SZodixStudyAcademic Library
ShelvesOpen access
Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated
Strategies for time series forecasting with generalized regression neural networks
15 references·3 citing·35 second hop
Strategies for time series forecasting with generalized regression neural networks (2021)Strategies for time series forecasting wi…The M4 Competition: 100,000 time series and 61 forecasting methods (2019)The M4 Competition: 100,000 t…FFORMA: Feature-based forecast model averaging (2019)FFORMA: Feature-based forecas…Toward Automatic Time-Series Forecasting Using Neural Networks (2012)Toward Automatic Time-Series …A review and comparison of strategies for multi-step ahead time series forecasting based on the NN5 forecasting competition (2012)A review and comparison of st…Advances in forecasting with neural networks? Empirical evidence from the NN3 competition on time series prediction (2011)Advances in forecasting with …An Empirical Comparison of Machine Learning Models for Time Series Forecasting (2010)An Empirical Comparison of Ma…Time series analysis forecasting and control (2009)Time series analysis forecast…Trend Time–Series Modeling and Forecasting With Neural Networks (2008)Trend Time–Series Modeling an…Automatic Time Series Forecasting: The forecast Package for R (2008)Automatic Time Series Forecas…Exponential smoothing: The state of the art—Part II (2006)Exponential smoothing: The st…Another look at measures of forecast accuracy (2006)Another look at measures of f…Financial time series forecasting using support vector machines (2003)Financial time series forecas…The M3-Competition: results, conclusions and implications (2000)The M3-Competition: results, …Out-of-sample tests of forecasting accuracy: an analysis and review (2000)Out-of-sample tests of foreca…Testing the null hypothesis of stationarity against the alternative of a unit root (1992)Testing the null hypothesis o…Analyzing the Dynamics of Customer Behavior: A New Perspective on Personalized Marketing through Counterfactual Analysis (2024)Analyzing the Dynamics of Cus…Effective machine learning model combination based on selective ensemble strategy for time series forecasting (2022)Effective machine learning mo…A novel multivariate grey model for forecasting periodic oscillation time series (2022)A novel multivariate grey mod…Distribution of the Estimators for Autoregressive Time Series with a Unit Root (1979)Distribution of the Estimators for Autoregressive Time Series With a Unit Root (1979)Testing for a Unit Root in Time Series Regression (1988)A Comparative Study of Unit Root Tests with Panel Data and a New Simple Test (1999)Unit root tests for panel data (2001)Modelling Asymmetric Cointegration and Dynamic Multipliers in a Nonlinear ARDL Framework (2014)Forecasting with artificial neural networks: (1998)Predicting direction of stock price index movement using artificial neural networks and support vector machines: The sample of the Istanbul Stock Exchange (2010)Predicting stock and stock price index movement using Trend Deterministic Data Preparation and machine learning techniques (2014)Stock market's price movement prediction with LSTM neural networks (2017)Time Series Analysis: Forecasting and Control (1977)Time Series Analysis: Forecasting and Control (1977)Forecasting methods and applications (1993)Machine Learning Strategies for Time Series Forecasting (2013)The M4 Competition: Results, findings, conclusion and way forward (2018)The accuracy of extrapolation (time series) methods: Results of a forecasting competition (1982)Error measures for generalizing about forecasting methods: Empirical comparisons (1992)Forecasting: theory and practice (2022)Combining forecasts: A review and annotated bibliography (1989)25 years of time series forecasting (2006)Forecasting Sales by Exponentially Weighted Moving Averages (1960)Forecasting seasonals and trends by exponentially weighted moving averages (2004)A hybrid method of exponential smoothing and recurrent neural networks for time series forecasting (2019)Artificial intelligence applications in supply chain management (2021)Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root (1981)DeepAR: Probabilistic forecasting with autoregressive recurrent networks (2019)Time Series Analysis Forecasting and Control. (1971)Strictly Proper Scoring Rules, Prediction, and Estimation (2007)Forecast evaluation for data scientists: common pitfalls and best practices (2022)M5 accuracy competition: Results, findings, and conclusions (2022)Statistical and Machine Learning forecasting methods: Concerns and ways forward (2018)Recurrent Neural Networks for Time Series Forecasting: Current status and future directions (2020)The predictive power of online chatter (2005)Quantile regression for dynamic panel data with fixed effects (2011)Tourism demand forecasting: A deep learning approach (2019)
this work references cited by second hop

References

  • 1992Testing the null hypothesis of stationarity against the alternative of a unit root12,634 cited
  • 2006Another look at measures of forecast accuracy5,736 cited
  • 2008Automatic Time Series Forecasting: The forecast Package for R3,538 cited
  • 2009Time series analysis forecasting and control2,585 cited
  • 2003Financial time series forecasting using support vector machines1,734 cited
  • 2000The M3-Competition: results, conclusions and implications1,700 cited
  • 2000Out-of-sample tests of forecasting accuracy: an analysis and review1,014 cited
  • 2019The M4 Competition: 100,000 time series and 61 forecasting methods990 cited
  • 2006Exponential smoothing: The state of the art—Part II953 cited
  • 2010An Empirical Comparison of Machine Learning Models for Time Series Forecasting793 cited
  • 2012A review and comparison of strategies for multi-step ahead time series forecasting based on the NN5 forecasting competition745 cited
  • 2019FFORMA: Feature-based forecast model averaging313 cited
  • 2011Advances in forecasting with neural networks? Empirical evidence from the NN3 competition on time series prediction272 cited
  • 2012Toward Automatic Time-Series Forecasting Using Neural Networks182 cited
  • 2008

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

Trend Time–Series Modeling and Forecasting With Neural Networks
149 cited

Cited by

  • 2022Effective machine learning model combination based on selective ensemble strategy for time series forecasting69 cited
  • 2022A novel multivariate grey model for forecasting periodic oscillation time series51 cited
  • 2024Analyzing the Dynamics of Customer Behavior: A New Perspective on Personalized Marketing through Counterfactual Analysis11 cited