[1] 金同熹. 机器零件的表面质量和接触[M]. 北京: 机械工业出版社, 1986:136-139. JIN Tong-xi. the surface quality and contrast of machine part[M]. Beijing: China Machine Press, 1986, 10:136-139. (in Chinese) [2] 郭前建,杨建国,王秀山. 精密磨削加工的神经网络误差补偿技术[J].中国机械工程, 2006,17(8):55-58. GUO Qian-jian, YANG Jian-guo, WANG Xiu-shan. Error compensation technology based on neural networks of precision grinding process[J]. China Mechanical Engineer, 2006,17(8):55-58. (in Chinese) [3] 张建立,李钢,俞研. 神经模糊技术在柔性加工工序质量保证系统中的应用研究[J].兵工学报, 2001,22(4):566- 569. ZHANG Jian-li, LI Gang, YU Yan. Application of neutral fuzzy technology in the system of guarantee for working procedure quality in flexible processing[J]. Acta Armamentarii, 2001,22(4): 566-569. (in Chinese) [4] ZHAO Xiao-guang, CHEN Bing-zhen, HE Xiao-rong. A novel neural network for the prediction of process variables[J]. Science in China: Series A,1995,38(3):355-367. [5] Psichogios D C, Ungar L H. A hybrid neural network first principles approach to process modeling[J]. AIChE Journal, 1992,38(10):1499-1511. [6] 张兵,袁寿其,成立,等.基于L-M优化算法的BP神经网络的作物需水量的预测模型的研究[J].农业工程学报,2004, 20(6):73-76. ZHANG Bing, YUAN Shou-qi, CHENG Li, et al. Model for predicting crop water requirements by using L-M optimization algorithm BP neural network[J]. Transactions of the Chinese Society of Agricultural Engineering, 2004, 20(6):73-76.(in Chinese) [7] Hornic K, Stinchcombe M,White H. Multiplayer feed-forward networks are universal approximators[J]. Neural Networks,1989,2:25-36. [8] 飞思科技产品研发中心.神经网络理论与MATLAB7实现[M].北京:电子工业出版社,2005:99-108. FECIT Technological Product Research Center. Neural networks and its implement MATLAB7[M]. Beijing: Publishing House of Electronics Industry, 2005:99-108. (in Chinese) |