Application of Gamma Test and Neuro-Fuzzy Models in Uncertainty Analysis for Prediction of Pipeline Scouring Depth
Application of Gamma Test and Neuro-Fuzzy Models in Uncertainty Analysis for Prediction of Pipeline Scouring Depth作者机构：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
出 版 物：《Journal of Water Resource and Protection》 (水资源与保护（英文）)
年 卷 期：2014年第6卷第5期
页 面：514-525页
学科分类：1002[医学-临床医学] 100214[医学-肿瘤学] 10[医学]
主 题：Pipelines Local Scour Gamma Test ANFIS
摘 要：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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