PERFORMANCE IMPROVEMENT OF BIOLOGICAL BOD IN RIVERS BASED ON DE-NOISING COMPARISON WAVELET-ANN CONJUNCTION, GP, ANN AND MLR METHODS (CASE STUDY: KARAJ DAM OUTLET STATION)

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RAJAEE TAHER; JAFARI HAMIDEH; RAHIMI ROGHAYEH

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Journal: AMIRKABIR JOURNAL OF CIVIL ENGINEERING (AMIRKABIR) Year:2017 | Volume:49 | Issue:2 Page(s): 273-284

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Title

PERFORMANCE IMPROVEMENT OF BIOLOGICAL BOD IN RIVERS BASED ON DE-NOISING COMPARISON WAVELET-ANN CONJUNCTION, GP, ANN AND MLR METHODS (CASE STUDY: KARAJ DAM OUTLET STATION)

Author(s)

RAJAEE TAHER | JAFARI HAMIDEH | RAHIMI ROGHAYEH | Issue Writer Certificate

Keywords

ARTIFICIAL NEURAL NETWORKQ1

BODQ1

DE-NOISINGQ2

KARAJ RIVERQ1

WAVELET TRANSFORMQ2

Abstract

This study considered ARTIFICIAL NEURAL NETWORK (ANN), multi-linear regression (MLR), Genetic Programming (GP) and wavelet analysis and ANN combination (WANN) models for monthly water biological oxygen demand (BOD) in station Karaj Dam outlet and investigates the effects of data preprocessing on model performance using discrete wavelet. For this purpose, in the first proposed model, observed time series of BOD were decomposed into several sub-time series at different scales by discrete WAVELET TRANSFORM. Then these sub-time series were imposed as inputs to the ANN method. In the second proposed model, observed time series of BOD were decomposed at ten scales by wavelet analysis. Then, total effective time series BOD were imposed as inputs to the neural network model for prediction of BOD in one month ahead. Results showed that the wavelet neural network models performance was better in prediction rather than the neural network and multi-linear regression models. The wavelet analysis model produced reasonable predictions for the extreme values. This model dropped the mean absolute percentage error for the MLR, GP, ANN and the first hybrid models from 1.87, 0.91, 0.65 and 0.46 respectively, to 0.44 and increased the Nash-Sutcliffe model efficiency coefficient from 0.23, 0.53, 0.73 and 0.81 to 0.83..

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APA: Copy

RAJAEE, TAHER, JAFARI, HAMIDEH, & RAHIMI, ROGHAYEH. (2017). PERFORMANCE IMPROVEMENT OF BIOLOGICAL BOD IN RIVERS BASED ON DE-NOISING COMPARISON WAVELET-ANN CONJUNCTION, GP, ANN AND MLR METHODS (CASE STUDY: KARAJ DAM OUTLET STATION). AMIRKABIR JOURNAL OF CIVIL ENGINEERING (AMIRKABIR), 49(2 ), 273-284. SID. https://sid.ir/paper/165820/en

Vancouver: Copy

RAJAEE TAHER, JAFARI HAMIDEH, RAHIMI ROGHAYEH. PERFORMANCE IMPROVEMENT OF BIOLOGICAL BOD IN RIVERS BASED ON DE-NOISING COMPARISON WAVELET-ANN CONJUNCTION, GP, ANN AND MLR METHODS (CASE STUDY: KARAJ DAM OUTLET STATION). AMIRKABIR JOURNAL OF CIVIL ENGINEERING (AMIRKABIR)[Internet]. 2017;49(2 ):273-284. Available from: https://sid.ir/paper/165820/en

IEEE: Copy

TAHER RAJAEE, HAMIDEH JAFARI, and ROGHAYEH RAHIMI, “PERFORMANCE IMPROVEMENT OF BIOLOGICAL BOD IN RIVERS BASED ON DE-NOISING COMPARISON WAVELET-ANN CONJUNCTION, GP, ANN AND MLR METHODS (CASE STUDY: KARAJ DAM OUTLET STATION),” AMIRKABIR JOURNAL OF CIVIL ENGINEERING (AMIRKABIR), vol. 49, no. 2 , pp. 273–284, 2017, [Online]. Available: https://sid.ir/paper/165820/en

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