Data analysis of sea water quality and climatological factors

Endangering marine life, disruption of local economies, and human health are some of the effects of harmful algae blooms in many parts of the world. In Hong Kong, these events are particularly concerning because of the region’s dense population and heavy reliance on seafood. Several research papers...

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Main Author: Kwok, Chin Kiat
Other Authors: Wong Kin Shun, Terence
Format: Final Year Project (FYP)
Language:English
Published: Nanyang Technological University 2024
Subjects:
Online Access:https://hdl.handle.net/10356/176480
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author Kwok, Chin Kiat
author2 Wong Kin Shun, Terence
author_facet Wong Kin Shun, Terence
Kwok, Chin Kiat
author_sort Kwok, Chin Kiat
collection NTU
description Endangering marine life, disruption of local economies, and human health are some of the effects of harmful algae blooms in many parts of the world. In Hong Kong, these events are particularly concerning because of the region’s dense population and heavy reliance on seafood. Several research papers regarding the use of prediction models to estimate water quality have been published for various locations around the world, namely in the United States and Hong Kong. In Hong Kong, empirical analysis has been done using deep neural network models with 3 to 12 layers have been deployed to 1990-2016 data from the Hong Kong Environmental Protection Department. This paper aims to evaluate the predictability of E. coli using a variety of models in the selected affected areas of Hong Kong. The objectives were to identify relevant factors and variables affecting the widespread growth of harmful algae blooms and conclude on the best model for the prediction of E. coli using various quantifying tools to check the fit of the model for our use case.
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spelling ntu-10356/1764802024-05-24T15:50:27Z Data analysis of sea water quality and climatological factors Kwok, Chin Kiat Wong Kin Shun, Terence School of Electrical and Electronic Engineering EKSWONG@ntu.edu.sg Engineering Engineering Endangering marine life, disruption of local economies, and human health are some of the effects of harmful algae blooms in many parts of the world. In Hong Kong, these events are particularly concerning because of the region’s dense population and heavy reliance on seafood. Several research papers regarding the use of prediction models to estimate water quality have been published for various locations around the world, namely in the United States and Hong Kong. In Hong Kong, empirical analysis has been done using deep neural network models with 3 to 12 layers have been deployed to 1990-2016 data from the Hong Kong Environmental Protection Department. This paper aims to evaluate the predictability of E. coli using a variety of models in the selected affected areas of Hong Kong. The objectives were to identify relevant factors and variables affecting the widespread growth of harmful algae blooms and conclude on the best model for the prediction of E. coli using various quantifying tools to check the fit of the model for our use case. Bachelor's degree 2024-05-20T04:43:32Z 2024-05-20T04:43:32Z 2024 Final Year Project (FYP) Kwok, C. K. (2024). Data analysis of sea water quality and climatological factors. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/176480 https://hdl.handle.net/10356/176480 en application/pdf Nanyang Technological University
spellingShingle Engineering
Engineering
Kwok, Chin Kiat
Data analysis of sea water quality and climatological factors
title Data analysis of sea water quality and climatological factors
title_full Data analysis of sea water quality and climatological factors
title_fullStr Data analysis of sea water quality and climatological factors
title_full_unstemmed Data analysis of sea water quality and climatological factors
title_short Data analysis of sea water quality and climatological factors
title_sort data analysis of sea water quality and climatological factors
topic Engineering
Engineering
url https://hdl.handle.net/10356/176480
work_keys_str_mv AT kwokchinkiat dataanalysisofseawaterqualityandclimatologicalfactors