TITLE:
Application of Gamma Test and Neuro-Fuzzy Models in Uncertainty Analysis for Prediction of Pipeline Scouring Depth
AUTHORS:
Naser Niknia, Hossein Kardan Moghaddam, S. M. Banaei, Hassan Torabi Podeh, Fereydoon Omidinasab, Azam Arabi Yazdi
KEYWORDS:
Pipelines, Local Scour, Gamma Test, ANFIS
JOURNAL NAME:
Journal of Water Resource and Protection,
Vol.6 No.5,
April
25,
2014
ABSTRACT: The
process involved in the local scour below pipelines is so complex as to make it
difficult to establish a general empirical model to provide accurate estimation
for scour. This paper describes the use of an adaptive neuro-fuzzy inference
system (ANFIS) and a Gamma Test (GT) to estimate the submerged pipeline scour
depth. The data sets of laboratory measurements were collected from published
literature and used to train the network or evolve the program. The developed
networks were validated by using the observations that were not involved in
training. The performance of ANFIS was found to be more effective when compared
with the results of regression equations and GT Network modelling in predicting
the scour depth of pipelines.