Stress-Strain Identification for Cottonseed and Castor Bean Based on Artificial Neural Networks

摘要：

Stress-strain relationship is the most important properties of physical mechanics of oilseeds during mechanical pressing. In view of the difficulty for establishing a mathematical model due to the complexity of physical mechanics performance, the stress-strain identification model for oilseeds based on BP neural network was developed to simulate the relationship. The identification results that the maximum error was less than 0.00005 and the maximum training times was less than 100 indicated that the method of stress-strnin identification for cottonseed and castor bean by using artificial neural networks is both feasible and effective.

关键词： Stress-strain relationship Identification Artificial neural networks cottonseed castor bean

作者: ZHENG Xiao HE Dongping LIN Guoxiang WANG Jingzhou

作者单位: Department of Mechanical Engineering Wuhan Polytechnic University Wuhan, Hubei Province 430023, China

会议类型: 国际会议

会议名称: 第二届国际计算机新科技与教育学术会议(Proceedings of the Second International Conference on Computer Science & Education ICCSE2007)

会议地点: 武汉

会议语种:英文

页码: 3-6

在线出版日期: 2007-07-25（万方平台首次上网日期，不代表论文的发表时间）