Samira Shirzaei Data-verified
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Researcher
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Biography and Research Information
OverviewAI-generated summary
Samira Shirzaei's research focuses on the application of statistical and machine learning models for forecasting and quality control. Her work includes comparative studies of models such as SIR, Linear Regression, Logistic Function, and ARIMA for predicting COVID-19 cases. She has also investigated the use of ARIMA and SARIMA models with grid search for forecasting COVID-19 numbers in the United States. Additionally, Shirzaei has explored quality control methods using S2 or S charts for subgroups of varying sample sizes, examining their average run lengths. Her research also extends to the acceptability of artificial intelligence in industrial processes, specifically within poultry processing, and the classification efficiencies of different models for categorizing breast fillet myopathies.
Metrics
- h-index: 3
- Publications: 7
- Citations: 60
Selected Publications
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"COVID vaccine" Google searches predict increases in percent anxiety and depression within the United States (2022)
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A comparative study of SIR Model, Linear Regression, Logistic Function and ARIMA Model for forecasting COVID-19 cases (2021)
Collaboration Network
Top Collaborators
- A comparative study of SIR Model, Linear Regression, Logistic Function and ARIMA Model for forecasting COVID-19 cases
- Forecasting COVID-19 Number of Cases by Implementing ARIMA and SARIMA with Grid Search in United States
- Quality control using S2 or S charts for subgroups of varying sample sizes and their exact average run lengths
- Acceptability of Artificial Intelligence in Poultry Processing and Classification Efficiencies of Different Classification Models in the Categorisation of Breast Fillet Myopathies
- Acceptability of Artificial Intelligence in Poultry Processing and Classification Efficiencies of Different Classification Models in the Categorisation of Breast Fillet Myopathies
- Acceptability of Artificial Intelligence in Poultry Processing and Classification Efficiencies of Different Classification Models in the Categorisation of Breast Fillet Myopathies
- Acceptability of Artificial Intelligence in Poultry Processing and Classification Efficiencies of Different Classification Models in the Categorisation of Breast Fillet Myopathies
- Acceptability of Artificial Intelligence in Poultry Processing and Classification Efficiencies of Different Classification Models in the Categorisation of Breast Fillet Myopathies
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