Author(s)

Naser Niknia, Hossein Kardan Moghaddam, S. M. Banaei, Hassan Torabi Podeh, Fereydoon Omidinasab, Azam Arabi Yazdi

Agricultural Meteorology, Department of Water Engineering, Ferdowsi University of Mashad, Mashhad, Iran.
Agriculture Faculty, Lorestan University, Khoramabad, Iran.
Department of Water Engineering, Lorestan University, Khoramabad, Iran.
Faculty Member of Birjand University of Technology, Birjand, Iran.
Faculty Member of Birjand University, Birjand, Iran.
Structural Eng., Lorestan University, Khoramabad, Iran.

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.

Pipelines, Local Scour, Gamma Test, ANFIS

Niknia, N. , Moghaddam, H. , Banaei, S. , Podeh, H. , Omidinasab, F. and Yazdi, A. (2014) Application of Gamma Test and Neuro-Fuzzy Models in Uncertainty Analysis for Prediction of Pipeline Scouring Depth. Journal of Water Resource and Protection, 6, 514-525. doi: 10.4236/jwarp.2014.65050.