https://libeldoc.bsuir.by/handle/123456789/45874
Title: | Machine learning methods for evaluating innovative projects |
Authors: | Shmeleva, A. Goldobin, I. Klimova, E. Moskvin, A. Lygarev, Y. |
Keywords: | материалы конференций;conference proceedings;learning methods;innovative projects |
Issue Date: | 2021 |
Publisher: | БГУИР |
Citation: | Machine learning methods for evaluating innovative projects / A. Shmeleva [et. al.] // Nano-Desing, Tehnology, Computer Simulations=Нанопроектирование, технология, компьютерное моделирование (NDTCS-2021) : тезисы докладов XIX Международного симпозиума, Минск, 28-29 октября 2021 года / Белорусский государственный университет информатики и радиоэлектроники ; редкол.: В. А. Богуш [и др.]. – Минск, 2021. – P. 111–112. |
Abstract: | The use of mathematical methods and machine learning algorithms based on them for solving applied decision-making problems is an urgent development of information technologies. Note that the proposed methods will automate and optimize the processing of projects submitted for consideration. In essence, the developed mathematical model and its implementation are a prototype of an expert decision-making system. The results obtained when solving the problem of evaluating innovative projects how the applicability of machine learning and artificial intelligence methods, which allow evaluating the characteristics of a project and selecting the most promising ones in order to minimize the risks of investors. |
URI: | https://libeldoc.bsuir.by/handle/123456789/45874 |
Appears in Collections: | NDTCS 2021 |
File | Description | Size | Format | |
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Shmeleva_Machine.pdf | 267.27 kB | Adobe PDF | View/Open |
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