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AI in Healthcare: Time-Series Forecasting Using Statistical, Neural, and Ensemble Architectures
12 references·1 citing·36 second hop
AI in Healthcare: Time-Series Forecasting Using Statistical, Neural, and Ensemble Architectures (2020)AI in Healthcare: Time-Series Forecasting…Statistical and Machine Learning forecasting methods: Concerns and ways forward (2018)Statistical and Machine Learn…Comparison of ARIMA and Artificial Neural Networks Models for Stock Price Prediction (2014)Comparison of ARIMA and Artif…Simple robust averages of forecasts: Some empirical results (2007)Simple robust averages of for…25 years of time series forecasting (2006)25 years of time series forec…Time series forecasting using a hybrid ARIMA and neural network model (2003)Time series forecasting using…Principles of Forecasting (2001)Principles of ForecastingA simulation study of artificial neural networks for nonlinear time-series forecasting (2001)A simulation study of artific…Forecasting with artificial neural networks: (1998)Forecasting with artificial n…Designing a neural network for forecasting financial and economic time series (1996)Designing a neural network fo…ARIMA model building and the time series analysis approach to forecasting (1983)ARIMA model building and the …Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root (1981)Likelihood Ratio Statistics f…Time Series Analysis Forecasting and Control. (1973)Time Series Analysis Forecast…A hybrid neural network based model for blood donation forecasting (2023)A hybrid neural network based…Time Series Analysis: Forecasting and Control (1977)Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Managerial Applications of Neural Networks: The Case of Bank Failure Predictions (1992)Financial time series forecasting using support vector machines (2003)DeepAR: Probabilistic forecasting with autoregressive recurrent networks (2019)An artificial neural network (p,d,q) model for timeseries forecasting (2009)Stock Price Prediction via Discovering Multi-Frequency Trading Patterns (2017)A systematic review of fundamental and technical analysis of stock market predictions (2019)A hybrid model integrating deep learning with investor sentiment analysis for stock price prediction (2021)A neural network model for bankruptcy prediction (1990)Support vector machine with adaptive parameters in financial time series forecasting (2003)Predicting the Price of Bitcoin Using Machine Learning (2018)Forecasting: theory and practice (2022)Distribution of the Estimators for Autoregressive Time Series with a Unit Root (1979)Testing for a Unit Root in Time Series Regression (1988)Bounds testing approaches to the analysis of level relationships (2001)Unit root tests in panel data: asymptotic and finite-sample properties (2002)Co-Integration and Error Correction: Representation, Estimation, and Testing (1987)On the use of cross-validation for time series predictor evaluation (2012)Stock price prediction using LSTM, RNN and CNN-sliding window model (2017)Time series forecasting of petroleum production using deep LSTM recurrent networks (2018)Time Series Analysis Forecasting and Control. (1971)Another look at measures of forecast accuracy (2006)The M4 Competition: 100,000 time series and 61 forecasting methods (2019)A comparative study of linear and nonlinear models for aggregate retail sales forecasting (2003)A novel nonlinear ensemble forecasting model incorporating GLAR and ANN for foreign exchange rates (2004)Neural network ensemble operators for time series forecasting (2014)A hybrid ARIMA and support vector machines model in stock price forecasting (2004)A novel hybridization of artificial neural networks and ARIMA models for time series forecasting (2010)Recurrent Neural Networks for Time Series Forecasting: Current status and future directions (2020)Expert Opinions in Forecasting: The Role of the Delphi Technique (2001)Consensus measurement in Delphi studies (2012)Rethinking Partial Least Squares Path Modeling: In Praise of Simple Methods (2012)Revealing the dynamic network structure of the Beck Depression Inventory-II (2014)The life course cube: A tool for studying lives (2018)Assessing the environmental impacts of renewable energy sources: A case study on air pollution and carbon emissions in China (2023)
this work references cited by second hop

References

  • 1981Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root14,647 cited
  • 2003Time series forecasting using a hybrid ARIMA and neural network model4,469 cited
  • 1998Forecasting with artificial neural networks:4,225 cited
  • 200625 years of time series forecasting1,589 cited
  • 2018Statistical and Machine Learning forecasting methods: Concerns and ways forward1,515 cited
  • 2001Principles of Forecasting1,178 cited
  • 1996Designing a neural network for forecasting financial and economic time series1,092 cited
  • 1973Time Series Analysis Forecasting and Control.972 cited
  • 2014Comparison of ARIMA and Artificial Neural Networks Models for Stock Price Prediction579 cited
  • 2001A simulation study of artificial neural networks for nonlinear time-series forecasting336 cited
  • 2007Simple robust averages of forecasts: Some empirical results242 cited
  • 1983ARIMA model building and the time series analysis approach to forecasting211 cited

Cited by

  • 2023A hybrid neural network based model for blood donation forecasting13 cited

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