Folorunsho Olaiya; Adesesan Barnabas Adeyemo

Application of Data Mining Techniques in Weather Prediction and Climate Change Studies

Full Text (PDF, 500KB), PP.51-59

Views: 0 Downloads: 0

Author(s)

Folorunsho Olaiya ^1,* Adesesan Barnabas Adeyemo ²

1. Department of Computer & Information Systems, Achievers University, Owo, Nigeria

2. University of Ibadan, Ibadan, Nigeria

* Corresponding author.

DOI: https://doi.org/10.5815/ijieeb.2012.01.07

Received: 8 Nov. 2011 / Revised: 20 Dec. 2011 / Accepted: 14 Jan. 2012 / Published: 8 Feb. 2012

Index Terms

Weather Forecasting, Data Mining, Artificial Neural Networks, Decision Trees

Abstract

Weather forecasting is a vital application in meteorology and has been one of the most scientifically and technologically challenging problems around the world in the last century. In this paper, we investigate the use of data mining techniques in forecasting maximum temperature, rainfall, evaporation and wind speed. This was carried out using Artificial Neural Network and Decision Tree algorithms and meteorological data collected between 2000 and 2009 from the city of Ibadan, Nigeria. A data model for the meteorological data was developed and this was used to train the classifier algorithms. The performances of these algorithms were compared using standard performance metrics, and the algorithm which gave the best results used to generate classification rules for the mean weather variables. A predictive Neural Network model was also developed for the weather prediction program and the results compared with actual weather data for the predicted periods. The results show that given enough case data, Data Mining techniques can be used for weather forecasting and climate change studies.

Cite This Paper

Folorunsho Olaiya, Adesesan Barnabas Adeyemo, "Application of Data Mining Techniques in Weather Prediction and Climate Change Studies", International Journal of Information Engineering and Electronic Business(IJIEEB), vol.4, no.1, pp.51-59, 2012. DOI:10.5815/ijieeb.2012.01.07

Reference

[1]Ahrens, C. D., 2007, "Meteorology" Microsoft® Student 2008 [DVD], Redmond, WA: Microsoft Corporation, 2007.

[2]Bregman, J.I., Mackenthun K.M., 2006, Environmental Impact Statements, Chelsea: MI Lewis Publication.

[3]Casas D. M, Gonzalez A.T, Rodrígue J. E. A., Pet J. V., 2009, “Using Data-Mining for Short-Term Rainfall Forecasting”, Notes in Computer Science, Volume 5518, 487-490

[4]Due R. A., 2007, A Statistical Approach to Neural Networks for Pattern Recognition, 8th edition. New York: John Wiley and Sons publication.

[5]Elia G. P., 2009, “A Decision Tree for Weather Prediction”, Universitatea Petrol-Gaze din Ploiesti, Bd. Bucuresti 39, Ploiesti, Catedra de Informatică, Vol. LXI, No. 1

[6]Fairbridge R. W., 2007, "Climate" Microsoft® Student 2008 [DVD], Redmond, WA: Microsoft Corporation, 2007.

[7]Han, J., Micheline K., 2007, Data Mining: Concepts and Techniques, San Fransisco, CA: Morgan Kaufmann publishers.

[8]Martin T. H., Howard B. D, Mark B., 2002, Neural Network Design, Shanghai: Thomson Asia PTE LTD and China Machine Press.

[9]Quinlan, J.R., 1997: See5 (available from http://www.rulequest.com/see5-info.html).

[10]Rushing J. R., Ramachandran U, Nair S., Graves R., Welch, Lin A., 2005, “A Data Mining Toolkit for Scientists and Engineers”, Computers & Geosciences, 31, 607-618.

[11]Wikipedia, 2010, "Effects of Global Warming" From Wikipedia - the free encyclopedia, retrieved from http://en.wikipedia.org/wiki/Effects_of_Global_Warming in March 2010

[12]Wikipedia, 2011, "Climate change" From Wikipedia - the free encyclopedia, retrieved from http://en.wikipedia.org/wiki/Climate_change in August 2011

International Journal of Information Engineering and Electronic Business (IJIEEB)