Prediction of dengue cases using the attention-based long short-term memory (LSTM) approach
This research proposes a ‘temporal attention’ addition for long-short term memory (LSTM) models for dengue prediction. The number of monthly dengue cases was collected for each of five Malaysian states i.e. Selangor, Kelantan, Johor, Pulau Pinang, and Melaka from 2011 to 2016. Climatic, demographic,...
Main Authors: | Majeed, Mokhalad A., Shafri, Helmi Z. M., Wayayok, Aimrun, Zulkafli, Zed |
---|---|
Format: | Article |
Published: |
PAGEPress Publications
2023
|
Similar Items
-
Fuzzy-embedded long short-term memory (FE-LSTM) with application in stock trading
by: Lim, Tammy Lee Xin
Published: (2022) -
Short-term multi-step-ahead sector-based traffic flow prediction based on the attention-enhanced graph convolutional LSTM network (AGC-LSTM)
by: Zhang, Ying, et al.
Published: (2024) -
Electrocorticography based motor imagery movements classification using long short-term memory (LSTM) based on deep learning approach
by: Rashid, Mamunur, et al.
Published: (2020) -
Perbandingan Metode Forecast berdasarkan Rerata dan Metode Long Short Term Memory (LSTM) pada PT. Indofarma Tbk.
by: Praditya, Tifa Ayu, et al.
Published: (2020) -
Foreign exchange prediction using long short-term memory neural network
by: Sim, Ming Shi
Published: (2019)