Application of Gamma Test and Neuro-Fuzzy Models in Uncertainty Analysis for Prediction of Pipeline Scouring Depth

ISSN Print: 1945-3094
ISSN Online: 1945-3108
www.scirp.org/Journal/jwarp
E-mail: jwarp@scirp.org

"Application of Gamma Test and Neuro-Fuzzy Models in Uncertainty Analysis for Prediction of Pipeline Scouring Depth"
written by Naser Niknia, Hossein Kardan Moghaddam, S. M. Banaei, Hassan Torabi Podeh, Fereydoon Omidinasab, Azam Arabi Yazdi,
published by Journal of Water Resource and Protection, Vol.6 No.5, 2014

has been cited by the following article(s):

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[3]	Predicting BOD under Various Hydrological Conditions in the Dongjin River Basin Using Physics-Based and Data-Driven Models
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[4]	Real-Time Flood Disaster Prediction System by Applying Machine Learning Technique
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[5]	도시지역의 수재해 예측을 위한 강우시나리오의 불확실성 분석
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[6]	Uncertainty Analysis of Rainfall Scenarios for the Prediction of Flood Disasters in Urban Areas
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[7]	Estimation of Scour Depth in Pipelines Laid on the Seabed under Live Bed Condition using a Hybrid [M5]^'-GLUE Model
	2018

[8]	Comparative Performance of Multiple Linear Regression and Artificial Neural Network Based Models in Estimation of Evaporation
	Advances in Research, 2017

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[5]	Uncertainty Analysis of Rainfall Scenarios for the Prediction of Flood Disasters in Urban Areas Journal of the Korean Society of Hazard Mitigation, 2019 DOI:10.9798/KOSHAM.2019.19.2.255