FRACTAL ASSESSMENT OF WAVELET BASED TECHNIQUES FOR RIVER FLOW TIME SERIES -A CASE STUDY OF GHAR-E-AGHAJ RIVER IN FARS PROVINCE

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FATAHI M.H.; TALEBBEYDOKHTI N.; RAKHSHANDEHROU GH.R.; SHAMSAI A.

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Journal: Journal of Water Resources Engineering Year:2011 | Volume:3 | Issue:5-6-7 Page(s): 1-11

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Title

FRACTAL ASSESSMENT OF WAVELET BASED TECHNIQUES FOR RIVER FLOW TIME SERIES -A CASE STUDY OF GHAR-E-AGHAJ RIVER IN FARS PROVINCE

Author(s)

FATAHI M.H. | TALEBBEYDOKHTI N. | RAKHSHANDEHROU GH.R. | SHAMSAI A. | Issue Writer Certificate

Keywords

WAVELETQ3

DE-NOISINGQ3

PREDICTABILITYQ3

TIME SERIES FRACTAL ANALYSISQ3

VALID LENGTHQ3

ANNQ3

Abstract

WAVELET analysis was used to preprocess the river flow time series in the present study. Using continuous and discrete WAVELET transforms the given signals which were the Ghar-e-Aghaj River flow time series in studying stations have been decomposed into approximation and detail signals. Approximation signal denoted the basic trend of the signal and the detail signal depicts the irregularities like jumps and sharp spikes. Using the fractal analysis the Hurst number of each time series was calculated and through that the time series correlation and persistency of the signals before and after the DE-NOISING can be retrievable. The average power of signals was also achieved through a spectral method. Studying the signals correlation and the average power one can understand that the signals correlation grow significantly after the preprocessing while the average power decrease to half. Thus, it can be claimed that half of the signal’s energy is the irregularities participation in the total power. Preprocessed and non-processed time series have been predicted using a multi-layer Perceptron artificial neural network with a Levenberg Marquardt training algorithm. Results of the predicting model depicted significant enhancement in the preprocessed river flow time series prediction. Results also showed that the discrete WAVELET transform is superior to continuous WAVELET transform for data preprocessing.

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APA: Copy

FATAHI, M.H., TALEBBEYDOKHTI, N., RAKHSHANDEHROU, GH.R., & SHAMSAI, A.. (2011). FRACTAL ASSESSMENT OF WAVELET BASED TECHNIQUES FOR RIVER FLOW TIME SERIES -A CASE STUDY OF GHAR-E-AGHAJ RIVER IN FARS PROVINCE. WATER ENGINEERING, 3(5-6-7), 1-11. SID. https://sid.ir/paper/169487/en

Vancouver: Copy

FATAHI M.H., TALEBBEYDOKHTI N., RAKHSHANDEHROU GH.R., SHAMSAI A.. FRACTAL ASSESSMENT OF WAVELET BASED TECHNIQUES FOR RIVER FLOW TIME SERIES -A CASE STUDY OF GHAR-E-AGHAJ RIVER IN FARS PROVINCE. WATER ENGINEERING[Internet]. 2011;3(5-6-7):1-11. Available from: https://sid.ir/paper/169487/en

IEEE: Copy

M.H. FATAHI, N. TALEBBEYDOKHTI, GH.R. RAKHSHANDEHROU, and A. SHAMSAI, “FRACTAL ASSESSMENT OF WAVELET BASED TECHNIQUES FOR RIVER FLOW TIME SERIES -A CASE STUDY OF GHAR-E-AGHAJ RIVER IN FARS PROVINCE,” WATER ENGINEERING, vol. 3, no. 5-6-7, pp. 1–11, 2011, [Online]. Available: https://sid.ir/paper/169487/en

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