A Conceptual Approach to NonLinear Identification and Modeling Based on Expert Opinions

In order to model uncertainty involved into a real-world process, a general approach combining both analytical and expert knowledge-based techniques to identify a nonlinear system model is proposed. The approach leads to using a new type of stochastic dependence of random processes, involving expert opinion, and which is a generalization of the disperssional identification technique.