Informations et ressources scientifiques
sur le développement des zones arides et semi-arides

Titre : Application of Wavelet Artificial Neural Networks in Forecasting Monthly and Seasonal Rainfall Using Temperature and Climate Indices : A Case Study of Queensland, Australia

Auteur : Ghamariadyan, Meysam

Université de soutenance : Swinburne University of Technology

Grade : Doctor of Philosophy (PhD) 2021

Résumé
Prediction of rainfall is of great importance for agriculture and industry, especially for the regions with high variability of climate, such as Australia. It also gives a chance to the decision-makers to overcome uncommon events such as floods and droughts. The research develops a new predictive model to forecast monthly and seasonal rainfall in Queensland, Australia. The method used in this study is based on a hybrid artificial neural network called wavelet ANN. This research could benefit agriculture and the society of Australia by providing excellent rainfall forecasts by mitigating the impacts of flooding and droughts.

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