Prediction of littoral drift with Adaptive Neuro-Fuzzy Inference System
Journal Title: Annals of Warsaw University of Life Sciences – SGGW. Land Reclamation - Year 2010, Vol 42, Issue 1
Abstract
The amount of sand moving parallel to a coastline forms a prerequisite for many harbor design projects. Such information is currently obtained through various empirical formulae. Despite so many works in the past, an accurate and reliable estimation of the rate of sand drift has still remained a problem. It is a nonlinear process and can be described by chaotic time series. The current study addresses this issue through the use of Adaptive Neuro-Fuzzy Inference System (ANFIS). ANFIS is about taking an initial fuzzy inference system (FIS) and tuning it with a back propagation algorithm based on the collection of input-output data. ANFIS was developed to predict the sand drift from a variety of causative variables. The structure and algorithm of ANFIS for predicting the rate of sand drift is described. The Adaptive Neuro-Fuzzy Inference System was validated by confirming its consistency with a database of specified physical process.
Authors and Affiliations
MASUMEH SABET, MEHDI NASERI, HOSEIN SABET
Keywords
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