Noise level estimation of chaotic hydrological time series
نویسنده
چکیده
A new method of estimating the noise level present in a chaotic hydrological time series is presented. The effectiveness of the method is first demonstrated using two artificial chaotic time series, i.e. the Henon map and the Lorenz equation, whose dynamic characteristics are known a priori, and then tested on two real hydrological time series: daily sfreamflow series observed in the Chao Phraya River basin in Thailand (raw data), and the same data "cleaned" by the method of Schreiber (1993a). Different levels of noise are added to the artificial chaotic time series in order to demonstrate the effectiveness of the method. A comparison of the results obtained using the proposed method and the method by Schreiber (1993a) clearly indicate a much better performance of the proposed method.
منابع مشابه
Model Based Method for Determining the Minimum Embedding Dimension from Solar Activity Chaotic Time Series
Predicting future behavior of chaotic time series system is a challenging area in the literature of nonlinear systems. The prediction's accuracy of chaotic time series is extremely dependent on the model and the learning algorithm. On the other hand the cyclic solar activity as one of the natural chaotic systems has significant effects on earth, climate, satellites and space missions. Several m...
متن کاملEvaluation of SARIMA time series models in monthly streamflow estimation in Idanak hydrometry station
prediction of hydrological variables is a highly effective tool in water resource management. One of the important tools for modeling hydrological processes is the use of time series modeling and analysis. River series production series can be used by time series models in various studies such as drought, flood, reservoir systems design and many other purposes For this purpose, monthly flow dat...
متن کاملDetection and predictive modeling of chaos in finite hydrological time series
The ability to detect the chaotic signal from a finite time series observation of hydrologic systems is addressed in this paper. The presence of random and seasonal components in hydrological time series, like rainfall or runoff, makes the detection process challenging. Tests with simulated data demonstrate the presence of thresholds, in terms of noise to chaotic-signal and seasonality to chaot...
متن کاملTREND-CYCLE ESTIMATION USING FUZZY TRANSFORM OF HIGHER DEGREE
In this paper, we provide theoretical justification for the application of higher degree fuzzy transform in time series analysis. Under the assumption that a time series can be additively decomposed into a trend-cycle, a seasonal component and a random noise, we demonstrate that the higher degree fuzzy transform technique can be used for the estimation of the trend-cycle, which is one of the ba...
متن کاملParameter Estimation of a Known Chaotic Time Series Corrupted by White Gaussian Noise
The subject of parameter estimation in linear signals embedded in white Gaussian noise has been extensively studied. The subject of nonlinear choatic signals, however, has received much less attention. This paper will examine some of the known techniques for estimating the parameters of chaotic signals such as iterative maps, including the tent map and the logistic map.
متن کامل