What is it about?
This study develops and applies a novel classification-forecasting model, namely Binary GP (BGP), for teleconnection studies between sea surface temperature (SST) variations and maximum monthly rainfall (MMR) events
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Why is it important?
The potential of GP to solve binary classification problems in hydrology has been explored in this paper. A particular attention is given to the data pre- and post-processing techniques as well as evaluation criteria required for the verification of the proposed Binary GP model. In order to perform the proposed BGP model, a new subroutine was written by the authors and added to the open-source GP software GPdotNet® (Hrnjica; 2009). GPdotNet is an artificial intelligence tool for applying GA and ANN in modeling, prediction, optimization and pattern recognitions.
Perspectives
Writing this article was a great pleasure as it has co-authors with outstanding back ground in genetic programming. I hope the methodology and the software presented in this article be used and discussed by other researchers.
Dr ALI DANANDEH MEHR
Antalya Bilim University
Read the Original
This page is a summary of: A binary genetic programing model for teleconnection identification between global sea surface temperature and local maximum monthly rainfall events, Journal of Hydrology, December 2017, Elsevier,
DOI: 10.1016/j.jhydrol.2017.10.039.
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Contributors
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