Title :
Application of the concept lattice based on principal components in the evaluation of regional logistics development
Author :
Jianhong Guo ; Lianwen Qian
Author_Institution :
Sch. of Econ., Xiamen Univ., Xiamen, China
Abstract :
Regional logistics development evaluation is a hot research field nowadays. In order to solve the problem of high complexity and multiply correlated indexes during the regional logistics evaluation, evaluate the developmental level of regional logistics scientifically and thus provide with scientific decision for relevant governmental departments, this paper proposes a method, i.e. the principal component combined with concept lattice, to evaluate the developmental level of the regional logistics. Referring to the statistical data, this paper comprehensively evaluates the developmental situations of China Mainland´s provincial logistics. According to the analysis and research results, the principal component analysis (PCA) based on the data can be used to undertake the dimension reduction process on multiple indicators; in addition, it to some degree weakens the multiple correlations between the indicators. Based on the score of the principal component, the concept lattice can be applied to lower the complexity of the evaluation, enhance the interpretability of the evaluation and make the evaluation result more consistent with the reality.
Keywords :
government; logistics; principal component analysis; China Mainland provincial logistics; PCA; concept lattice; correlated indexes; dimension reduction process; governmental departments; principal component analysis; regional logistics development evaluation; scientific decision; statistical data; Economics; Educational institutions; Indexes; Lattices; Logistics; Principal component analysis; Rail transportation; concept lattice; evaluation; principal component analysis (PCA); regional logistics;
Conference_Titel :
Natural Computation (ICNC), 2013 Ninth International Conference on
Conference_Location :
Shenyang
DOI :
10.1109/ICNC.2013.6817946