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Temperature Prediction using Machine Learning Approaches

Anjali T, Chandini K, Anoop K, Lajish V L
Computational Intelligence and Data Analytics (CIDA Lab)
Department of Computer Science
University of Calicut, India
๐Ÿ“ Paper

Abstract: Weather prediction is one of the most important research areas due to its applicability in real-world problems like meteorology, agricultural studies, etc. We propose a method for temperature prediction using three machine learning models - Multiple Linear Regression (MLR), Artificial Neural Network (ANN) and Support Vector Machine (SVM), through a comparative analysis using the weather data collected from Central Kerala during the period 2007 to 2015. The experimental results are evaluated using Mean Error (ME), Mean Absolute Error (MAE), Root Mean Square Error (RMSE) and Correlation Coefficients (CC). The error metrics and the CC shows that MLR is a more precise model for temperature prediction than ANN and SVM.

Weather Prediction Dataset: The dataset for this research was procured with the support from Agricultural Research Station, Anakkayam and College of Horticulture, Kerala Agricultural University, Vellanikkara. The weather data is procured from 3 different districts in Kerala - Malappuram, Calicut, and Thrissur. Since these districts are situated in the middle region of Kerala, the dataset can efficiently represent the weather conditions and variations of Central Kerala. The samples used for this study are collected from different sources. Daily values of pressure, humidity, wind speed, wind direction and temperature during 2009-2012 are taken from the Agricultural Research Station, Mannuthy, Thrissur. Monthly values of the dry bulb, wet bulb, number of rainy days, rainfall, humidity, and maximum temperature during 2009-2014 are collected from Agricultural Research Station, Anakkayam. Daily hourly data, including humidity, pressure, wind speed and wind direction during 2010 -2015 are collected from Calicut International Airport, Malappuram.

Acknowledgement
We thank Dr. B. Ajith Kumar, Assistant Professor and Head, Department of Agricultural Meteorology, College of Horticulture, Kerala Agricultural University, Vellanikkara, Thrissur and Dr. Abdul Hakkim V M, Professor (Soil and Water Engineering), College of Agriculture, Padannakkad, Kasargode for their assistance in data collection.

For inquiries, please contact:
Anoop K ๐Ÿ“ง [email protected] ๐ŸŒ website
Lajish V L ๐Ÿ“ง [email protected] ๐ŸŒ website
Anjali T ๐Ÿ“ง [email protected]

Citation

@inproceedings{anjali2019temperature,
  title={Temperature prediction using machine learning approaches},
  author={Anjali, T and Chandini, K and Anoop, K and Lajish, VL},
  booktitle={2019 2nd International Conference on Intelligent Computing, Instrumentation and Control Technologies (ICICICT)},
  volume={1},
  pages={1264--1268},
  year={2019},
  organization={IEEE},
  doi={10.1109/ICICICT46008.2019.8993316}
}

Related works

[1] Anjali T, Lajish V L, Anoop K, Manjary P Gangan, "Anomalous Weather Prediction in Kerala using Machine Learning Techniques". 32nd Kerala Science Congress, Abstract publisher: Kerala State Council for Science, Technology and Environment, 2020, pp. 170, ISBN: 978-81-942768-0-7. (Abstract)

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