Enhanced combination modeling method for combustion efficiency in coal-fired boilers
Applied Soft Computing
Modeling rainfall-runoff process using soft computing techniques
Computers & Geosciences
Artificial bee colony algorithm and pattern search hybridized for global optimization
Applied Soft Computing
Variable Formulation Search for the Cutwidth Minimization Problem
Applied Soft Computing
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The necessity of sewers to carry sediment has been recognized for many years. Typically, old sewage systems were designated based on self-cleansing concept where there is no deposition in sewer. These codes were applicable to non-cohesive sediments (typically storm sewers). This study presents adaptive neuro-fuzzy inference system (ANFIS), which is a combination of neural network and fuzzy logic, as an alternative approach to predict the functional relationships of sediment transport in sewer pipe systems. The proposed relationship can be applied to different boundaries with partially full flow. The present ANFIS approach gives satisfactory results (r^2=0.98 and RMSE=0.002431) compared to the existing predictor.