Developing 3-step modeling strategy exploiting knowledge based techniques

Abstract

Artificial neural networks have been used as an important technique in modeling and optimization for engineering design. In this work, 3-step modeling strategy based on knowledge based techniques is proposed to develop new efficient modeling instead of conventional artificial neural network (ANN) modeling. The knowledge based artificial neural networks are constructed by incorporating the existing knowledge such as empirical formulas, equivalent circuit models and semi-analytical equations in neural network structures. In this new technique, required knowledge is created in the first step and used in the second step as a coarse model. Therefore each model shows better performance than former. In this strategy, conventional ANN, prior knowledge input and prior knowledge input with difference techniques are utilized not only to improve modeling accuracy but also to reduce time consumption during modeling. The advantages of using 3-step modeling are demonstrated on Branin function modeling application.