R. A. Aliev & J. Kacprzyk 
15th International Conference on Applications of Fuzzy Systems, Soft Computing and Artificial Intelligence Tools – ICAFS-2022 

The general scope of the book covers diverse areas of fuzzy systems, soft computing, AI tools such as uncertain computation, decision-making under imperfect information, deep learning, and others. The topics of the papers include theory and application of Soft Computing, Neuro-Fuzzy Technology, Intelligent Control, Deep Learning-Machine Learning, Fuzzy Logic in Data Analytics, Evolutionary Computing, Fuzzy logic and Artificial Intelligence in Engineering, Social Sciences, Business, Economics, Material Sciences, and others.


This book presents the proceedings of the 16th International Conference on Applications of Fuzzy Systems, Soft Computing, and Artificial Intelligence Tools, ICAFS-2022, held in Budva, Montenegro, on August 26-27, 2022. This is a useful guide for academics, practitioners, and graduates in fields of fuzzy logic and soft computing. It allows for increasing of interest in development and applying of these paradigms in various real-life fields.

Inhaltsverzeichnis

On some de novo type approaches to fuzzy decision making, optimization and control: an application to sustainable regional development.- Summarization of bimodal information from large data sets.- Multi-attribute decision making in material selection under Z-valued information.- Decision making on students’ performance estimation.- Decision making on selection of Ferritic stainless steel.- Forecasting demand in the commodity market of food products using neural networks.- Estimation of countries’ economic development by using Z-number theory.- Optimal implication-based fuzzy control system for a steam generator.- Prediction of energy consumption in residential buildings using Type-2 fuzzy wavelet Neural Network.- Analysis of knee osteoarthritis grading using Deep Learning .- Solving problem of unit commitment by exchange market algorithm and dynamic planning method.- Regular Identification Algorithms for a Special Class of Neuro-Fuzzy Models ANFIS.