ArticleIEEE transactions on instrumentation and measurement2021
EVDHM-ARIMA-Based Time Series Forecasting Model and Its Application for COVID-19 Cases.
Article in IEEE transactions on instrumentation and measurement, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- FCP-Former: Enhancing Long-Term Multivariate Time Series Forecasting with Frequency Compensation.Sensors (Basel, Switzerland) · 2025Article
- Characterization of RAP Signal Patterns, Temporal Relationships, and Artifact Profiles Derived from Intracranial Pressure Sensors in Acute Traumatic Neural Injury.Sensors (Basel, Switzerland) · 2025Article
- Fuzzy inference-based LSTM for long-term time series prediction.Scientific reports · 2023Article
- A novel online multi-task learning for COVID-19 multi-output spatio-temporal prediction.Heliyon · 2023Article
- Semi-Supervised KPCA-Based Monitoring Techniques for Detecting COVID-19 Infection through Blood Tests.Diagnostics (Basel, Switzerland) · 2023Article
- Hybrid prediction of infections and deaths due to COVID-19 in two Colombian data series.PloS one · 2023Article
- Nonstationary time series forecasting using optimized-EVDHM-ARIMA for COVID-19.Frontiers in big data · 2023Article
- McS-Net: Multi-class Siamese network for severity of COVID-19 infection classification from lung CT scan slices.Applied soft computing · 2022Article
- A comparative study for predictive monitoring of COVID-19 pandemic.Applied soft computing · 2022Article
- Interval type-2 fuzzy computational model for real time Kalman filtering and forecasting of the dynamic spreading behavior of novel Coronavirus 2019.ISA transactions · 2022Article
- An Empirical Mode Decomposition Fuzzy Forecast Model for COVID-19.Neural processing letters · 2022Article
- A proficient approach to forecast COVID-19 spread via optimized dynamic machine learning models.Scientific reports · 2022Article
- Deep Generative Learning-Based 1-SVM Detectors for Unsupervised COVID-19 Infection Detection Using Blood Tests.IEEE transactions on instrumentation and measurement · 2022Article
- Impact of social determinants on COVID-19 infections: a comprehensive study from Saudi Arabia governorates.Humanities & social sciences communications · 2022Review
- Supply forecasting and profiling of urban supermarket chains based on tensor quantization exponential regression for social governance.PeerJ. Computer science · 2022Article
- COVID-19 disease identification from chest CT images using empirical wavelet transformation and transfer learning.Biomedical signal processing and control · 2022Article
- Identification of the ARX Model with Random Impulse Noise Based on Forgetting Factor Multi-error Information Entropy.Circuits, systems, and signal processing · 2022Article
- LBP-based information assisted intelligent system for COVID-19 identification.Computers in biology and medicine · 2021Article
- Optimization in the Context of COVID-19 Prediction and Control: A Literature Review.IEEE access : practical innovations, open solutions · 2021Article
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4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
The time-series forecasting makes a substantial contribution in timely decision-making. In this article, a recently developed eigenvalue decomposition of Hankel matrix (EVDHM) along with the autoregressive integrated moving average (ARIMA) is applied to develop a forecasting model for nonstationary time series. The Phillips-Perron test (PPT) is used to define the nonstationarity of time series. EVDHM is applied over a time series to decompose it into respective subcomponents and reduce the nonstationarity. ARIMA-based model is designed to forecast the future values for each subcomponent. The forecast values of each subcomponent are added to get the final output values. The optimized value of ARIMA parameters for each subcomponent is obtained using a genetic algorithm (GA) for minimum values of Akaike information criterion (AIC). Model performance is evaluated by estimating the future values of daily new cases of the recent pandemic disease COVID-19 for India, USA, and Brazil. The high efficacy of the proposed method is convinced with the results.
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