COVID-19 growth prediction using multivariate long short term memory

05/10/2020
by   Novanto Yudistira, et al.
0

Coronavirus disease (covid-19) spread forecasting is an important task to track the growth of pandemic. Existing predictions are merely based on qualitative analysis and mathematical modeling. The use as much as possible of available big data with machine learning is still limited in covid-19 growth prediction even though the availability of data is abundance. To make use of big data in prediction by using deep learning, we use Long Short Term Memory (LSTM) method to learn correlation of covid-19 growth over time. The structure of LSTM layer is searched heuristically until achieving the best validation score. Firstly, we trained training data containing confirmed cases from around the globe. We achieve favorable performance compared to RNN method with comparable low validation error. The evaluation is done based on graph visualization and RMSE. We found that it is difficult to achieve exactly the same quantity of confirmed cases over time, however, LSTM is able to provide similar pattern between actual and prediction. In future, our proposed prediction can be used for anticipating the forthcoming pandemics. The code is provided here: https://github.com/cbasemaster/lstmcorona

READ FULL TEXT
research
09/14/2020

Short-Term Forecasting COVID-19 Cases In Turkey Using Long Short-Term Memory Network

COVID-19 has been one of the most severe diseases, causing a harsh pande...
research
07/10/2022

Deep Transformer Model with Pre-Layer Normalization for COVID-19 Growth Prediction

Coronavirus disease or COVID-19 is an infectious disease caused by the S...
research
09/07/2020

Projections for COVID-19 spread in India and its worst affected five states using the Modified SEIRD and LSTM models

The last leg of the year 2019 gave rise to a virus named COVID-19 (Coron...
research
01/25/2023

Prediction of COVID-19 by Its Variants using Multivariate Data-driven Deep Learning Models

The Coronavirus Disease 2019 or the COVID-19 pandemic has swept almost a...
research
10/27/2021

LSTM-RPA: A Simple but Effective Long Sequence Prediction Algorithm for Music Popularity Prediction

The big data about music history contains information about time and use...
research
08/26/2022

Static Seeding and Clustering of LSTM Embeddings to Learn from Loosely Time-Decoupled Events

Humans learn from the occurrence of events in a different place and time...
research
11/14/2022

An Interpretable Hybrid Predictive Model of COVID-19 Cases using Autoregressive Model and LSTM

The Coronavirus Disease 2019 (COVID-19) has posed a severe threat to glo...

Please sign up or login with your details

Forgot password? Click here to reset