REGIONALIZATION OF ARAS WATERSHED BY SOFM

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AHANI A.; MOUSAVI NADOUSHANI S.S.

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Paper Information

Journal: IRAN-WATER RESOURCES RESEARCH Year:2015 | Volume:10 | Issue:3 (31) Page(s): 88-98

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Information Journal Paper

Title

REGIONALIZATION OF ARAS WATERSHED BY SOFM

Author(s)

AHANI A. | MOUSAVI NADOUSHANI S.S. | Issue Writer Certificate

Keywords

KOHONEN SOFMQ2

CLUSTER ANALYSISQ3

L-MOMENTSQ2

FLOOD FREQUENCY ANALYSISQ2

Abstract

Self-Organizing Feature Maps (SOFM) are a category of artificial neural networks with a special ability in pattern recognition and data clustering using attributes of data points. In this study, ability of Kohonen self-organizing feature maps has been assessed in regionalization of Aras watershed in order to perform regional FLOOD FREQUENCY ANALYSIS. Results showed SOFM can be used as an efficient tool for data clustering and regionalization of watersheds. Furthermore the results showed that the cluster validity measure is equal to optimum value for regionalization of Aras watershed, when the number of regions is equal to 4. Also heterogeneity measures are equal to optimum values, when number of regions is equal to 2 or 4. However, when number of regions is equal to 2, largest regions can be formed.

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APA: Copy

AHANI, A., & MOUSAVI NADOUSHANI, S.S.. (2015). REGIONALIZATION OF ARAS WATERSHED BY SOFM. IRAN-WATER RESOURCES RESEARCH, 10(3 (31)), 88-98. SID. https://sid.ir/paper/100163/en

Vancouver: Copy

AHANI A., MOUSAVI NADOUSHANI S.S.. REGIONALIZATION OF ARAS WATERSHED BY SOFM. IRAN-WATER RESOURCES RESEARCH[Internet]. 2015;10(3 (31)):88-98. Available from: https://sid.ir/paper/100163/en

IEEE: Copy

A. AHANI, and S.S. MOUSAVI NADOUSHANI, “REGIONALIZATION OF ARAS WATERSHED BY SOFM,” IRAN-WATER RESOURCES RESEARCH, vol. 10, no. 3 (31), pp. 88–98, 2015, [Online]. Available: https://sid.ir/paper/100163/en

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