钟承奎,牛明飞.关于无穷维耗散非线性动力系统全局吸引子的存在性[J].兰州大学学报:自然科学版,2003,39(2):1-5. ZHONG Cheng-kui, NIU Ming-fei. On the existence of global attractor for a class of infinite dimensional dissipative non-linear dynamic systems[J]. Journal of Lanzhou University: Natural Sciences, 2003, 39(2): 1-5.(in Chinese)
[2]
李 凡,段建立,吴 敏.采用混沌变异演化算法在边坡稳定分析中的应用[J].合肥工业大学学报:自然科学版,2002,25(1):109-112. LI Fan, DUAN Jian-li, WU Min. Application of an evolution program with chaos mutation to the analysis of slope stability[J]. Journal of Hefei University of Technology: Natural Science, 2002, 25(1): 109-112.(in Chinese)
[3]
毕龙珠,王腾军,杨海彦,等.混沌时间序列在建筑物沉降预测中的应用研究[J].测绘信息与工程,2009,34(2):49-51. BI Long-zhu, WANG Teng-jun, YANG Hai-yan, et al. Application of chaos time series to subsidence forecasting[J]. Journal of Geomatics, 2009, 34(2): 49-51.(in Chinese)
[4]
夏银飞,张季如,夏元友.混沌时间序列在路基工后沉降中的应用[J].华中科技大学学报:城市科学版,2005,22(3):89-93. XIA Yin-fei, ZHANG Ji-ru, XIA Yuan-you. Application of chaotic time series on road foundation’s sedimentation[J]. Journal of Huazhong University of Science and Technology:Urban Science Edition, 2005, 22(3): 89-93.(in Chinese)
[5]
李 峰,宋建军,董来启,等.基于混沌神经网络理论的城市地面沉降量预测模型[J].工程地质学报,2008,16(5):715-720. LI Feng, SONG Jian-jun, DONG Lai-qi, et al. Chaos neural network theory based model for quantitative prediction of urban ground subsidence[J]. Journal of Engineering Geology, 2008, 16(5): 715-720.(in Chinese)
[6]
ROSE B T. Tennessee rockfall management system[D]. Blacksburg: Virginia Polytechnic Institute and State University, 2005.
[7]
GHOLIPOUR A, ARAABI B, LUCAS C. Predicting chaotic time series using neural and neurofuzzy models: a comparative study[J]. Neural Process Letters, 2006, 24(3): 217-239.
[8]
陈 健.基坑变形的混沌时间序列分析方法及应用研究[J].测绘,2011,34(2):57-59. CHEN Jian. Analytic method and application about chaotic foundation pit deformation time-series[J]. Surveying and Mapping, 2011, 34(2): 57-59.(in Chinese)
[9]
陈 铿,韩伯棠.混沌时间序列分析中的相空间重构技术综述[J].计算机科学,2005,32(4):67-70. CHEN Keng, HAN Bo-tang. A survey of state space reconstruction of chaotic time series analysis[J]. Computer Science, 2005, 32(4): 67-70.(in Chinese)
[10]
汤 琳,杨永国.混沌时间序列分析及应用研究[J].武汉理工大学学报,2010,32(19):189-192. TANG Lin, YANG Yong-guo. Chaotic time series analysis and its application research[J]. Journal of Wuhan University of Technology, 2010, 32(19): 189-192.(in Chinese)
[11]
孙海云,曹庆杰.混沌时间序列建模及预测[J].系统工程理论与实践,2001,21(5):106-113. SUN Hai-yun, CAO Qing-jie. The modeling and forecasting of chaotic time series[J]. Systems Engineering―Theory and Practice, 2001, 21(5): 106-113.(in Chinese)
[12]
李红霞,许士国,徐向舟,等.混沌理论在水文领域中的研究现状及展望[J].水文,2007,27(6):1-5,58. LI Hong-xia, XU Shi-guo, XU Xiang-zhou, et al. Current status and prospect of chaos theory research in hydrology[J]. Journal of China Hydrology, 2007, 27(6): 1-5, 58.(in Chinese)
[13]
马红光,李夕海,王国华,等.相空间重构中嵌入维和时间延迟的选择 [J].西安交通大学学报,2004,38(4):335-338. MA Hong-guang, LI Xi-hai, WANG Guo-hua, et al. Selection of embedding dimension and delay time in phase space reconstruction[J]. Journal of Xi’an Jiaotong University, 2004, 38(4): 335-338.(in Chinese)
[14]
高雷阜.煤与瓦斯突出的混沌动力系统演化规律研究[D].阜新:辽宁工程技术大学,2006. GAO Lei-fu. Study on chaotic dynamical system evolution of coal and gas outburst[D]. Fuxin: Liaoning Technical University, 2006.(in Chinese)
[15]
AYATT N E, CHERIET M, SUEN C Y. Automatic model selection for the optimization of SVM kernels[J]. Pattern Recognition, 2005, 38(10): 1733-1745.
