Standard

Application of neural network algorithms to optimize the development of residential neighbourhoods. / Salnikov, Viktor; Pridvizhkin, Stanislav; Prokhorov, Vitalii и др.
в: E3S Web of Conferences, Том 419, 02033, 2023.

Результаты исследований: Вклад в журнал › Материалы конференции › Рецензирование

Harvard

Salnikov, V, Pridvizhkin, S, Prokhorov, V & Tokhtuev, A 2023, 'Application of neural network algorithms to optimize the development of residential neighbourhoods', E3S Web of Conferences, Том. 419, 02033. https://doi.org/10.1051/e3sconf/202341902033

APA

Salnikov, V., Pridvizhkin, S., Prokhorov, V., & Tokhtuev, A. (2023). Application of neural network algorithms to optimize the development of residential neighbourhoods. E3S Web of Conferences, 419, [02033]. https://doi.org/10.1051/e3sconf/202341902033

Vancouver

Salnikov V, Pridvizhkin S, Prokhorov V, Tokhtuev A. Application of neural network algorithms to optimize the development of residential neighbourhoods. E3S Web of Conferences. 2023;419:02033. doi: 10.1051/e3sconf/202341902033

Author

Salnikov, Viktor ; Pridvizhkin, Stanislav ; Prokhorov, Vitalii и др. / Application of neural network algorithms to optimize the development of residential neighbourhoods. в: E3S Web of Conferences. 2023 ; Том 419.

BibTeX

@article{f4b598672c9e4fbb8361ae15ebb9ee3e,
title = "Application of neural network algorithms to optimize the development of residential neighbourhoods",
abstract = "The paper presents proposals for the use of neural network algorithms to optimize the development of residential neighbourhoods: the corresponding model is shown, its features are discussed, the relevance and prospects for the development of the proposed approach in the planning of new residential neighbourhoods are substantiated. The proposed model allows to optimize the economic efficiency of residential neighbourhoods by varying the parameters of their design, construction, and operation, considering the characteristics of the life cycle of construction and investment projects. {\textcopyright} WFCES 2023.",
author = "Viktor Salnikov and Stanislav Pridvizhkin and Vitalii Prokhorov and Atrem Tokhtuev",
year = "2023",
doi = "10.1051/e3sconf/202341902033",
language = "English",
volume = "419",
journal = "E3S Web of Conferences",
issn = "2261-236X",
publisher = "EDP Sciences",

}

RIS

TY - JOUR

T1 - Application of neural network algorithms to optimize the development of residential neighbourhoods

AU - Salnikov, Viktor

AU - Pridvizhkin, Stanislav

AU - Prokhorov, Vitalii

AU - Tokhtuev, Atrem

PY - 2023

Y1 - 2023

N2 - The paper presents proposals for the use of neural network algorithms to optimize the development of residential neighbourhoods: the corresponding model is shown, its features are discussed, the relevance and prospects for the development of the proposed approach in the planning of new residential neighbourhoods are substantiated. The proposed model allows to optimize the economic efficiency of residential neighbourhoods by varying the parameters of their design, construction, and operation, considering the characteristics of the life cycle of construction and investment projects. © WFCES 2023.

AB - The paper presents proposals for the use of neural network algorithms to optimize the development of residential neighbourhoods: the corresponding model is shown, its features are discussed, the relevance and prospects for the development of the proposed approach in the planning of new residential neighbourhoods are substantiated. The proposed model allows to optimize the economic efficiency of residential neighbourhoods by varying the parameters of their design, construction, and operation, considering the characteristics of the life cycle of construction and investment projects. © WFCES 2023.

UR - http://www.scopus.com/inward/record.url?partnerID=8YFLogxK&scp=85171542536

U2 - 10.1051/e3sconf/202341902033

DO - 10.1051/e3sconf/202341902033

M3 - Conference article

VL - 419

JO - E3S Web of Conferences

JF - E3S Web of Conferences

SN - 2261-236X

M1 - 02033

ER -

ID: 45144156