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. This paper proposes the integrated use of simulation and Artificial Intelligence techniques in hybrid system architectures for advanced industrial problem solving.
Forecasts Modelling in Industrial Applications Based on AI Techniques
REVETRIA, ROBERTO;BRUZZONE, AGOSTINO;MOSCA, ROBERTO;ORSONI, ALESSANDRA
2001-01-01
Abstract
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. This paper proposes the integrated use of simulation and Artificial Intelligence techniques in hybrid system architectures for advanced industrial problem solving.
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