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
Analogue methods (AMs) rely on the hypothesis that similar situations, in terms of atmospheric circu...
Wind speed and its direction at two offshore locations along the west coast of India are predicted o...
This paper discusses the formation of an appropriate regression model in precipitation prediction. P...
AbstractWe use genetic programming (GP), a variant of evolutionary computation, to build interpretab...
The last ten years has seen the introduction and rapid growth of a market in weather derivatives, fi...
Weather systems use enormously complex combinations of numerical tools for study and forecasting. Un...
AbstractWeather forecasting is complex and not always accurate, moreover, it is generally defined by ...
BACKGROUND In recent years, the price drop in off-the-shelf computer systems has enabled small insti...
Genetic programming (GP), a relatively new evolutionary technique, is demonstrated in this study to ...
Title from first page of PDF file (viewed September 9, 2010) ; Includes bibliographical references (...
Genetic programming (or GP) is a random search technique that emerged in the late 1980s and early 19...
This dissertation describes research to enhance hydrometeorological forecasts and their application ...
Abstract: The precipitations are characterized by important spatial and temporal variation. Model de...
AbstractThe need for reliable predictions in environmental modelling is well-known. Particularly, th...
The need for reliable predictions in environmental modelling is well-known. Particularly, the predic...
Analogue methods (AMs) rely on the hypothesis that similar situations, in terms of atmospheric circu...
Wind speed and its direction at two offshore locations along the west coast of India are predicted o...
This paper discusses the formation of an appropriate regression model in precipitation prediction. P...
AbstractWe use genetic programming (GP), a variant of evolutionary computation, to build interpretab...
The last ten years has seen the introduction and rapid growth of a market in weather derivatives, fi...
Weather systems use enormously complex combinations of numerical tools for study and forecasting. Un...
AbstractWeather forecasting is complex and not always accurate, moreover, it is generally defined by ...
BACKGROUND In recent years, the price drop in off-the-shelf computer systems has enabled small insti...
Genetic programming (GP), a relatively new evolutionary technique, is demonstrated in this study to ...
Title from first page of PDF file (viewed September 9, 2010) ; Includes bibliographical references (...
Genetic programming (or GP) is a random search technique that emerged in the late 1980s and early 19...
This dissertation describes research to enhance hydrometeorological forecasts and their application ...
Abstract: The precipitations are characterized by important spatial and temporal variation. Model de...
AbstractThe need for reliable predictions in environmental modelling is well-known. Particularly, th...
The need for reliable predictions in environmental modelling is well-known. Particularly, the predic...
Analogue methods (AMs) rely on the hypothesis that similar situations, in terms of atmospheric circu...
Wind speed and its direction at two offshore locations along the west coast of India are predicted o...
This paper discusses the formation of an appropriate regression model in precipitation prediction. P...