TECHNOLOGICAL BASIS OF “INDUSTRY 4.0”
DEEP LEARNING OF COMPLEX INTERCONNECTED PROCESSES FOR BILEVEL OPTIMIZATION PROBLEM UNDER UNCERTAINTY
This research is focus on advanced modelling and design of complex interconnected processes. These processes are characterized by multiple inputs, outputs and state parameters as well as non-linearity, non–stationarity and uncertainty due to environmental disturbances. There are presented two models for deep learning and knowledge extraction using methods of multivalued logical and probable functions and networks model. These models can be applied for complex processes in the area of environment, transportation and complex systems working under uncertainty.