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     Research Journal of Applied Sciences, Engineering and Technology


Analysis Method and its Application of Weighted Grey Relevance Based on Super Efficient DEA

Zheng Xie and Lianguang Mo
Hunan City University Yiyang, Hunan, 413000, China
Research Journal of Applied Sciences, Engineering and Technology  2013  2:470-474
http://dx.doi.org/10.19026/rjaset.5.4975  |  © The Author(s) 2013
Received: May 08, 2012  |  Accepted: May 29, 2012  |  Published: January 11, 2013

Abstract

For the objectivity issue of grey relevance analysis method determining weight, a new weighted grey relevance analysis method based on super efficient DEA has been proposed. The new method combines the advantage of super efficient DEA analysis and grey relevance analysis and takes grey relevance analysis as the central model and super efficient model as the sub-model, which determines the weight vector of all the relevance coefficient from every observation point of each sub factor, then calculates the comparatively best relation grade and obtains objective superior sequence of all factors. Super DEA can improve the resolving power of the model to grey relation grade, breakthrough the limit of weight sum being one and make the average weight more flexible. The validity of the combined algorithm has been proved by the case study of the influencing factors of vacant commercial housing.

Keywords:

Grey relevance method, relation grade, super efficient DEA, weight,


References


Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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