Information granules-based long-term forecasting of time series via BPNN under three-way decision framework
C Zhu, X Ma, C Zhang, W Ding, J Zhan - Information Sciences, 2023 - Elsevier
As a significant issue in the machine learning field, the long-term forecasting of time series
has aroused extensive attention from academia and industry. Specifically, transforming time …
has aroused extensive attention from academia and industry. Specifically, transforming time …
Long-term time series forecasting with multilinear trend fuzzy information granules for LSTM in a periodic framework
C Zhu, X Ma, W Ding, J Zhan - IEEE Transactions on Fuzzy …, 2023 - ieeexplore.ieee.org
Considerable research achievements have been made in utilizing information granulation
as an effective technique for addressing long-term time-series forecasting. However, existing …
as an effective technique for addressing long-term time-series forecasting. However, existing …
Temporal deep learning architecture for prediction of COVID-19 cases in India
To combat the recent coronavirus disease 2019 (COVID-19), academician and clinician are
in search of new approaches to predict the COVID-19 outbreak dynamic trends that may …
in search of new approaches to predict the COVID-19 outbreak dynamic trends that may …
Predicting the epidemics trend of COVID-19 using epidemiological-based generative adversarial networks
The Coronavirus disease 2019 (COVID-19) is a respiratory illness that can spread from
person to person. Since the COVID-19 pandemic is spreading rapidly over the world and its …
person to person. Since the COVID-19 pandemic is spreading rapidly over the world and its …
Adapting recurrent neural networks for classifying public discourse on COVID-19 symptoms in Twitter content
The COVID-19 infection, which began in December 2019, has claimed many lives and
impacted all aspects of human life. With time, COVID-19 was identified as a pandemic …
impacted all aspects of human life. With time, COVID-19 was identified as a pandemic …
Analyzing the stock volatility spillovers in Chinese financial and economic sectors
By regarding the Chinese financial and economic sectors as a system, this article studies the
stock volatility spillover in the system and explores its effects on the overall performance of …
stock volatility spillover in the system and explores its effects on the overall performance of …
Forecasting the Spot Market Electricity Price with a Long Short-Term Memory Model Architecture in a Disruptive Economic and Geopolitical Context
In this paper, we perform a short-run Electricity Price Forecast (EPF) with a Recurrent Neural
Network (RNN), namely Long Short-Term Memory (LSTM), using an algorithm that selects …
Network (RNN), namely Long Short-Term Memory (LSTM), using an algorithm that selects …
An autoregressive integrated moving average and long short-term memory (ARIM-LSTM) hybrid model for multi-source epidemic data prediction
The COVID-19 pandemic has far-reaching impacts on the global economy and public
health. To prevent the recurrence of pandemic outbreaks, the development of short-term …
health. To prevent the recurrence of pandemic outbreaks, the development of short-term …
Machine learning approach for forecast analysis of novel COVID-19 scenarios in India
The novel coronavirus (nCOV) is a new strain that needs to be hindered from spreading by
taking effective preventive measures as swiftly as possible. Timely forecasting of COVID-19 …
taking effective preventive measures as swiftly as possible. Timely forecasting of COVID-19 …
Smart COVIDNet: designing an IoT-based COVID-19 disease prediction framework using attentive and adaptive-derived ensemble deep learning
Since the end of 2019, the world has faced severe issues over Corona Virus Disease of
2019 (COVID-19). So there is a need for some essential precautionary measures until the …
2019 (COVID-19). So there is a need for some essential precautionary measures until the …