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Forecasting Water Quality, Parameters By Neural Network Technique

FYP Sem 2 2019/2020

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Main Author: Aldobai, Aiad Mazin Deeb
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Published: 2023
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WQI by IE Moddling
Water Quality
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spelling my.uniten.dspace-214592023-05-04T15:36:40Z Forecasting Water Quality, Parameters By Neural Network Technique Aldobai, Aiad Mazin Deeb WQI by IE Moddling Water Quality FYP Sem 2 2019/2020 Throughout this study, an approximate Water Quality Index (WQI) in Kelantan River, Malaysia, will also be developed and validated for an Artificial Neural Network (ANN). Digital information from 30 data collection locations was designed and tested for the ANN model. Two sets for simulation data were separated. For the first set of ANNs, five independent water quality variables were used as input parameters to be trained, checked and validated. As a result, multiple linear regression (MLR) was utilized to replace the independent variables with the lowest variance commitment. Dissolved Oxygen (DO) cover independent variables representing substantially 75% of WQI variance; Biochemical Solids (SS), Ammoniacal Nitrate (AN), Biochemical Oxygen Demand (BOD). Only 8% and 2% of the discrepancy made a significant contribution to the substance Oxygen Demand (COD) and the pH. Therefore, only four independent variables for preparation, testing and recognition of ANN have been used in the 2nd collection of information. In addition, the statistical significance given by six independent variables (0.92) in prediction of WQI are only marginally better than the actual WQI (0.91) data sets, including one that clearly demonstrate the ANN network, whether it is trained by fuzzy inference system (ANFIS) to redact COD and the pH as independent variables, to investigate WQI accurately . 2023-05-03T16:57:50Z 2023-05-03T16:57:50Z 2020-02 https://irepository.uniten.edu.my/handle/123456789/21459 application/pdf
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
topic WQI by IE Moddling
Water Quality
spellingShingle WQI by IE Moddling
Water Quality
Aldobai, Aiad Mazin Deeb
Forecasting Water Quality, Parameters By Neural Network Technique
description FYP Sem 2 2019/2020
format
author Aldobai, Aiad Mazin Deeb
author_facet Aldobai, Aiad Mazin Deeb
author_sort Aldobai, Aiad Mazin Deeb
title Forecasting Water Quality, Parameters By Neural Network Technique
title_short Forecasting Water Quality, Parameters By Neural Network Technique
title_full Forecasting Water Quality, Parameters By Neural Network Technique
title_fullStr Forecasting Water Quality, Parameters By Neural Network Technique
title_full_unstemmed Forecasting Water Quality, Parameters By Neural Network Technique
title_sort forecasting water quality, parameters by neural network technique
publishDate 2023
_version_ 1806424469083783168
score 13.222552

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