Title: Analysis of weather data using various regression algorithms

Authors: Yeturu Jahnavi

Addresses: Department of Computer Science and Engineering, Geethanjali Institute of Science and Technology, Nellore, Andhra Pradesh, 524137, India

Abstract: Weather forecasting is a vital application in meteorology and has been one of the most challenging problems around the world. Data mining is a process that uses a variety of data analysis tools to discover patterns and relationships in data that may be used to make valid predictions. This is carried out using several regression algorithms. This paper focuses on weather analysis using various regression algorithms in data mining. In this work, linear regression, classification and regression tree, multilayer perceptron neural network and support vector machine (SVM) are used. For weather analysis various primary atmospheric parameters such as average temperature, average pressure and relative humidity are considered. The performance is analysed using various evaluation measures. Evaluation criteria like root mean square error, mean absolute error, relative absolute error and root relative square error are used for measuring the performance of regression algorithms.

Keywords: data mining; weather prediction; regression algorithms.

DOI: 10.1504/IJDS.2019.100321

International Journal of Data Science, 2019 Vol.4 No.2, pp.117 - 141

Received: 11 Mar 2017
Accepted: 27 Dec 2017
Published online: 26 Jun 2019 *

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