DocumentCode :
3226661
Title :
Research on UML-Based Green Alignment Selection Decision Making Model
Author :
Ke Tao ; Xiao-Ping Wu
Author_Institution :
Sch. of Civil Eng. & Archit., Central South Univ., Changsha
Volume :
2
fYear :
2008
fDate :
20-22 Oct. 2008
Firstpage :
681
Lastpage :
685
Abstract :
In accordance with the characteristics of green alignment selection and problems existing in the current intelligent alignment selection design, this paper integrates the advantages of Unified Modeling Language (UML) in the software engineering and, then proposes comprehensive solution based on decision making model of UML green alignment selection. Furthermore, this paper elucidates ideas of each decision making model and each object-oriented view, represents the complex system, via the manifest and simple visual graphs, from different perspective, and finally enables developer and decision maker to acquire clear understanding of it. In addition, this paper completes the requirements analysis, modular decomposition, object model construction and relevance analysis between objects with the application of UML-based green alignment selection decision making model.
Keywords :
Unified Modeling Language; decision making; formal specification; formal verification; object-oriented languages; systems analysis; traffic engineering computing; transportation; UML-based green alignment selection decision making model; Unified Modeling Language; complex system; intelligent alignment selection design; modular decomposition; object model construction; relevance analysis; requirement analysis; software engineering; transportation; Application software; Civil engineering; Computer architecture; Decision making; Object oriented modeling; Power system modeling; Software engineering; Software systems; Unified modeling language; Visualization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computation Technology and Automation (ICICTA), 2008 International Conference on
Conference_Location :
Hunan
Print_ISBN :
978-0-7695-3357-5
Type :
conf
DOI :
10.1109/ICICTA.2008.380
Filename :
4659848
Link To Document :
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