Drought Modelling Using Artificial Intelligence Algorithms in Izmir District

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Date

2022

Authors

Zeynep Irem Ozen
Berk Sadettin Tengerlek
Damla Yuksel
Efthymia Staiou
Mir Jafar Sadegh Safari

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Volume Title

Publisher

SPRINGER-VERLAG SINGAPORE PTE LTD

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Green Open Access

No

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Abstract

The world's water resources are decreasing day by day due to factors such as climate change drought inefficient pricing policies implemented by the government population growth uncontrolled water consumption technological developments and industrialization. A decrease in water resources causes water scarcity in the long-term period. This study is conducted to analysis the meteorological drought in Izmir district Turkey. Inspired by the real-life problem drought estimation models are developed through artificial neural network-based artificial intelligence techniques incorporating a decision support system. The Z-score index (ZSI) values are computed using precipitation data collected from five meteorological station in Kucuk Menderes basin and several developed models are compared according to the variety of statistical performance metrics.

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Keywords

Drought, Artificial neural networks, Feed forward backpropagation, Generalized regression, Radial basis function, Z-Score Index, NEURAL-NETWORKS, Feed Forward Backpropagation, Artificial Neural Networks, Generalized Regression, Radial Basis Function, Z-Score Index, Drought

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Source

21st International Symposium on Production Research (ISPR) - Digitizing Production System

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Start Page

689

End Page

701
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