DocumentCode
478308
Title
Evaluation of Index for Green Zoology Building and Its Definite Algorithm in Path Analysis
Author
Ding, Qian ; Tong, Qiaoling ; Tong, Hengqing
Author_Institution
Sch. of Urban Design, Wuhan Univ., Wuhan
Volume
4
fYear
2008
fDate
18-20 Oct. 2008
Firstpage
506
Lastpage
510
Abstract
With the need of scientific and rational evaluation mechanisms, green zoology building is the development trend of building construction. Based on the basic concept of the green zoology buildings with China´s national conditions, this paper discusses the index system of green zoology building and its calculation. The feature of the calculation is that the second level index is a virtual no observational data, and the summary coefficient is calculated in accordance with samples instead of the prior designated. In the view of the neural network structure, it is an unsupervised learning neural network. Making use of the method of path analysis and the combination of vector length constraint and the prescription constraint, a deterministic algorithm is established. Our algorithm can not only scientifically determine the summary coefficient but also calculate the relations between the indexes, so as to provide a comprehensive and profound analysis method of green building evaluation index system.
Keywords
deterministic algorithms; environmental factors; neural nets; structural engineering computing; unsupervised learning; zoology; building construction; deterministic algorithm; evaluation index system; green zoology building; neural network; path analysis; prescription constraint; unsupervised learning; vector length constraint; Algorithm design and analysis; Environmental economics; Green buildings; Pollution; Power generation economics; Protection; Water conservation; Water storage; Windows; Zoology;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation, 2008. ICNC '08. Fourth International Conference on
Conference_Location
Jinan
Print_ISBN
978-0-7695-3304-9
Type
conf
DOI
10.1109/ICNC.2008.542
Filename
4667335
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