ANALYSIS OF MODERN METHODS OF THE FINANCIAL CONDITION OF THE ENTERPRISE EVALUATION

Анотація

The article investigates scientific approaches to the financial condition of enterprises analysis. The main methods of assessing the financial condition of enterprises are identified. The problem of financial recovery of enterprises in the context of strengthening their financial condition is considered. The essence of financial recovery of enterprises according to different approaches is analyzed, the ways of financial recovery in uncertainty conditions are given. The following methods of economic phenomena research and processes are used: scientific abstraction (theoretical generalizations of the most essential approaches to financial recovery), graphic (schematic visualization of algorithm of realization of financial recovery of the enterprises). The main tasks for a comprehensive assessment of the financial condition of enterprises are indicated. Different approaches to the definition of the category «comprehensive assessment of the financial condition of the enterprise» are analyzed. The advantages of introducing a comprehensive assessment of the financial condition of enterprises have been established. As a result of the existing methods and models analysis for assessing the financial condition of enterprises, it is determined that for the implementation of decision-making procedures there is a need to choose the optimal mathematical apparatus taking into account the specifics of solving a particular financial problem. It is proposed to formalize financial objects on the basis of artificial intelligence devices. In particular, the theory of fuzzy sets allows taking into account the different parameters of the object under study, as well as to stratify the evaluation process and analyze a powerful set of evaluation parameters. The theory of neural networks allows solving the problems of pattern recognition and formation, obtaining and storing knowledge (empirically found regular connections of images and influences on the object of control), qualitative characteristics of images evaluation, decision-making. The theory of genetic algorithms allows the debugging of models that solve the problem of compiling different schedules, forecasting economic processes, designing complex systems and more. It is substantiated that the use of fuzzy sets, neural networks and genetic algorithms in assessing the financial condition of the enterprise is a promising area of financial decision support systems development.

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