MATHEMATICAL ASPECTS OF NEURO-FUZZY TECHNOLOGY APPLICATION IN PROJECT MANAGEMENT

Elena Kiseleva, Olga Prytomanova, Sergiy Zhuravel

Abstract


The combination of neural networks and fuzzy logic provides the core of neuro-fuzzy technologies, are fundamentally different mathematical constructions. Artificial neural networks are considered as universal models of the human brain, capable of learning the recognition of unknown regularities. Artificial neural networks are built on the principle of organization and functioning of their biological analogues (networks of human brain neurons). In recent years, neural networks have become a practice wherever problems of identification, prediction, classification, management need to be addressed.

Unlike neural networks, in which unstructured numerical data is used to find a solution to a problem through training and tuning, fuzzy technologies (fuzzy systems) use expert information about the regularities found in available experimental data in the form of natural language rules "IF-TO ". These rules are formalized with the help of fuzzy logic, they allow to build identification models with relatively small datasets.


Keywords


neuro-fuzzy technologies; fuzzy logic; efficiency analysis; project management; PMBOK PMI

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ISSN (Print) : 2449-7320

ISSN (Online) : 2449-8726