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| Main Author: | |
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| Format: | Artículo científico |
| Language: | en |
| Published: |
Universidad Nacional Autónoma de México
2016
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| Online Access: | https://www.redalyc.org/articulo.oa?id=56546701002 https://www.redalyc.org/journal/565/56546701002/ https://www.redalyc.org/journal/565/56546701002/html/ https://www.redalyc.org/journal/565/56546701002/56546701002.epub https://www.redalyc.org/journal/565/56546701002/movil |
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| _version_ | 1866585624000069632 |
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| author | BAHRAM CHOUBIN |
| author_facet | BAHRAM CHOUBIN |
| contents | Application of several data-driven techniques to predict a standardized precipitation index BAHRAM CHOUBIN ARASH MALEKIAN MOHAMMAD GOLSHAN Biología multi adaptive neuro M5P model tree climate signals Taylor diagrams Climate modeling and prediction is important in water resources management, especially in arid and semi-arid regions that frequently suffer further from water shortages. The Maharlu-Bakhtegan basin, with an area of 31000 km2 is a semi-arid and arid region located in southwestern Iran. Therefore, precipitation and water shortage in this area have many problems. This study presents a drought index modeling approach based on large-scale climate indices by using the adaptive neuro-fuzzy inference system (ANFIS), the M5P model tree and the multilayer perceptron (MLP). First, most of the climate signals were determined from 25 climate signals using factor analysis, and subsequently, the standardized precipitation index (SPI) was predicted one to 12 months in advance with ANFIS, the M5P model tree and MLP. The evaluation of the models performance by error parameters and Taylor diagrams demonstrated that performance of the MLP is better than the other models. The results also revealed that the accuracy of prediction increased considerably by using climate indices of the previous month (t – 1) (RMSE = 0.802, ME = –0.002 and PBIAS = –0.47). 2016 artículo científico 0187-6236 https://www.redalyc.org/articulo.oa?id=56546701002 https://www.redalyc.org/journal/565/56546701002/ https://www.redalyc.org/journal/565/56546701002/html/ https://www.redalyc.org/journal/565/56546701002/56546701002.epub https://www.redalyc.org/journal/565/56546701002/movil en http://www.redalyc.org/revista.oa?id=565 Atmósfera application/pdf Universidad Nacional Autónoma de México Atmósfera (México) Num.2 Vol.29 |
| format | Artículo científico |
| id | redalyc_56546701002 |
| language | en |
| publishDate | 2016 |
| publisher | Universidad Nacional Autónoma de México |
| spellingShingle | Application of several data-driven techniques to predict a standardized precipitation index BAHRAM CHOUBIN Biología multi adaptive neuro M5P model tree climate signals Taylor diagrams Application of several data-driven techniques to predict a standardized precipitation index BAHRAM CHOUBIN ARASH MALEKIAN MOHAMMAD GOLSHAN Biología multi adaptive neuro M5P model tree climate signals Taylor diagrams Climate modeling and prediction is important in water resources management, especially in arid and semi-arid regions that frequently suffer further from water shortages. The Maharlu-Bakhtegan basin, with an area of 31000 km2 is a semi-arid and arid region located in southwestern Iran. Therefore, precipitation and water shortage in this area have many problems. This study presents a drought index modeling approach based on large-scale climate indices by using the adaptive neuro-fuzzy inference system (ANFIS), the M5P model tree and the multilayer perceptron (MLP). First, most of the climate signals were determined from 25 climate signals using factor analysis, and subsequently, the standardized precipitation index (SPI) was predicted one to 12 months in advance with ANFIS, the M5P model tree and MLP. The evaluation of the models performance by error parameters and Taylor diagrams demonstrated that performance of the MLP is better than the other models. The results also revealed that the accuracy of prediction increased considerably by using climate indices of the previous month (t – 1) (RMSE = 0.802, ME = –0.002 and PBIAS = –0.47). 2016 artículo científico 0187-6236 https://www.redalyc.org/articulo.oa?id=56546701002 https://www.redalyc.org/journal/565/56546701002/ https://www.redalyc.org/journal/565/56546701002/html/ https://www.redalyc.org/journal/565/56546701002/56546701002.epub https://www.redalyc.org/journal/565/56546701002/movil en http://www.redalyc.org/revista.oa?id=565 Atmósfera application/pdf Universidad Nacional Autónoma de México Atmósfera (México) Num.2 Vol.29 |
| title | Application of several data-driven techniques to predict a standardized precipitation index |
| topic | Biología multi adaptive neuro M5P model tree climate signals Taylor diagrams |
| url | https://www.redalyc.org/articulo.oa?id=56546701002 https://www.redalyc.org/journal/565/56546701002/ https://www.redalyc.org/journal/565/56546701002/html/ https://www.redalyc.org/journal/565/56546701002/56546701002.epub https://www.redalyc.org/journal/565/56546701002/movil |