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Simulation of Residential Real Estate Markets in the Largest Russian Cities
Economy of Regions. 2022. Vol. 18. No. 2. P. 609–622.
Alekseev A.
The existing mass appraisal models and mathematical tools for predicting the market value of residential property have a number of disadvantages, as they are developed for individual regions. Without considering the constantly changing economic environment, these models quickly become outdated and require constant updating. Thus, they are not suitable for construction business optimisation. The study aims to create a universally applicable real estate appraisal system for Russian cities, regardless of the constantly changing economic situation. This goal was achieved through the creation of a neural network, whose input parameters include construction and operational data, geographical factors, time effect, as well as a number of indicators characterising the economic situation in specific regions, Russia and the world. In order to examine the dynamics of real estate markets in the Russian Federation, statistical data for neural network training were collected over a long period from 2006 to 2020. Virtual computer experiments were performed for testing the developed system. They showed that minimum size one-room apartments of 16 square meters have the highest unit cost per square meter in Moscow. Two-room apartments with an area of 90 square meters have the maximum price, as well as 100 sq. m. three-room, 110 sq. m. four-room and 120 sq. m. five-room apartments. In Ekaterinburg, two-room apartments with a total area of 30 square meters have the highest cost per square meter; the same applies for 110 sq. m. three-room, 130 sq. m. four-room and 150 sq. m. five-room apartment. Thus, the proposed system can be used to optimise the construction business. It can be also be useful for government institutions concerned with urban real estate market management, property taxation, and housing market improvement.
Language:
English
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The textbook presents methods and algoгithms for automatic analysis
of соrроrа of texts in natural languages. It is intended fоr sfudenБ of
methods of processing texts in паtчrаl languages and creating training
arays of texts.
Fоr students, graduate students and researchers studying methods
of computational linguistics and word processing. ...
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A. Radomskii, Mathematical notes 2026 Vol. 119 No. 6 P. 1136–1147
We obtain an upper bound for the sum $\sum_{n\leq N} (a_{n}/\varphi (a_{n}))^{s}$, where $\varphi$ is Euler's totient function, $s\in\mathbb{N}$, and $a_{1},\ldots, a_{N}$ are positive integers (not necessarily distinct) with some restrictions. As applications, for any $t>0$, we obtain an upper bound for the number of $n\in [1,N]$ such that $a_{n}/ \varphi (a_{n})> t$. ...
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Абызов А. Н., Буутай П. Н., Математика и теоретические компьютерные науки 2026 Т. 4 № 2 С. 4–75
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отрицательных экономических последствий некоторых нештатных ситуаций, связанных
со сбоями поставок сырьевого материала.
Ключевые слова: нештатная ситуация, производственный брак, нейронная сеть, прогнозирование, сырьевой материал, моделирование ...
Added: February 15, 2026
Yasnitsky L., Голдобин М. А., В кн.: Искусственный интеллект в решении актуальных социальных и экономических проблем ХХI века : Сборник статей по материалам Десятой всероссийской научно-практической конференции с международным участием (г. Пермь, ПГНИУ, 9–10 октября 2025 г.).: Пермский государственный национальный исследовательский университет, 2025.
В статье предложен алгоритм нейросетевого метода поиска выбросов статистической информации. Алгоритм основан на анализе поведения накопленной ошибки обучения
множества нейросетей персептронного типа с одним скрытым слоем, полученной суммированием для каждого примера обучающего набора данных. Количество нейронов
скрытого слоя каждой нейросети определяется исходя из следствия теоремы Арнольда –
Холмогорова – Хехт-Нильсена, которое регламентирует количество связей и количество
нейронов скрытого слоя, ...
Added: February 15, 2026
Пермский государственный национальный исследовательский университет, 2025.
Представлены материалы Десятой всероссийской научно-практической конференции с международным участием «Искусственный интеллект в решении
актуальных социальных и экономических проблем ХХI века», которая проводилась 9–10 октября 2025 г. в Перми, ПГНИУ.
Сборник предназначен для научных и педагогических работников, преподавателей, аспирантов, магистрантов, студентов и всех, кто интересуется и занимается проблемами развития и применения методов искусственного интеллекта. ...
Added: February 15, 2026
Dobrynskaya V. V., Tomtosov A., Речмедина С., / NRU HSE. Series WP BRP 60/FE/2017 "SERIES: FINANCIAL ECONOMICS". 2025.
We study the application of factor investing in the market for real estate (REITs). The analysis of traditional factor strategies, such as momentum, value, size and profitability, reveals their unstable and atypical behavior in comparison to the equity market, however, there is a strong momentum effect in the factor strategies. We propose a new dynamic ...
Added: January 21, 2026