Performance Prediction of Carbon Fiber Protofilament Based on SAGA-SVR

贺聪; 任立红; 丁永生

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Performance Prediction of Carbon Fiber Protofilament Based on SAGA-SVR

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摘要

The existing optimized performance prediction of carbon fiber protofilament process model is still unable to meet the production needs. A way of performance prediction on carbon fiber protofilament was presented based on support vector regression( SVR) which was optimized by an optimization algorithm combining simulated annealing algorithm and genetic algorithm( SAGA-SVR). To verify the accuracy of the model,the carbon fiber protofilament production test data were analyzed and compared with BP neural network( BPNN). The results show that SAGA-SVR can predict the performance parameters of the carbon fiber protofilament accurately.

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《东华大学学报：英文版》 |2014年第2期|92-97|共6页
作者
贺聪; 任立红; 丁永生;
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作者单位

College of Information Science and Technology;

Donghua University;

Engineering Research Center of Digitized Textile & Fashion Technology;

Ministry of Education;

Donghua University;

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原文格式 PDF
正文语种 chi
中图分类自动化技术在各方面的应用;
关键词
support vector regression(SVR) machine; genetic algorithm(GA); simulated annealing algorithm(SA); carbon fiber; performance prediction;

Performance Prediction of Carbon Fiber Protofilament Based on SAGA-SVR

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