%0 Journal Article
%A Gorokhovatskiy, V. A.
%A Zamula, А. А.
%D 2016
%I Begell House
%K multiparametric control, fuzzy logic, model accuracy, knowledge base, membership function, quality parameters, linguistic variables, fuzzy inference systems, fuzzy model learning, commercial bank model
%N 19
%P 1775-1785
%R 10.1615/TelecomRadEng.v75.i19.60
%T EMPLOYMENT OF INTELLIGENT TECHNOLOGIES IN MULTIPARAMETRIC CONTROL SYSTEMS
%U http://dl.begellhouse.com/journals/0632a9d54950b268,00d03fa917720df5,460d387945e7e367.html
%V 75
%X It is suggested an approach to multiparametric control over the complex systems with application of the intelligent technologies. On the basis of fuzzy logic there are developed the models of formalization of controlling factors that allowed to adequately implement the quality parameters at functioning of the system. It is determined the fuzzy mechanism of modeling, and the knowledge base is designed based on the expert assessments and statistical data. Fuzzy model learning is implemented upon the criterion of minimization of the deviation error by means of adjusting the parameters of membership functions on the basis of the learning sample. The application problem is solved on the example of the commercial bank that confirmed improvement of the control accuracy over its financial indicators after implementing the fuzzy models.
%8 2017-03-01