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Application of Projection Pursuit Classification Model in Comprehensive Evaluation of Common Papermaking Materials |
Received:June 02, 2019 |
DOI:10.11981/j.issn.1000-6842.2020.03.53 |
Key Words:RAGA algorithm;PPC model;classification;comprehensive evaluation |
Fund Project:中国林科院林业新技术所基本科研业务费专项资助(CAF,基金号:CAFYBB2019SY039)。 |
Author Name | Affiliation | Postcode | ZHAO Jingyuan* | Jiangsu Provincial Key Lab of Pulp and Paper Science and Technology, Nanjing Forestry University, Nanjing, Jiangsu Province, 210037 | 210037 | XIONG Zhixin | Jiangsu Provincial Key Lab of Pulp and Paper Science and Technology, Nanjing Forestry University, Nanjing, Jiangsu Province, 210037 | 210037 | LIANG Long | Institution of Chemical Industry of Forestry Products, CAF, Nanjing, Jiangsu Province, 210042 | 210042 | FANG Guigan | Institution of Chemical Industry of Forestry Products, CAF, Nanjing, Jiangsu Province, 210042 | 210042 |
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Abstract: |
In this paper, the projection pursuit classification (PPC) and accelerated genetic algorithm (RAGA) based on real coding were combined and optimized multiple index parameters to convert high-dimensional data indexes into one-dimensional projection. Based on the RAGA-PPC model, the various papermaking raw materials were classified, and evaluated effectively. The conclusion demonstrated that eva-luation result of RAGA-PPC model was consistent with the actual category of the papermaking raw materials. Furtherly this method has more advantages in objectivity, reliability, accuracy and has practical application prospects. |
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