جستجو در تالارهای گفتگو

Evidence of Low-Dimensional Determinism in Monthly Water Level Time Series in Lake Van, Turkey Original Article, B39 Daneshfaraz R, Asadi H, Saghebian SM. Journal. Civil Eng. Urban. 2(6): 220-225. 2012. ABSTRACT:Adequate knowledge of lake water level variations is important for proper planning and management of water resources and design of environment. In this study chaotic behavior of monthly water level variations in the lake Van during January 1944 - April 2002 is investigated. The lake Van is the largest lake in Turkey. The methods and indicators of chaos theory (power spectrum, average mutual information, false nearest neighbours, correlation dimension and largest Lyapunov exponents) were applied. The value of power spectrum (4.1) indicate that chaotic (fractal) behavior to the lake water level time series. The optimal delay time (5 month) and embedding dimension (5) are obtained from average mutual information and false nearest neighbours techniques, respectively. Optimal values are then used for the estimation of the correlation dimension and the largest Lyapunov exponent for inspecting possible signatures of chaotic dynamics. The low correlation dimension (3.2) suggest the presence of low-dimensional chaos; also imply that the water level dynamics are dominantly governed by four variables. The positive largest Lyapunov exponent value (0.0085) indicated a signature of chaos. These results give a positive indication towards considering lake water level as a chaotic system. Keywords:Chaos theory, Correlation dimension, Lyapunov exponent, Power spectrum, Time series, Van Lake. منبع: [Hidden Content] دانلود: [Hidden Content],%20B%2039%20220-225.pdf JCEU, B 39 220-225.pdf

Local Prediction in River Discharge Time Series Original Article, B9 Ghorbani MA, Daneshfaraz R, Arvanagi H, Pourzangbar A, Saghebian SM, Kaveh Kar SH. Journal. Civil Eng. Urban. 2(2): 51-55. 2012. ABSTRACT: In this paper, chaotic behavior of the daily river discharge time series from the Karoon River, during January 1999-December 2004 is investigated. The phase space, which describes the evolution of the behavior of a nonlinear system, is reconstructed using the delay embedding theorem suggested by TAKENS. The delay time used for the reconstruction is chosen after examining the first minimum of the average mutual information (AMI) of the data. It is found that a delay time of 40 days and the sufficient embedding dimension is estimated using the false nearest neighbor algorithm which has a value of 8 for the river flow time series. Based on these embedding parameters we calculate the average divergence rate of nearby orbits given by the largest Lyapunov exponent. The largest Lyapunov exponent 0.0255 for is estimated. In this study the local prediction model has been applied to predict daily discharge time series. In this prediction model, the dynamics of the system are described step by step locally in the phase space, the results are quite satisfactory. Keywords: Chaos theory; Karoon River; Local Prediction; Lyapunov exponent; Time series منبع: [Hidden Content] دانلود: [Hidden Content].,B9-51-55.pdf J. Civil Eng. Urban.,B9-51-55.pdf