Dengue prediction using neural network

Remle, Nor Atikah (2017) Dengue prediction using neural network. Project Report. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia. (Submitted)

	Text (24 Pages) Dengue prediction using neural network.pdf - Submitted Version Download (373kB)
	Text (Full Text) Dengue prediction using neural network.pdf - Submitted Version Restricted to Registered users only Download (2MB)

Abstract

Dengue Prediction Using Neural Network (DPUNN) is a system that help user to know the dengue cases and prediction of dengue cases in Malaysia. This system using Artificial Neural Network (ANN) technique to predict the dengue cases. The model of the neural network is used to test for the prediction based on dengue data and to know either NN can solve the problem for dengue prediction. Furthermore, waterfall model is used in the methodology part which have analysis, requirements specification, design, implementation, testing and integration and lastly operation and maintenance to make sure the system is successfully. This system developed using XAMPP, MySQL as database, bootstrap as a template and other software which is include Adobe Photoshop CS6, Matlab and Microsoft Project 2007. Other than that, this DPUNN evaluate the performance of dengue prediction application using real dengue data in Malaysia. Then, after evaluation it will correct the model accordingly and use the model to put in the system. Lastly, this system can make user alert to the dengue cases on their current state.

Actions (login required)

View Item