A deep learning algorithm for modeling and forecasting of COVID-19 in five worst affected states of India
A deep learning algorithm for modeling and forecasting of COVID-19 in five worst affected states of India
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DOI：
10.1016/j.aej.2020.09.037
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发表时间：
2020-09-30
影响因子：
6.8
通讯作者：
Bazaz MA
中科院分区：
文献类型：
--
作者：
Farooq J;Bazaz MA
本文采用深度学习提出了一种基于人工神经网络（ANN）的在线增量学习技术，用于开发 Covid-19 大流行的自适应和非侵入性分析模型，以分析疾病传播的时间动态。该模型能够实时智能地适应新的现实情况，而无需每次从不断发展的训练数据中接收到新数据集时从头开始重新训练模型。该模型利用历史数据进行了验证，并预测了印度受影响最严重的五个州未来 30 天的疾病传播情况。
In this paper, deep learning is employed to propose an Artificial Neural Network (ANN) based online incremental learning technique for developing an adaptive and non-intrusive analytical model of Covid-19 pandemic to analyze the temporal dynamics of the disease spread. The model is able to intelligently adapt to new ground realities in real-time eliminating the need to retrain the model from scratch every time a new data set is received from the continuously evolving training data. The model is validated with the historical data and a forecast of the disease spread for 30-days is given in the five worst affected states of India.
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