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Designing Software for Risk Assessment Using a Neural Network

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dc.contributor.authorLebedeva, A. V.
dc.contributor.authorGuseva, A. I.
dc.contributor.authorЛебедева, Анна Валерьевна
dc.contributor.authorГусева, Анна Ивановна
dc.contributor.otherФакультет бизнес-информатики и управления комплексными системами
dc.date.accessioned2024-11-29T10:42:22Z
dc.date.available2024-11-29T10:42:22Z
dc.date.issued2021
dc.description.abstract© 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.This article presents the results of the research in terms of using mathematical methods for the risk management process in the implementation of software development projects. Software development projects are not always implemented in a final form that meets the expectations of customers. Both internal and external factors can influence this. In this regard, the problems of risk management, which inevitably arise during the implementation of software development projects, become particularly relevant due to the large uncertainty of the internal and especially external environment of enterprises. The introduction of a comprehensive approach to risk management allows the company to form an objective view of the current and planned activities of the organization, taking into account possible negative events or new opportunities, anticipate risks and make decisions based on information about them, respond to risks in a timely manner and reduce the negative impact of risks in their implementation. Within the framework of this research, the risk assessment software is designed to assess the situation in the project, predict the future effectiveness of the project, and build scenarios to support decision-making. Such software will allow to combine all the actions of the analyst in one tool, where all the information about the project and the external environment will be stored, updated and constantly used for training the Neural Network apparatus on which the software is designed. This work was supported by Russian Foundation for Basic Research (RFBR) grant № 20-010-00708\20.
dc.format.extentС. 181-187
dc.identifier.citationLebedeva, A. V. Designing Software for Risk Assessment Using a Neural Network / Lebedeva, A.V., Guseva, A.I. // Advances in Intelligent Systems and Computing. - 2021. - 1310. - P. 181-187. - 10.1007/978-3-030-65596-9_23
dc.identifier.doi10.1007/978-3-030-65596-9_23
dc.identifier.urihttps://www.doi.org/10.1007/978-3-030-65596-9_23
dc.identifier.urihttps://www.scopus.com/record/display.uri?eid=2-s2.0-85098202853&origin=resultslist
dc.identifier.urihttps://openrepository.mephi.ru/handle/123456789/23507
dc.relation.ispartofAdvances in Intelligent Systems and Computing
dc.titleDesigning Software for Risk Assessment Using a Neural Network
dc.typeConference Paper
dspace.entity.typePublication
oaire.citation.volume1310
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relation.isAuthorOfPublication23b35aa9-9178-4bd2-8518-a31c29111cb9
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