Open AccessA combined method for designing operations using soft computing
Author(s) -
D. A. Rastorguev,
A. V. Zotov,
R. R. Dema,
Н. С. Соломатин
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/734/1/012164
Subject(s) - computer science , flexibility (engineering) , artificial neural network , inference , adaptive neuro fuzzy inference system , soft computing , fuzzy logic , artificial intelligence , neuro fuzzy , variety (cybernetics) , reliability (semiconductor) , fuzzy control system , machine learning , mathematics , statistics , physics , quantum mechanics , power (physics)
The article considers the possibility and features of shared use of two approaches of modern artificial intelligence: neural networks and fuzzy logic. Taking into account the advantages and disadvantages of each of the methods considered, the method of sequential use of these systems is considered. Fuzzy systems can be used for the initial creation of an expert inference system with its subsequent adjustment by optimization methods. It is possible to use the formation of a fuzzy inference system based on a hybrid neural net inference system based on control points obtained analytically or experimentally, followed by the generation of dataset for training neural networks. The use of these methods together increases the speed of operation designing, reliability of output, flexibility of approach to the choice of parameters, expansion of capabilities in production environments characterized by a wide variety of operations, materials, processing methods. An example of using this approach for the cladding method is given.