ABSTRACT
This chapter introduces a limited amount of fundamentals on artificial neural networks (ANN) to a beginner to get him/her started on using this modeling technique. It emphasizes on how to develop artificial neural network-based models using selected examples. Each application example is presented with step-by-step solution procedure that includes major results. An artificial neural network is a computational structure and is characterized by net topology, node characteristics, and learning rules. In principle, artificial neural networks can compute any mathematical function. In food related areas, ANNs have most often been employed as flexible, nonlinear regression, and classification models. Because it is a data-driven modeling technique, it requires data that include both the inputs and the desired results. Use an artificial neural network approach to develop a single and direct procedure for estimating the heat transfer coefficient to avoid the use of a time-consuming, iterative solution.
