Neural network and genetic algorithm technology in data mining of manufacturing quality information

Limei Song; Xing-Hua Qu; Shenghua Ye

doi:10.1117/12.460212

12 March 2002 Neural network and genetic algorithm technology in data mining of manufacturing quality information

Limei Song, Xing-Hua Qu, Shenghua Ye

Proceedings Volume 4730, Data Mining and Knowledge Discovery: Theory, Tools, and Technology IV; (2002) https://doi.org/10.1117/12.460212
Event: AeroSense 2002, 2002, Orlando, FL, United States

Abstract

Data Mining of Manufacturing Quality Information (MQI) is the key technology in Quality Lead Control. Of all the data mining methods, Neural Network and Genetic Algorithm is widely used for their strong advantages, such as non-linear, collateral, veracity etc. But if you singly use them, there will be some limitations preventing your research, such as convergence slowly, searching blindness etc. This paper combines their merits and use Genetic BP Algorithm in Data Mining of MQI. It has been successfully used in the key project of Natural Science Foundation of China (NSFC) - Quality Control and Zero-defect Engineering (Project No. 59735120).

Citation Download Citation

Limei Song, Xing-Hua Qu, and Shenghua Ye "Neural network and genetic algorithm technology in data mining of manufacturing quality information", Proc. SPIE 4730, Data Mining and Knowledge Discovery: Theory, Tools, and Technology IV, (12 March 2002); https://doi.org/10.1117/12.460212

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