Multilayer feedforward networks are universal approximators
Neural Networks
Computer Vision and Fuzzy-Neural Systems
Computer Vision and Fuzzy-Neural Systems
An expert system for predicting aeration performance of weirs by using ANFIS
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Predicting flow conditions over stepped chutes based on ANFIS
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Advances in Engineering Software
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Artificial intelligent methods are today extensively used in many areas. They are known as powerful tools to solve engineering problems with uncertainties. The purpose of this study was to develop a model, using artificial intelligent methods, for estimating air-demand ratio in venturi weirs. For this aim, Adaptive Network based Fuzzy Inference Systems (ANFIS) and Artificial Neural Network (ANNs) methods were used. The test results revealed that ANFIS model predicted the measured values at higher accuracy than ANNs model. Average correlation coefficients (R^2) in ANFIS models were achieved equal to 0.9623 for @b=0.75 and 0.9666 for @b=0.50. Extremely good agreement between the predicted and measured values confirms that ANFIS model can be successfully used to predict air-demand ratio in venturi weirs.