A Deep Learning Approach for Dengue Fever Prediction in Malaysia Using LSTM with Spatial Attention

This research aims to predict dengue fever cases in Malaysia using machine learning techniques. A dataset consisting of weekly dengue cases at the state level in Malaysia from 2010 to 2016 was obtained from the Malaysia Open Data website and includes variables such as climate, geography, and demogra...

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Veröffentlicht in:	International journal of environmental research and public health 2023-02, Vol.20 (5), p.4130
Hauptverfasser:	Majeed, Mokhalad A, Shafri, Helmi Zulhaidi Mohd, Zulkafli, Zed, Wayayok, Aimrun
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Climate Comparative analysis Datasets Decision trees Deep Learning Demographic variables Demography Dengue Dengue fever Development and progression Forecasting Geography Humans Humidity Land use Long short-term memory Machine Learning Malaysia Mosquitoes Neural networks Population density Predictions Public health Rain Root-mean-square errors Support vector machines Time series Vector-borne diseases Websites
Online-Zugang:	Volltext
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