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Boosted Regression Tree for Modeling Evaporation Piche Using Other Climatic Factors Over Ilorin

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  • Ezekiel I. D.*

    (Department of Mathematics and Statistics, Federal Polytechnic Ilaro, Ogun State, Nigeria)

  • Alabi N. O.

    (Department of Mathematics and Statistics, Federal Polytechnic Ilaro, Ogun State, Nigeria)

Abstract

Evaporation is one of the climatic/meteorological factors influenced by causes of climate change. Interest in the topic of climate change has been growing over the last three decades. The threat it poses cannot be overemphasized particularly in developing economies largely due to the connection it has with national development issues. We present a regression tree grown using recursive binary splitting, cost complexity pruning and boosting to study the relationship between evaporation piche and other climatic factors such as relative humidity, solar radiation, sunshine hours, wind speed, temperature and rainfall over the city of Ilorin in Nigeria. These factors are generally seen to change with rising climatic changes in a place. Analysis of the fitted tree reveals that relative humidity, temperature and rainfall are the most important meteorological factors affecting the level of evaporation piche in the city of Ilorin.

Suggested Citation

  • Ezekiel I. D.* & Alabi N. O., 2018. "Boosted Regression Tree for Modeling Evaporation Piche Using Other Climatic Factors Over Ilorin," Academic Journal of Applied Mathematical Sciences, Academic Research Publishing Group, vol. 4(9), pages 98-106, 09-2018.
    • Handle: RePEc:arp:ajoams:2018:p:98-106
    DOI: arpgweb.com/?ic=journal&journal=17&info=aims
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    1. Sungwon Kim & Jalal Shiri & Ozgur Kisi, 2012. "Pan Evaporation Modeling Using Neural Computing Approach for Different Climatic Zones," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(11), pages 3231-3249, September.
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