DocumentCode :
2930450
Title :
The pattern of multi-layer grey situation decision in intensive land use evaluation for towns
Author :
Li Xi-can ; Zhang Guang-bo ; Yuan Zheng ; Tian Ye ; Cheng Shu-han
Author_Institution :
Coll. of Inf. Sci. & Eng., Shandong Agric. Univ., Taian, China
fYear :
2013
fDate :
15-17 Nov. 2013
Firstpage :
248
Lastpage :
252
Abstract :
Based on the uncertainty of intensive land use evaluation, using the grey system theory, the pattern of multilayers grey situation decision in intensive land use evaluation for towns is presented in this paper. At first, according to the first-layer evaluation indexes, we establish the grey decision situation, and compute the weighted grey decision situation of indexes of the first layer´s unit system, construct the second layer evaluation index´s grey decision situation of unit system. Secondly, we compute the weighted grey decision situation of indexes of the second layer´s unit system, and construct grey decision situation of the second layer´s unit system. In the same way, repeating the above processes, the top layer´s weighted grey decision situation of unit system is gained. According to the contained information of the top layer´s grey decision situation, we determine the type and sequence of evaluation samples. The applied example shows that the model presented in this paper is valid.
Keywords :
grey systems; land use planning; first layer unit system index; first-layer evaluation index; grey system theory; intensive land use evaluation; multilayer grey situation decision pattern; second layer evaluation index grey decision situation; second layer unit system; top layer weighted grey decision situation; town; Cities and towns; Decision making; Educational institutions; Finite element analysis; Indexes; Mathematical model; Stability criteria; decision; grey situation; intensive land use; weight;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Grey Systems and Intelligent Services, 2013 IEEE International Conference on
Conference_Location :
Macao
ISSN :
2166-9430
Print_ISBN :
978-1-4673-5247-5
Type :
conf
DOI :
10.1109/GSIS.2013.6714774
Filename :
6714774
Link To Document :
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