摘要
误差反向传播神经网络具有能够正确逼近非线性映射关系的优点,将其运用到复相结构陶瓷材料抗弯强度预测当中,克服了陶瓷材料研究中单因素实验法不能正确反映抗弯强度与添加组分多因素之间复杂的非线性关系的弱点,通过抗弯强度预测和试验验证,该方法可行有效,为快捷、经济地开发研制新的陶瓷材料提供新的思路和有效手段。
A flexural strength toughness predicting system of advanced ceramic composites based on BP neural network was developed, which can precisely predict the relationship between material composition and the flexural strength through self-training with the present data, and can perfectly aid the ceramic materials design. This system has friendly interfaces, extensive application, good operating feasibility and reliability examined with the present Al_2O_3/SiC/(W,Ti)C ceramics
出处
《陶瓷》
CAS
2005年第4期10-12,共3页
Ceramics
基金
国家自然科学基金 (50 4 0 50 4 7)
山东省优秀中青年科学家科研奖励基金 (2 0 0 0 - 4 9)资助项目
