[1]
|
王红瑞,宋宇,刘昌明,等.混沌理论及在水科学中的应用与存在的问题[J].水科学进展,2004,15(3):400-407. |
[2]
|
Sivakumar B.Chaos theory in geophysics:past,present and future[J].Chaos,SolitonsandFractals,2004,19:441-462. |
[3]
|
赵永龙.水文动力系统混沌分析及其非线性预测[D].成都:四川联合大学,1997. |
[4]
|
王文均,叶敏,陈显维.长江径流时间序列混沌特性的定量分析[J].水科学进展,1994,5(2):87-93. |
[5]
|
Taken S F.Detecting strange attractors in turbulence[J].Lecture Notes in Mathematics,1981,898:366-381. |
[6]
|
ASCE Task Committee.Artificial neural networks in hydrology-Ⅰ:Preliminary concepts[J].Journal of Hydrologic Engineering,2000,5(2):115-123. |
[7]
|
ASCE Task Committee.Artificial neural networks in hydrology-Ⅱ:Hydrological applications[J].Journal of Hydrologic Engineering,2000,5(2):124-137. |
[8]
|
Vladimir N Vapnik 著,张学工译.统计学习理论的本质[M].北京:清华大学出版社,2000. |
[9]
|
林剑艺,程春田.支持向量机在中长期径流预报中的应用[J].水利学报,2006,37(6):681-686. |
[10]
|
Liong S Y,Sivapragasm C.Flood stage forecasting with SVM[J].Journal of the American Water Resources Association,2002,38(1):173-186. |
[11]
|
廖杰,王文圣,李跃清,等.支持向量机及其在径流预测中的应用[J].四川大学学报(工程科学版),2006,38(6):24-29. |
[12]
|
李国庆,陈守煜.基于模糊模式识别的支持向量机的回归预测方法[J].水科学进展,2005,16(5):741-746. |
[13]
|
Packabd N H,CrutchfieiD J P,Farmer J D,et al.Geometry from a time series[J].Physics Review Letters,1980,45:712-716. |
[14]
|
GRA SSB ER GER P,PROCACCIA I Measuring the strangeness of strange attractors[J].Physica D,1983,9:189-208. |
[15]
|
Vapnik V.Statistical Learning Theory[M].New York:Springer,1998. |
[16]
|
Smola A J,Schoelkopf B.A tutorial on support vector regression[J].Statistics and Computing,2004,14:199-222. |
[17]
|
Vapnik V.The Nature of Statistical Learning Theory[M].New York:Springer Verlag,1999. |
[18]
|
Hsu C W,Chang C C,Lin C J.A Practical Guide to Support Vector Classification[R].Technical report,Department of Computer Science and Information Engineering,National Taiwan University,2003. |
[19]
|
Dong B,Cao C,Lee S E.Applying support vector machines to predict building energy consumption in tropical region[J].Energy and Buildings,2005,37:545-553. |
[20]
|
Chen P W,Wang J Y,Lee H W.Model selection of SVMs using GA approach[A].2004 IEEE International Joint Conference[C].Budapest:2004.2 035-2 040. |
[21]
|
Yu X Y,Liong S Y,Babovic V.EC-SVM approach for real-time hydrologic forecasting[J].Journal of Hydroinformatics,2004,6(3):209-233. |
[22]
|
Pai P F,Hong W C.Support vector machines with simulated annealing algorithms in electricity load forecasting[J].Energy Conversion and Management,2005,46(17):2669-2688. |
[23]
|
Duan QY,Sorooshian S,Gupta V K.Optimal use of the SCE-UA global optimization method for calibrating watershed models[J].Journal of Hydrology,1994,158(1):265-284. |
[24]
|
Duan QY,Sorooshiaa S,Gupta V K.Optimal use of the SCE-UA global optimization method for calibrating watershed models[J].Journal of Hydrology,1994,158(1):265-284. |
[25]
|
Sorooshiaa S,Duan Q,Gupta V K.Calibration of rainfall-runoff models:application of global optimization to the Sacramento soil moisture accounting mode[J].Water Resources Research,1993,29(4):1 185-1 194. |
[26]
|
Kuczera G.Efficient subspace probabilistic parameter optimization for catchment models[J].Water Resources Research,1997,33(1):177-185. |
[27]
|
卢宇,陈宇红,贺国光.应用改进型小数据量法计算交通流量的最大Lypunov指数[J].系统工程理论与实践,2007(1):85-90. |