Constructing a Method for an Evaluation Index System Based on Graph Distance Classification and Principal Component Analysis
Based on the importance of having an evaluation index system, a new method that combines PCA with graph distance classification is presented to make up the deficiencies of principal component analysis in the process of index screening, and this method is applied in the construction of an evaluation...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2019-01-01
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| Series: | Advances in Materials Science and Engineering |
| Online Access: | http://dx.doi.org/10.1155/2019/6015754 |
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| _version_ | 1832552569187074048 |
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| author | Keyou Shi Yong Liu Zhijun Zhang Qing Yu Qiucai Zhang |
| author_facet | Keyou Shi Yong Liu Zhijun Zhang Qing Yu Qiucai Zhang |
| author_sort | Keyou Shi |
| collection | DOAJ |
| description | Based on the importance of having an evaluation index system, a new method that combines PCA with graph distance classification is presented to make up the deficiencies of principal component analysis in the process of index screening, and this method is applied in the construction of an evaluation index system for the environmental quality of decommissioning uranium tailing. The seepage indexes were classified into six classes using graph distance classification, which selects the representative elements, including pH, ∑α, 210Pb, 210Po, F−, and NO3−. All of the representative elements were analyzed by PCA while determining the seepage indexes, including pH, U, Ra, ∑α, NH4-N, and F−, and establishing an index system for environmental quality evaluation that consists of two primary indexes (seepage and radiation environment) and 12 secondary indexes. The results showed that the model had ensured that the sifted indexes had a significant effect on the evaluation result and avoided the deletion of some important indexes and that it had stronger applicability and maneuverability. |
| format | Article |
| id | doaj-art-643077a2bd7c4ec8a1712a4de564f3b6 |
| institution | Kabale University |
| issn | 1687-8434 1687-8442 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Materials Science and Engineering |
| spelling | doaj-art-643077a2bd7c4ec8a1712a4de564f3b62025-02-03T05:58:24ZengWileyAdvances in Materials Science and Engineering1687-84341687-84422019-01-01201910.1155/2019/60157546015754Constructing a Method for an Evaluation Index System Based on Graph Distance Classification and Principal Component AnalysisKeyou Shi0Yong Liu1Zhijun Zhang2Qing Yu3Qiucai Zhang4School of Resource Environmental and Safety Engineering, University of South China, Hengyang 421001, ChinaSchool of Resource Environmental and Safety Engineering, University of South China, Hengyang 421001, ChinaSchool of Resource Environmental and Safety Engineering, University of South China, Hengyang 421001, ChinaSchool of Resource Environmental and Safety Engineering, University of South China, Hengyang 421001, ChinaSchool of Resource Environmental and Safety Engineering, University of South China, Hengyang 421001, ChinaBased on the importance of having an evaluation index system, a new method that combines PCA with graph distance classification is presented to make up the deficiencies of principal component analysis in the process of index screening, and this method is applied in the construction of an evaluation index system for the environmental quality of decommissioning uranium tailing. The seepage indexes were classified into six classes using graph distance classification, which selects the representative elements, including pH, ∑α, 210Pb, 210Po, F−, and NO3−. All of the representative elements were analyzed by PCA while determining the seepage indexes, including pH, U, Ra, ∑α, NH4-N, and F−, and establishing an index system for environmental quality evaluation that consists of two primary indexes (seepage and radiation environment) and 12 secondary indexes. The results showed that the model had ensured that the sifted indexes had a significant effect on the evaluation result and avoided the deletion of some important indexes and that it had stronger applicability and maneuverability.http://dx.doi.org/10.1155/2019/6015754 |
| spellingShingle | Keyou Shi Yong Liu Zhijun Zhang Qing Yu Qiucai Zhang Constructing a Method for an Evaluation Index System Based on Graph Distance Classification and Principal Component Analysis Advances in Materials Science and Engineering |
| title | Constructing a Method for an Evaluation Index System Based on Graph Distance Classification and Principal Component Analysis |
| title_full | Constructing a Method for an Evaluation Index System Based on Graph Distance Classification and Principal Component Analysis |
| title_fullStr | Constructing a Method for an Evaluation Index System Based on Graph Distance Classification and Principal Component Analysis |
| title_full_unstemmed | Constructing a Method for an Evaluation Index System Based on Graph Distance Classification and Principal Component Analysis |
| title_short | Constructing a Method for an Evaluation Index System Based on Graph Distance Classification and Principal Component Analysis |
| title_sort | constructing a method for an evaluation index system based on graph distance classification and principal component analysis |
| url | http://dx.doi.org/10.1155/2019/6015754 |
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