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Selection finance's source by method of machine learning


Martynova Yu.A.
(about the author)

Martynova Yuliya Anatolevna – (Saint-Petersburg State University of Aerospace Instrumentation (SUAI) )

Published in:
Russian Journal of Innovation Economics
– Volume 9, Number 3 (July-September 2019)

JEL classification: D81, С45, С65

Keywords: fuzzy logic, machine learning, neural network, performance evaluation


Citation:
Martynova Yu.A. (2019). Selection finance's source by method of machine learning. Russian Journal of Innovation Economics, 9(3), 1037-1048. doi: 10.18334/vinec.9.3.41177


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Abstract:

The results of choosing a financial institution for servicing organizations using the technologies used in machine learning, in particular, neural networks and fuzzy logic, are presented. In the conditions of insufficient information, traditional methods of solving such tasks do not work reliably enough, therefore, the work demonstrates a method for determining the best bank using these technologies. To search for the desired solution, the simulation of random values of those parameters that are responsible, in the opinion of the author, for the choice of a bank, was performed. Such a database of examples, which can be called "toy" is involved in the training of the neural network. In addition, it is shown the possibility of obtaining an assessment of the effectiveness of the selected institution for servicing the organization using fuzzy logic.








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Krichevskiy M.L., Martynova Yu.A. (2018). Instrumenty iskusstvennogo intellekta pri otsenke effektivnosti investitsionnogo proekta [Instruments of artificial intelligence in assessment of effectiveness of investment project]. Creative economy. 12 (8). 1105-1118. (in Russian). doi: 10.18334/ce.12.8.39265.
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