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

DOI: 10.4236/jwarp.2014.65050   PDF   HTML   XML   3,461 Downloads   4,710 Views   Citations


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.

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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.

Conflicts of Interest

The authors declare no conflicts of interest.


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