Making Management Decisions in the Business Environment Based on Fuzzy Logic Methods
- DOI
- 10.2991/assehr.k.210322.192How to use a DOI?
- Keywords
- Expert systems, Business environment, Management decisions, Fuzzy logic, Uncertainty and risk conditions
- Abstract
The scientific research deals with the issues related to forming the structural component of ensuring managerial decision-making in business by using fuzzy logic in uncertainty and risk conditions. Improving the process of information support for management decision-making becomes possible by expanding the functional structure of expert systems (ES) in supporting services that adapt the ES functionality for the end-user ‒ organisations’ management. The article deals with further developing the information and analytical model for supporting the formation of management decisions in the conditions of constant changes and functional variability. The scientific hypothesis is that management decision-making in the business environment with the help of expert systems can be implemented through the formation of a new approach to the construction of a system for presenting the tasks to be solved by modifying the knowledge base into a two-level system (methodological-analytical and experimental levels). The scientific novelty is expressed in the functional modification of the approach to the formation and provision of data to accept administrative decisions based on changes in the analytical structure aimed at various tasks.
- Copyright
- © 2021, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Dmitry Stakhanov AU - Olga Grishchenko AU - Svetlana Fedortsova PY - 2021 DA - 2021/03/30 TI - Making Management Decisions in the Business Environment Based on Fuzzy Logic Methods BT - Proceedings of the VIII International Scientific and Practical Conference 'Current problems of social and labour relations' (ISPC-CPSLR 2020) PB - Atlantis Press SP - 647 EP - 652 SN - 2352-5398 UR - https://doi.org/10.2991/assehr.k.210322.192 DO - 10.2991/assehr.k.210322.192 ID - Stakhanov2021 ER -