Hybrid Strategy for Product Quality Credit Evaluation Based on Statistics and Artificial Neural Network

Abstract:

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In China, quality credit is an important part of the social credit system, and evaluation of quality credit is the key to the construction of quality credit system. In this paper, on the basis of product quality credit factor analysis and evaluation index construction, a hybrid strategy of three stages is proposed according to the different nature of indicators. The emphasis is put on intelligent evaluation model based on statistics and artificial neural network. According to the results of experimental verification, this credit evaluation method shows a high accuracy for the evaluation of quality credit.

Info:

Periodical:

Advanced Materials Research (Volumes 361-363)

Edited by:

Qunjie Xu, Honghua Ge and Junxi Zhang

Pages:

1499-1505

Citation:

L. M. Liu et al., "Hybrid Strategy for Product Quality Credit Evaluation Based on Statistics and Artificial Neural Network", Advanced Materials Research, Vols. 361-363, pp. 1499-1505, 2012

Online since:

October 2011

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Price:

$41.00

[1] GB/T 23791-2009 General classification of enterprise quality credit (In Chines).

[2] Yongchao Gao, Limei Liu and Huitao Wang: China Standardization (In Chines) (2009), p.4.

[3] Lizhi Wang: China Quality (2010) (In Chines), p.16.

[4] Kuitong Xian and Ruyi Ye: World Standardization and Quality Management (In Chines) (2008), p.45.

[5] Yongchao Gao and Huitao Wang: Standardization Science (In Chines) (2011), in press.

[6] Xinyou Xiong and Yu Liu. Modern Economic Information (In Chines) (2009), p.153.

[7] QB/T 4112-2010 Credit evaluation norms for food industry enterprises (In Chines).

[8] Chunsheng Zhu, Yuanrui Zhan and Shijun Jia: 2010 International Conference on Management and Service Science, p.1.

DOI: https://doi.org/10.1109/icmss.2010.5576862

[9] Xinying Zhang, Chong Wu; A. F. Ferretti: 2009 International Conference on Management and Service Science, p.1.

[10] Hui Ren, Yujing He and Ning Chang: 2009 International Symposium on Computer Network and Multimedia Technology, p.1.

[11] Z. Yanli, G. Xiaojuan and W. Shunping etc: 2010 International Conference on Challenges in Environmental Science and Computer Engineering, p.29.

[12] Y. Ping. 2009 International Conference on Business Intelligence and Financial Engineering, p.138.

[13] Yunna Wu and Zhaomin Si: 2008 International Conference on Risk Management & Engineering Management, p.653.

[14] Honglei Wang: 2010 International Conference on E-Health Networking, Digital Ecosystems and Technologies, p.61.

[15] Ning Liu, Enjun Xia and Yang Li: 2010 International Symposium on Computational Intelligence and Design, p.103.

[16] Yijun Liu, Qiuru Cai and Ye Luo etc: 2009 International Conference on Networking and Digital Society, p.81.

DOI: https://doi.org/10.1109/icnds.2009.26

[17] Yuansheng Huang and Chengfang Tian: 2008 International Conference on Risk Management & Engineering Management, p.482.

[18] Jian Hu: 2009 International Conference on Computer Science & Education, p.103.

[19] ISO 26000: 2008 Guidance on Social Responsibility.