Comparative analysis of neuro-fuzzy systems of electrooptical images classification in uncertain environment
AbstractA comparative analysis of neuro-fuzzy algorithms is performed and their performance in classification of electrooptical images in an uncertain environment is investigated. Classification algorithms based on Kohonen, ANFIS, NEFCLASS neuro-fuzzy nets have been considered, and their comparison analysis has been conducted. A new method for classification of electrooptical images in the considered class of problems is proposed.
Methods of system analysis and control in conditions of risk and uncertainty