FKM-Based Clustering Case Retrieval of the High-Rise Building Structural Intelligent Scheme Design

Firstly, the disadvantage of the traditional "hard clustering" was analyzed; and the basic principles and algorithm steps of the fuzzy clustering was presented, it can express and process the class of objects which is not clearly in nature. Secondly, the theory and cluster analysis method...

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Bibliographic Details
Published in:Applied Mechanics and Materials Vol. 174-177; pp. 1748 - 1752
Main Authors: Liu, Shu Jun, Ou, Jin Ping, Zhang, Shi Zhong, Zhang, Shi Hai
Format: Journal Article
Language:English
Published: Zurich Trans Tech Publications Ltd 01.05.2012
Subjects:
High-Rise Building
Case Retrieval
Design of the Structural Intelligent Scheme
Fuzzy K-Means Algorithm
Clustering Analysis
ISBN:9783037854235, 3037854235
ISSN:1660-9336, 1662-7482, 1662-7482
Online Access:Get full text
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Summary:Firstly, the disadvantage of the traditional "hard clustering" was analyzed; and the basic principles and algorithm steps of the fuzzy clustering was presented, it can express and process the class of objects which is not clearly in nature. Secondly, the theory and cluster analysis method is introduced to design high-rise structure; based on the fuzzy K-Means clustering analysis, the case retrieval method of the high-level structural intelligent design was established. Lastly, the example of engineering application was given in where the 26 projects data was used as the basis for the cluster and instance retrieval; the former 20 data is used to cluster and the last 4 data used to instance retrieval, the clustering member is k=4. Practice shows that the fuzzy k-means cluster analysis method is effective for the intelligent design of high-rise structure to obtain an instance, and opens up new ways and means for the high-rise building intelligent design.
Bibliography:Selected, peer reviewed papers from the 2nd International Conference on Civil Engineering, Architecture and Building Materials (CEABM 2012), May 25-27, 2012, Yantai, China
ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISBN:9783037854235
3037854235
ISSN:1660-9336
1662-7482
1662-7482
DOI:10.4028/www.scientific.net/AMM.174-177.1748