Forecasts Modeling in Industrial Applications Based on Artificial Intelligence Techniques

The management of industrial systems involves decision making with respect to complex processes that are often stochastic in nature. Simulation is frequently the only effective mean to model the complexity of such industrial processes. Simulation enables detailed scenario testing and, thus, is well suited for "what if" analysis. However, industrial users often need to solve inverse problems, such as optimization or decision analysis, which cannot be handled by simulation alone. This paper proposes the integrated use of simulation and Artificial Intelligence techniques in hybrid system architectures for advanced industrial problem solving. Hybrid Decision Support Systems (DSSs), combine the complementary strengths of different techniques for integrated forecasting ,modeling, and optimization.