[16]
LEE P H, CHEN Yi, PEI S C, et al. Evidence of the correlation between positive lyapunov exponents and good chaotic random number sequences[J]. Computer Physics Communications, 2004, 160(3): 187-203.
[17]
KIM H S, EYKHOH R, SALAS J D. Nonlinear dynamics, delay times, and embedding windows[J]. Physicra D: Nonlinear Phenomena, 1999, 127(1/2): 48-60.
[18]
KOJIMA C, RAPISARDA P, TAKABA K. Lyapunov sta- bility analysis of higher-order 2-D systems[C]∥IEEE. Preceedings of the 48th IEEE Conference on Decision and Control. Shanghai: IEEE, 2010: 1734-1739.
[19]
陈益峰,吕金虎,周创兵.基于Lyapunov指数改进算法的边坡位移预测[J].岩石力学与工程学报,2001,20(5):671-675. CHEN Yi-feng, LU Jin-hu, ZHOU Chuang-bing. Prediction of slope displacement by using Lyapunov exponent improved technique[J]. Chinese Journal of Rock Mechanics and Engineering, 2001, 20(5): 671-675.(in Chinese)
[20]
郁俊莉,王其文.Lyapunov指数混沌特性判定研究[J].武汉理工大学学报,2004,26(2):90-92. YU Jun-li, WANG Qi-wen. Research of judging the chaotic characteristics with the Lyapunov exponents[J]. Journal of Wuhan University of Technology, 2004, 26(2): 90-92.(in Chinese)
[21]
张安兵,高井祥,刘新侠,等.边坡变形时序非线性判定及混沌预测研究[J].中国安全科学学报,2008,18(4):55-60. ZHANG An-bing, GAO Jing-xiang, LIU Xin-xia, et al. Nonlinear test and chaotic prediction of slope deformation sequences[J]. China Safety Science Journal, 2008, 18(4): 55-60.(in Chinese)
[22]
张 勇,关 伟.基于最大Lyapunov指数的多变量混沌时间序列预测[J].物理学报,2009,58(2):756-763. ZHANG Yong, GUAN Wei. Predication of multivariable chaotic time series based on maximal Lyapunov exponen[J]. Acta Physica Sinica, 2009, 58(2): 756-763.(in Chinese)
[23]
张 勇,关 伟.基于最大李亚普诺夫指数的改进混沌时间序列预测[J].信息与控制,2009,38(3):360-364. ZHANG Yong, GUAN Wei. An improved method for forecasting chaotic time series based on maximum Lyapunov exponent[J].Information and Control, 2009, 38(3): 360-364.(in Chinese)
[24]
向昌盛,张林峰.混沌时间序列预测模型参数同步优化[J].计算机工程与应用,2011,47(1):4-7. XIANG Chang-sheng, ZHANG Lin-feng. Simultaneous optimization of chaotic time series prediction model parameters[J]. Computer Engineering and Applications, 2011, 47(1): 4-7.(in Chinese)
[25]
韩 敏,魏 茹.基于改进典型相关分析的混沌时间序列预测[J].大连理工大学学报,2008,48(2):292-297. HAN Min, WEI Ru. Chaotic time series prediction based on modified canonical correlation analysis[J]. Journal of Dalian University of Technology, 2008, 48(2): 292-297.(in Chinese)