Configurational entropy spectral analysis (CESAS) is developed with spectral power as a random variable for streamflow forecasting. It is found that the CESAS derived by maximizing the configurational entropy yields the same solution as by the Burg entropy spectral analysis (BESA). Comparison of forecasted streamflows by CESAS and BESA shows less than 0.001% difference between the two analyses and thus the two entropy spectral analyses are concluded to be identical. Thus, the Burg entropy spectral analysis and two configurational entropy spectral analyses form the maximum entropy spectral analysis. (C) 2015 Elsevier B.V. All rights reserved
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Monthly streamflow has elements of stochasticity, seasonality, and periodicity. Spectral analysis an...
Entropy spectral analysis is developed for monthly streamflow forecasting, which contains the use of...
This paper develops a minimum relative entropy theory with frequency as a random variable, called MR...
In the field of stochastic hydrology, hydrologic series is formed with the non- periodic component, ...
Several algorithms have been used in maximum entropy spectral analysis. Among them, the standard Bur...
A new spectral estimate, the maximum entropy method, is described. In the maximum entropy method, th...
A quick and accurate determination of flow passing through a river section is fundamental for a larg...
Forecasting of monthly and annual groundwater levels is important for water resources management, ir...
The method of maximum entropy spectral analysis is reviewed . The main purpose is to establish this ...
This paper was prompted by growing evidence that Shannon's measure of uncertainty can be used as a s...
This dissertation discusses the multivariate hydrologic analysis by the entropy theory. It is divide...
A flow duration curve (FDC) is widely used for predicting water supply, hydropower, environmental fl...
Selecting an optimum number of calibration sites for hydrological modeling is challenging. Modelers ...
Frequency analysis of streamflow is critical for water-resources system planning, water conservancy ...
This paper describes methods for calculating the most likely values of link flows in networks with i...
Monthly streamflow has elements of stochasticity, seasonality, and periodicity. Spectral analysis an...
Entropy spectral analysis is developed for monthly streamflow forecasting, which contains the use of...
This paper develops a minimum relative entropy theory with frequency as a random variable, called MR...
In the field of stochastic hydrology, hydrologic series is formed with the non- periodic component, ...
Several algorithms have been used in maximum entropy spectral analysis. Among them, the standard Bur...
A new spectral estimate, the maximum entropy method, is described. In the maximum entropy method, th...
A quick and accurate determination of flow passing through a river section is fundamental for a larg...
Forecasting of monthly and annual groundwater levels is important for water resources management, ir...
The method of maximum entropy spectral analysis is reviewed . The main purpose is to establish this ...
This paper was prompted by growing evidence that Shannon's measure of uncertainty can be used as a s...
This dissertation discusses the multivariate hydrologic analysis by the entropy theory. It is divide...
A flow duration curve (FDC) is widely used for predicting water supply, hydropower, environmental fl...
Selecting an optimum number of calibration sites for hydrological modeling is challenging. Modelers ...
Frequency analysis of streamflow is critical for water-resources system planning, water conservancy ...
This paper describes methods for calculating the most likely values of link flows in networks with i...