Modeling of Fluid Industry Based on FlexibleNeural Tree

Abstract

Realizing optimal control of fluid industry is a difficult problem due to its features of complexity, strong correlation, non-linear and uncertainty. For solving the problem, we propose build the whole model for it. Cement production process is taken as an instance, and its production process model is gotten by evolving flexible neural tree (FNT). The FNT model's structure and parameters are optimized by probabilistic incremental program evolution (PIPE) and simulation annealing (SA) respectively. The result demonstrates that the put forward method is effective and feasible for solving the problem.