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Time Series Forecasting with Statistical, Machine Learning, and Deep Learning Methods: Past, Present, and Future
16 references·1 citing·28 second hopsampled
Time Series Forecasting with Statistical, Machine Learning, and Deep Learning Methods: Past, Present, and Future (2023)Time Series Forecasting with Statistical,…M5 accuracy competition: Results, findings, and conclusions (2022)M5 accuracy competition: Resu…Forecasting: theory and practice (2022)Forecasting: theory and pract…Recurrent Neural Networks for Time Series Forecasting: Current status and future directions (2020)Recurrent Neural Networks for…The M4 Competition: 100,000 time series and 61 forecasting methods (2019)The M4 Competition: 100,000 t…N-BEATS: Neural basis expansion analysis for interpretable time series forecasting (2019)N-BEATS: Neural basis expansi…DeepAR: Probabilistic forecasting with autoregressive recurrent networks (2019)DeepAR: Probabilistic forecas…A hybrid method of exponential smoothing and recurrent neural networks for time series forecasting (2019)A hybrid method of exponentia…Statistical and Machine Learning forecasting methods: Concerns and ways forward (2018)Statistical and Machine Learn…Conditional Time Series Forecasting with Convolutional Neural Networks (2017)Conditional Time Series Forec…Optimal combination forecasts for hierarchical time series (2011)Optimal combination forecasts…25 years of time series forecasting (2006)25 years of time series forec…A state space framework for automatic forecasting using exponential smoothing methods (2002)A state space framework for a…The theta model: a decomposition approach to forecasting (2000)The theta model: a decomposit…Out-of-sample tests of forecasting accuracy: an analysis and review (2000)Out-of-sample tests of foreca…Forecasting with artificial neural networks: (1998)Forecasting with artificial n…The Combination of Forecasts (1969)The Combination of ForecastsGA-LSTM: Performance Optimization of LSTM driven Time Series Forecasting (2024)GA-LSTM: Performance Optimiza…Book Review: Time Series Analysis: Forecasting and Control (1977)Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)The accuracy of extrapolation (time series) methods: Results of a forecasting competition (1982)Financial time series forecasting using support vector machines (2003)Time series forecasting using a hybrid ARIMA and neural network model (2003)The Precision of National Income Estimates (1942)New Methods of Quality Control (1963)Short-Term Sales Forecasting (1965)Principles of Forecasting (2001)Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy (2009)Error measures for generalizing about forecasting methods: Empirical comparisons (1992)The M3-Competition: results, conclusions and implications (2000)On the use of cross-validation for time series predictor evaluation (2012)Forecasting at Scale (2017)Co-Integration and Error Correction: Representation, Estimation, and Testing (1987)Stock price prediction using LSTM, RNN and CNN-sliding window model (2017)Exponential smoothing: The state of the art (1985)Forecasting methods and applications (1993)Time Series Analysis Forecasting and Control. (1971)Time Series Analysis: Forecasting and Control. (1978)Forecasting principles and practice (2018)Adaptive Graph Convolutional Recurrent Network for Traffic Forecasting (2020)Another look at measures of forecast accuracy (2006)Automatic Time Series Forecasting: The forecast Package for R (2008)Strictly Proper Scoring Rules, Prediction, and Estimation (2007)Forecast evaluation for data scientists: common pitfalls and best practices (2022)Practical Bayesian Optimization of Machine Learning Algorithms (2012)Deep Learning for Time Series Forecasting: Tutorial and Literature Survey (2022)
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References

  • 1998Forecasting with artificial neural networks:4,282 cited
  • 1969The Combination of Forecasts3,438 cited
  • 2019DeepAR: Probabilistic forecasting with autoregressive recurrent networks2,851 cited
  • 2018Statistical and Machine Learning forecasting methods: Concerns and ways forward1,659 cited
  • 200625 years of time series forecasting1,598 cited
  • 2020Recurrent Neural Networks for Time Series Forecasting: Current status and future directions1,429 cited
  • 2019N-BEATS: Neural basis expansion analysis for interpretable time series forecasting1,149 cited
  • 2002A state space framework for automatic forecasting using exponential smoothing methods1,106 cited
  • 2000Out-of-sample tests of forecasting accuracy: an analysis and review1,092 cited
  • 2019The M4 Competition: 100,000 time series and 61 forecasting methods1,068 cited
  • 2022Forecasting: theory and practice1,041 cited
  • 2019A hybrid method of exponential smoothing and recurrent neural networks for time series forecasting791 cited
  • 2022M5 accuracy competition: Results, findings, and conclusions669 cited
  • 2017Conditional Time Series Forecasting with Convolutional Neural Networks558 cited
  • 2000The theta model: a decomposition approach to forecasting

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513 cited
  • 2011Optimal combination forecasts for hierarchical time series471 cited
  • Cited by

    • 2024GA-LSTM: Performance Optimization of LSTM driven Time Series Forecasting25 cited