ArticleChaos, solitons, and fractals2021
A novel grey model based on traditional Richards model and its application in COVID-19.
Article in Chaos, solitons, and fractals, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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11 citing papers in PubMed.
- Predicting the incidence of rifampicin resistant tuberculosis in Yunnan, China: a seasonal time series analysis based on routine surveillance data.BMC infectious diseases · 2024Article
- Two novel nonlinear multivariate grey models with kernel learning for small-sample time series prediction.Nonlinear dynamics · 2023Article
- Analysis of COVID-19 outbreak in Hubei province based on Tencent's location big data.Frontiers in public health · 2023Article
- Application of logistic differential equation models for early warning of infectious diseases in Jilin Province.BMC public health · 2022Article
- A novel grey model based on Susceptible Infected Recovered Model: A case study of COVD-19.Physica A · 2022Article
- Forecasting the transmission trends of respiratory infectious diseases with an exposure-risk-based model at the microscopic level.Environmental research · 2022Article
- Prediction intervals of the COVID-19 cases by HAR models with growth rates and vaccination rates in top eight affected countries: Bootstrap improvement.Chaos, solitons, and fractals · 2022Article
- Predicting the Number of Reported Pulmonary Tuberculosis in Guiyang, China, Based on Time Series Analysis Techniques.Computational and mathematical methods in medicine · 2022Article
- Modeling and forecasting the COVID-19 pandemic with heterogeneous autoregression approaches: South Korea.Results in physics · 2021Article
- Short-term prediction of COVID-19 spread using grey rolling model optimized by particle swarm optimization.Applied soft computing · 2021Article
- A new grey quadratic polynomial model and its application in the COVID-19 in China.Scientific reports · 2021Article
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3 authors.
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Abstract
In 2020, a new type of coronavirus is in the global pandemic. Now, the number of infected patients is increasing. The trend of the epidemic has attracted global attention. Based on the traditional Richards model and the differential information principle in grey prediction model, this paper uses the modified grey action quantity to propose a new grey prediction model for infectious diseases. This model weakens the dependence of the Richards model on single-peak and saturated S-shaped data, making Richards model more applicable, and uses genetic algorithm to optimize the nonlinear terms and the background value. To illustrate the effectiveness of the model, groups of slowly growing small-sample and large-sample data are selected for simulation experiments. Results of eight evaluation indexes show that the new model is better than the traditional GM(1,1) and grey Richards model. Finally, this model is applied to China, Italy, Britain and Russia. The results show that the new model is better than the other 7 models. Therefore, this model can effectively predict the number of daily new confirmed cases of COVID-19, and provide important prediction information for the formulation of epidemic prevention policies.
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