Advances in Intelligent Systems and Computing
Modern cybernetics and computer engineering papers and topics are presented in
the proceedings. This proceedings is a Vol. 3 of the Computer Science On-line
Conference proceedings. Papers in this part discuss modern cybernetics and applied
informatics in technical systems.
This book constitutes the refereed proceedings of the Applied Informatics and
Cybernetics in Intelligent Systems section of the 9th Computer Science On-line
Conference 2020 (CSOC 2020), held on-line in April 2020.
CSOC 2020 has received (all sections) more than 270 submissions from more
than 35 countries. More than 65% of accepted submissions were received from
Europe, 21% from Asia, 8% from Africa, 4% from America and 2% from Australia.
CSOC 2020 conference intends to provide an international forum for the discussion
of the latest high-quality research results in all areas related to Computer
Computer Science On-line Conference is held on-line, and modern communication
technology, which are broadly used, improves the traditional concept of
scientific conferences. It brings equal opportunity to participate for all researchers
around the world.
Analytical justification of decision options using decision support systems (DSS) significantly improves the quality of decisions. The use of the currently existing DSS, which usually includes one or two decision-making methods, does not always lead to the desired results, since each method is based on certain assumptions and is not universal. The noticeable effect is achieved when many decision-making methods are included in one DSS knowledge base. The systems that meet these requirements belong to the class of Expert Decision Support Systems (EDSS), which currently includes more than 50 decisionmaking methods. Expanding the EDSS knowledge base, made by including new methods in it, allows choosing the most suitable solution method for each decision-making task. Addition of the decision table model, which is the basis of the system knowledge base, allows developing EDSS without completely processing the system program code. The ELECTRE methods were adopted for expanding the EDSS knowledge base. The basis for the selection was their key feature, which consists in the fact that they do not use the alternative valuation convolution operation given in different scales according to individual criteria. The article shows the adapted algorithms of the ELECTRE family methods ready for inclusion in EDSS. The algorithm is proposed for obtaining a criterion matrix being based on alternatives that serve as input information for the ELECTRE methods in cases where there is no objective information to fill it. The results of the study can be used to develop EDSS, that open the way to analytically substantiate solutions using methods that were not previously used in the system.