Adaptive Cascade Bagging of Neuro-Fuzzy Models for the Classification of Defects in Renewable Energy Facilities
The work solves the problem of increasing the accuracy and efficiency of the classification of defects in renewable energy facilities under conditions of limited computing resources and uncertainty of input data. An adaptive intelligent system based on cascade bagging of neuro-fuzzy models has been proposed, which combines the hypersector Fuzzy LVQ method, the associative FBSB model and the modified Wang–Mendel method.