Prediction of Heat Transfer Rate of a Wire-on-Tube Type Heat Exchanger: An Artificial Intelligence Approach

In this paper, an innovative approach is used to predict the rate of heat transfer of a wire-on-tube type heat exchanger by utilizing the support vector machine model. Heat exchangers have been a well-studied subject over the past decades. Various approaches have been used to determine the heat transfer rate of heat exchangers. To solve this algorithm, a computer program was developed using MATLAB software. This helped us formulate an equation for the total heat transfer which gave minimal error when compared to traditional techniques. This model exhibits inherent advantages due to its use of the structural risk minimization principle in formulating cost functions and of quadratic programming during model optimization. A comparative study between the artificial neural network and the support vector machine approach is also illustrated. The paper then provides its conclusion.