Classification of European Residential Tall Buildings - Application Assumptions

被引:0
作者
Zamojski, Tomasz [1 ]
机构
[1] Wroclaw Univ Sci & Technol, 27 Wybrzeze Stanislawa Wyspianskiego, PL-50370 Wroclaw, Poland
来源
SYSTEM DEPENDABILITY-THEORY AND APPLICATIONS, DEPCOS-RELCOMEX 2024 | 2024年 / 1026卷
关键词
European residential high-rise buildings; Classification; Machine Learning; Artificial Intelligence; Vertical Habitat; Architecture; Real Estate;
D O I
10.1007/978-3-031-61857-4_34
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Residential high-rise buildings are the domain of large cities, urban agglomerations and metropolitan areas. The dynamic urbanization of the residential environment is resulting in increasingly dense population and development, which, unfortunately, is associated with limited access to housing resources for the average citizen. In this article, special interest is focused on the evaluation and categorization of the composition, functions and structures of residential high-rise buildings and their close surroundings (neighborhoods). The proposed application, based on the collected data about the customer, his needs and preferences arising from his personal life, professional work, educational needs, financial situation, etc., will give a preliminary answer as to whether the "indicated" apartment in a tall building meets his requirements and possibilities. This article is an attempt develop an application to classify European residential tall buildings and their living environment with a use of machine learning techniques and models. The presented assumptions of the application are a preliminary approach to the problem of supporting the process of finding housing (for rent or purchase) that meets the requirements of habitat.
引用
收藏
页码:349 / 359
页数:11
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