Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/77958
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dc.contributor.authorKamdar, Dhruv Kamlesh
dc.date.accessioned2019-06-10T06:48:45Z
dc.date.available2019-06-10T06:48:45Z
dc.date.issued2019
dc.identifier.urihttp://hdl.handle.net/10356/77958
dc.description.abstractWater in Singapore is treated to make it safe for consumption. Many tests are conducted to eliminate harmful bacteria; however, the common treatment methods may not be effective in removing all the bacteria that may cause harm. Machine learning can be introduced to improve on the filtering process, allowing classification of bacteria of interest. An initial study of the bacteria followed by the designing of a classifier will boost the detection and classification process. This project proposes an implementation of Support Vector Machine and Artificial Neural Network Classifiers to enable classification and predictions of giardia from samples of water.en_US
dc.format.extent57 p.en_US
dc.language.isoenen_US
dc.rightsNanyang Technological University
dc.subjectDRNTU::Engineering::Electrical and electronic engineeringen_US
dc.titleImaging process and data management of drinking water bacteriaen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorLiu Aiqunen_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeBachelor of Engineering (Electrical and Electronic Engineering)en_US
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Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)
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