The platform will undergo maintenance on Sep 14 at about 7:45 AM EST and will be unavailable for approximately 2 hours.
2017
DOI: 10.1088/1757-899x/245/5/052025
|View full text |Cite
|
Sign up to set email alerts
|

Models for Experimental High Density Housing

Abstract: Abstract. The article presents the effects of research on models of high density housing. The authors present urban projects for experimental high density housing estates. The design was based on research performed on 38 examples of similar housing in Poland that have been built after 2003. Some of the case studies show extreme density and that inspired the researchers to test individual virtual solutions that would answer the question: How far can we push the limits? The experimental housing projects show str… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

0
7
0

Year Published

2020
2020
2024
2024

Publication Types

Select...
5

Relationship

0
5

Authors

Journals

citations
Cited by 5 publications
(7 citation statements)
references
References 1 publication
(1 reference statement)
0
7
0
Order By: Relevance
“…Yet, few studies discussed occupant perception of density. Bradecki et al (2017); Dave (2011) concluded that the feeling of high density is related to typology rather than being an issue of how many people are living within one square km or unit space. This aligns with what this study found; that perception of density is related to buildings form, typology, location of windows and setbacks.…”
Section: Discussionmentioning
confidence: 99%
“…Yet, few studies discussed occupant perception of density. Bradecki et al (2017); Dave (2011) concluded that the feeling of high density is related to typology rather than being an issue of how many people are living within one square km or unit space. This aligns with what this study found; that perception of density is related to buildings form, typology, location of windows and setbacks.…”
Section: Discussionmentioning
confidence: 99%
“…BP neural networks [26], support vector machines [20], Gaussian process regression [43], random forests [44], radial basis function neural networks [45] and other methods in the application of concrete strength prediction [46], beam shear strength prediction [47], column bearing capacity prediction [48], bridge damage detection [49], and frame structure damage prediction [50] all show that machine learning can not only predict the damage of the structure in the macro-aspect but also predict the bearing capacity of structural components. Among many machine learning algorithms, the Gaussian process regression method has advantages in dealing with regression problems such as small sample size, multiple influencing factors, and nonlinearity [51][52][53]. Compared with other machine learning algorithms, such as artificial neural networks and support vector machines, Gaussian process regression is easy to implement, with fewer parameters and strong model interpretability [54][55][56][57][58].…”
Section: Background: Gprmentioning
confidence: 99%
“…Changes in the Polish political and economic system since 1989 have resulted in unfavourable processes in the structure of residential areas. Housing complexes which developed very quickly in open green areas, often gated, have strengthened the urban sprawl phenomenon, created spatial chaos and worsened the quality of the environment [16][17][18][19].…”
Section: Introductionmentioning
confidence: 99%