Drought Modelling Using Artificial Intelligence Algorithms in Izmir District

Zeynep İrem Özen; Berk Sadettin Tengerlek; Damla Yüksel; Efthymia Staiou; Mir Jafar Sadegh Safari

doi:10.1007/978-3-030-90421-0_59

Drought Modelling Using Artificial Intelligence Algorithms in Izmir District

Zeynep İrem Özen, Berk Sadettin Tengerlek, Damla Yüksel, Efthymia Staiou^*, Mir Jafar Sadegh Safari

^*Corresponding author for this work

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

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 Küçük Menderes basin, and several developed models are compared according to the variety of statistical performance metrics.

Original language	English
Title of host publication	Digitizing Production Systems - Selected Papers from ISPR 2021
Editors	Numan M. Durakbasa, M. Güneş Gençyılmaz
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	689-701
Number of pages	13
ISBN (Print)	9783030904203
DOIs	https://doi.org/10.1007/978-3-030-90421-0_59
Publication status	Published - 2022
Externally published	Yes
Event	International Symposium for Production Research, ISPR2021 - Virtual, Online Duration: 7 Oct 2021 → 9 Oct 2021

Publication series

Name	Lecture Notes in Mechanical Engineering
ISSN (Print)	2195-4356
ISSN (Electronic)	2195-4364

Conference

Conference	International Symposium for Production Research, ISPR2021
City	Virtual, Online
Period	7/10/21 → 9/10/21

Bibliographical note

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Keywords

Artificial neural networks
Drought
Feed forward backpropagation
Generalized regression
Radial basis function
Z-Score Index

Access to Document

10.1007/978-3-030-90421-0_59

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Özen, Z. İ., Tengerlek, B. S., Yüksel, D., Staiou, E., & Safari, M. J. S. (2022). Drought Modelling Using Artificial Intelligence Algorithms in Izmir District. In N. M. Durakbasa, & M. G. Gençyılmaz (Eds.), Digitizing Production Systems - Selected Papers from ISPR 2021 (pp. 689-701). (Lecture Notes in Mechanical Engineering). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-90421-0_59

Özen, Zeynep İrem ; Tengerlek, Berk Sadettin ; Yüksel, Damla et al. / Drought Modelling Using Artificial Intelligence Algorithms in Izmir District. Digitizing Production Systems - Selected Papers from ISPR 2021. editor / Numan M. Durakbasa ; M. Güneş Gençyılmaz. Springer Science and Business Media Deutschland GmbH, 2022. pp. 689-701 (Lecture Notes in Mechanical Engineering).

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title = "Drought Modelling Using Artificial Intelligence Algorithms in Izmir District",

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 K{\"u}{\c c}{\"u}k Menderes basin, and several developed models are compared according to the variety of statistical performance metrics.",

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doi = "10.1007/978-3-030-90421-0_59",

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Özen, Zİ, Tengerlek, BS, Yüksel, D, Staiou, E & Safari, MJS 2022, Drought Modelling Using Artificial Intelligence Algorithms in Izmir District. in NM Durakbasa & MG Gençyılmaz (eds), Digitizing Production Systems - Selected Papers from ISPR 2021. Lecture Notes in Mechanical Engineering, Springer Science and Business Media Deutschland GmbH, pp. 689-701, International Symposium for Production Research, ISPR2021, Virtual, Online, 7/10/21. https://doi.org/10.1007/978-3-030-90421-0_59

Drought Modelling Using Artificial Intelligence Algorithms in Izmir District. / Özen, Zeynep İrem; Tengerlek, Berk Sadettin; Yüksel, Damla et al.
Digitizing Production Systems - Selected Papers from ISPR 2021. ed. / Numan M. Durakbasa; M. Güneş Gençyılmaz. Springer Science and Business Media Deutschland GmbH, 2022. p. 689-701 (Lecture Notes in Mechanical Engineering).

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

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T1 - Drought Modelling Using Artificial Intelligence Algorithms in Izmir District

AU - Özen, Zeynep İrem

AU - Tengerlek, Berk Sadettin

AU - Yüksel, Damla

AU - Staiou, Efthymia

AU - Safari, Mir Jafar Sadegh

PY - 2022

Y1 - 2022

N2 - 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 Küçük Menderes basin, and several developed models are compared according to the variety of statistical performance metrics.

AB - 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 Küçük Menderes basin, and several developed models are compared according to the variety of statistical performance metrics.

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KW - Drought

KW - Feed forward backpropagation

KW - Generalized regression

KW - Radial basis function

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Özen Zİ, Tengerlek BS, Yüksel D, Staiou E, Safari MJS. Drought Modelling Using Artificial Intelligence Algorithms in Izmir District. In Durakbasa NM, Gençyılmaz MG, editors, Digitizing Production Systems - Selected Papers from ISPR 2021. Springer Science and Business Media Deutschland GmbH. 2022. p. 689-701. (Lecture Notes in Mechanical Engineering). doi: 10.1007/978-3-030-90421-0_59

Drought Modelling Using Artificial Intelligence Algorithms in Izmir District

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Keywords

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