burkart, N., Huber, M.F., Journal of Artificial Intelligence Research, 70, 245, 2021.
[29] Nasteski, V., Horizons. b, 4, 51, 2017.
[30] Ahn, S., Choi, H., Lim, J., Lee, K.E., Journal of the Korean Statistical Society, 49,161, 2020.
[31] Choi, H., Kim, J., Kim, Y., Journal of the Korean Statistical Society, 39(4):479–487, 2010.
[32] Li, Y., Zha, H., Zhou, Z., Proceeding of the AAAI conference on Artificial Intelligence. 31, 2017.
[33] Osisanwo, F., Akinsola, J., Awodele, O., Hinmikaiye, J., Olakanmi, O., Akinjobi, j. et al., International Journal of Computer Trends and Technology (IJCTT), 48, 128, 2017.
[34] Schwenker, F., Trentin, E., Pattern Recognition Letters, 37, 4, 2014.
[35] Anjali, T., Chandini, K., Anoop, K., Lajish, V., 2019 2nd International conference on intelligent computing, instrumentation and control technologies (ICICICT), 1, 1264, 2019.
[36] Mayr, A., Klambauer, G., Unterthiner, T., Hochreiter, S., Frontiers in Environmental Science, 3, 80, 2016.
[37] Kim, T.Y., Park, I., Journal of the Korean Statistical Society, 50, 756, 2021.
[38] LeCun, Y., Bengio, Y., Hinton, G., Nature, 521, 436, 2015.
[39] Goodfellow, I., Bengio, Y., Courville, A., Deep learning. MIT press, Cambridge, 2016.
[40] Schmidhuber, J., Neural networks, 61, 85, 2015.
[41] Nielsen, M.A., Neural networks and deep learning, Determination press San Francisco, CA, USA, Washington, 2015.
[42] Ketkar, N., Santana, E., Deep learning with Python, Springer, New York, 2017.
[43] Nwankpa, C., Ijomah, W., Gachagan, A., Marshall, S., arXiv preprint arXiv:1811.03378, 2018.
[44] Zhang, G., Pan, Y., Zhang, L., Automation in Construction, 133, 104016, 2022.
[45] Paszyn´ski, M., Grzeszczuk, R., Pardo, D., Demkowicz, L., International Conference on Computational Scienc, 114–121, 2021.
Published
2025-08-09
How to Cite
Tufail, M., & Gul, S. (2025). Artificial Intelligence and Statistical Regression for the Prediction of Temperature over Sukkur Region. International Journal of Artificial Intelligence & Mathematical Sciences, 3(2), 50-61. https://doi.org/10.58921/ijaims.v3i2.125
