Early prediction of dengue outbreak using Artificial Neural Network (ANN) / Muhammad Sirajuddin Ismail

The dengue fever is a mosquito-borne viral infection that has become one of the world's most quickly spreading and dangerous diseases. To prevent and lessen the impact, effective public health management and control tactics require early dengue epidemic detection and forecasting. This study aim...

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Main Author:	Ismail, Muhammad Sirajuddin
Format:	Thesis
Language:	English
Published:	2024
Subjects:	Neural networks (Computer science)
Online Access:	https://ir.uitm.edu.my/id/eprint/95728/1/95728.pdf
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id	my-uitm-ir.95728
record_format	uketd_dc
spelling	my-uitm-ir.957282024-05-30T15:12:39Z Early prediction of dengue outbreak using Artificial Neural Network (ANN) / Muhammad Sirajuddin Ismail 2024 Ismail, Muhammad Sirajuddin Neural networks (Computer science) The dengue fever is a mosquito-borne viral infection that has become one of the world's most quickly spreading and dangerous diseases. To prevent and lessen the impact, effective public health management and control tactics require early dengue epidemic detection and forecasting. This study aims to investigate the requirements of utilizing the Artificial Neural Network algorithm for prediction of dengue outbreak. The objective is to develop Dengue Outbreak Prediction System using Artificial Neural Network algorithm and evaluate its performance. By employing this algorithm, we can analyse historical dengue data, weather conditions, and other relevant factors these may include temperature, humidity, rainfall, and population density to predict potential outbreak accurately. The developed model holds the potential to assist healthcare industry in findings and predictions that can help raise awareness among community members, empowering them to take preventive measures and participate in vector control efforts. This research contributes to the field by exploring the application of machine learning algorithms in the healthcare industry. The results of this study will provide valuable insights into enhancing the efficiency and reliability of dengue outbreak, ultimately benefiting both the healthcare and people around the world. 2024 Thesis https://ir.uitm.edu.my/id/eprint/95728/ https://ir.uitm.edu.my/id/eprint/95728/1/95728.pdf text en public degree Universiti Teknologi MARA, Terengganu College of Computing, Informatics and Mathematics Abd Talib, Hasnita
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Abd Talib, Hasnita
topic	Neural networks (Computer science)
spellingShingle	Neural networks (Computer science) Ismail, Muhammad Sirajuddin Early prediction of dengue outbreak using Artificial Neural Network (ANN) / Muhammad Sirajuddin Ismail
description	The dengue fever is a mosquito-borne viral infection that has become one of the world's most quickly spreading and dangerous diseases. To prevent and lessen the impact, effective public health management and control tactics require early dengue epidemic detection and forecasting. This study aims to investigate the requirements of utilizing the Artificial Neural Network algorithm for prediction of dengue outbreak. The objective is to develop Dengue Outbreak Prediction System using Artificial Neural Network algorithm and evaluate its performance. By employing this algorithm, we can analyse historical dengue data, weather conditions, and other relevant factors these may include temperature, humidity, rainfall, and population density to predict potential outbreak accurately. The developed model holds the potential to assist healthcare industry in findings and predictions that can help raise awareness among community members, empowering them to take preventive measures and participate in vector control efforts. This research contributes to the field by exploring the application of machine learning algorithms in the healthcare industry. The results of this study will provide valuable insights into enhancing the efficiency and reliability of dengue outbreak, ultimately benefiting both the healthcare and people around the world.
format	Thesis
qualification_level	Bachelor degree
author	Ismail, Muhammad Sirajuddin
author_facet	Ismail, Muhammad Sirajuddin
author_sort	Ismail, Muhammad Sirajuddin
title	Early prediction of dengue outbreak using Artificial Neural Network (ANN) / Muhammad Sirajuddin Ismail
title_short	Early prediction of dengue outbreak using Artificial Neural Network (ANN) / Muhammad Sirajuddin Ismail
title_full	Early prediction of dengue outbreak using Artificial Neural Network (ANN) / Muhammad Sirajuddin Ismail
title_fullStr	Early prediction of dengue outbreak using Artificial Neural Network (ANN) / Muhammad Sirajuddin Ismail
title_full_unstemmed	Early prediction of dengue outbreak using Artificial Neural Network (ANN) / Muhammad Sirajuddin Ismail
title_sort	early prediction of dengue outbreak using artificial neural network (ann) / muhammad sirajuddin ismail
granting_institution	Universiti Teknologi MARA, Terengganu
granting_department	College of Computing, Informatics and Mathematics
publishDate	2024
url	https://ir.uitm.edu.my/id/eprint/95728/1/95728.pdf
_version_	1804889972733378560

Early prediction of dengue outbreak using Artificial Neural Network (ANN) / Muhammad Sirajuddin Ismail

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