BibTeX
@MISC{_meteorologicaldata,
author = {},
title = {Meteorological Data Analysis and Prediction by Means of Genetic Programming},
year = {}
}
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Abstract
Weather systems use extremely complex combinations of mathematical tools for anal-ysis and forecasting. Unfortunately, due to phenomena in the world climate, such as the greenhouse effect, classical models may become inadequate mostly because they lack adap-tation. Therefore, the weather prediction problem is suited for heuristic approaches, such as Evolutionary Algorithms. Experimentation with heuristic methods like Genetic Program-ming (GP) can lead to the development of new insights or promising models that can be fine tuned with more focused techniques. This paper describes a GP approach for analysis and prediction of data and provides experimental results of the afore mentioned method on real-world meteorological time series. 1.
Keyphrases
genetic programming meteorological data analysis real-world meteorological time series classical model heuristic method weather system world climate greenhouse effect weather prediction problem gp approach focused technique complex combination mathematical tool heuristic approach genetic program-ming new insight evolutionary algorithm experimental result
