GB 50009-2001建筑结构荷载规范[S].北京:中国标准出版社. GB 50009-2001 Codes of Loads on Building Structures[S]. Beijing: Standard Press of China.(in Chinese)
[2]
顾 明,周?毅.神经网络方法在大跨度屋面风压研究中的应用[J].工程力学, 2003, 20(4): 99-103. GU Ming, ZHOU Xuanyi. Application of neural networks in the prediction of wind load on long-span roofs[J]. Engineering Mechanics, 2003, 20(4): 99-103.(in Chinese)
[3]
傅继阳,谢壮宁,倪振华.大跨度屋盖结构风压分布特性的模糊神经网络预测[J].建筑结构学报,2002, 23(1): 62-67. FU Jiyang, XIE Zhuangning, NI Zhenhua. Prediction of wind load on large span roof using fuzzy neural networks[J]. Journal of Building Structures,2002, 23(1): 62-67.(in Chinese)
[4]
傅继阳,甘 泉.大跨平屋盖结构风压分布特性的神经网络模型[J].华南理工大学学报, 2003, 31(8): 62-66. FU Jiyang, GAN Quan. Nerual network model for wind pressure distribution characteristics of large-span flat roofs[J]. Journal of South China University of Technology, 2003, 31(8): 62-66.(in Chinese)
[5]
丁幼亮,李爱群,杜东升,等.基于神经网络的大跨度空间结构脉动风荷载的随机模拟[J].特种结构, 2006, 23(2): 1-3. DING Youliang, LI Aiqun, DU Dongsheng, et al. Random simulation of fluctuating wind load of large-span roofs based on neural networks[J]. Special Structures, 2006, 23(2): 1-3.(in Chinese)
[6]
Williams RJ, Peng J. An efficient gradient-based algorithm for on-line training of recurrent network trajectories[J]. Neural Computer, 1990,2(4):490-501.
[7]
Parlos AG, Chong KT, Atiya AF. Application of the recurrent multilayer perceptron in modeling complex process dynamics[J]. IEEE Trans. Neural Networks, 1994,5(2): 255-266.
[8]
Puskorius GV, Feldkamp LA. Neurocontrol of nonlinear dynamical systems with Kalman filter trained recurrent networks[J].IEEE Trans. Neural Networks,1994,5(2):279-297.
[9]
Zhang Yi. Foundations of implementing the competitive layer model by Lotka-Volterra recurrent neural networks[J]. IEEE Transactions on Neural Networks, 2010,21(3): 494-507.
[10]
Zhou Wei, Zurada J M. Competitive layer model of discrete time recurrent neural networks with LT neurons[J]. Neural Computation, 2010,22:2137-2160.
[11]
Feng DZ, Zheng WX, Jia Y, Neural network learning algorithm for tracking minor subspace in high-dimensional data stream[J]. IEEE Transactions on Neural Networks,2005,16(3):513-521.
[12]
Kirk David B, Hwu, Wen mei W. Applications of GPU computing series, Programming massively parallel processors: a hands-on approach[M]. Morgan Kaufmann, 2010.
[13]
Campolucci P, Uncini A, Piazza F, et al. On-line learning algorithms for locally recurrent neural networks[J]. IEEE Trans. Neural Networks, 1999(10):253-271.
[14]
Puskorius GV, Feldkamp LA.Recurrent network training with the decoupled Extended Kalman Filter Algorithm[C]// in Proceedings of the 1992 SPIE Conference on the Science of Artificial Neural Networks, Orlando 1992(1710):461-473.
[15]
Puskorius GV, Feldkamp LA. Model reference adaptive control with recurrent networks trained by the dynamic DEKF algorithm[C]// in International Joint Conference on Neural Networks, Baltimore II, 1992, 106-113.
[16]
Puskorius GV, Feldkamp LA, Neurocontrol of nonlinear dynamical systems with Kalman filter trained recurrent networks[J]. IEEE Trans. Neural Networks,1994,5(2):279-297.
[17]
Abdelbaki Djouambi, Alina Voda, Abdelfatah Charef, Recursive prediction error identification of fractional order models[J].Communications in Nonlinear Science and Numerical Simulation, 2012,17(6): 2517-2524.
[18]
Frasconi P, Gori M, Soda G. Local feedback multilayered networks[J]. Neural Computation, 1992, 4(1): 120-130.
[19]
王吉民. 薄膜结构的风振响应分析和风洞试验研究[D]. 杭州:浙江大学, 2001. WANG Jimin. Wind-induced response analysis and study on wind tunnel exprement of membrane structures[D].Hangzhou:zhejiang University,2001.(in Chinese)