Using intelligent methods to predict air-demand ratio in venturi weirs

Abstract

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.