Hidden behavior prediction of complex systems based on semi-quantitative information

In engineering, it is important to predict hidden behaviors of complex systems. The existing methods for predicting the hidden behavior cannot use semi-quantitative information. As such, in this paper a new BRB based model is proposed to predict the hidden behavior. In the proposed BRB based model, the initial values of parameters are usually given by experts, thus some of them may not be accurate, which can lead to inaccurate prediction results. In order to solve the problem, a parameter estimation algorithm for training the parameters of the forecasting model is further proposed on the basis of maximum likelihood (ML) algorithm. A case study is conducted to demonstrate the capability and potential applications of the proposed forecasting model with the parameter estimation algorithm.