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A Model Ranking Based Selective Ensemble Approach for Time Series Forecasting
15 references·0 citing·35 second hop
A Model Ranking Based Selective Ensemble Approach for Time Series Forecasting (2015)A Model Ranking Based Selective Ensemble …Optimal sub-models selection algorithm for combination forecasting model (2014)Optimal sub-models selection …Performance evaluation of weights selection schemes for linear combination of multiple forecasts (2012)Performance evaluation of wei…A novel neural network ensemble architecture for time series forecasting (2011)A novel neural network ensemb…Meta-learning for time series forecasting and forecast combination (2010)Meta-learning for time series…Improving artificial neural networks’ performance in seasonal time series forecasting (2008)Improving artificial neural n…Comparison of direct and iterative artificial neural network forecast approaches in multi-periodic time series forecasting (2008)Comparison of direct and iter…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…Model combination in neural-based forecasting (2005)Model combination in neural-b…Time series forecasting using a hybrid ARIMA and neural network model (2003)Time series forecasting using…Combined forecasts from linear and nonlinear time series models (2002)Combined forecasts from linea…Review of guidelines for the use of combined forecasts (2000)Review of guidelines for the …Improved methods of combining forecasts (1984)Improved methods of combining…The Combination of Forecasts (1983)The Combination of ForecastsA Bayesian Approach to the Linear Combination of Forecasts (1975)A Bayesian Approach to the Li…Combining forecasts: A review and annotated bibliography (1989)Combining forecasts: A review and annotated bibliography (1990)The M3-Competition: results, conclusions and implications (2000)The M4 Competition: 100,000 time series and 61 forecasting methods (2019)Forecast combinations: An over 50-year review (2022)Forecasting: theory and practice (2022)The Combination of Forecasts (1969)Trends and random walks in macroeconmic time series (1982)Forecasting, Structural Time Series Models and the Kalman Filter (1990)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)Book Review: Time Series Analysis: Forecasting and Control (1977)Time Series Analysis: Forecasting and Control. (1978)On the use of cross-validation for time series predictor evaluation (2012)A survey on forecasting of time series data (2016)Time-series forecasting of seasonal items sales using machine learning – A comparative analysis (2022)Introduction to Grey system theory (1989)Forecasting with artificial neural networks: (1998)Using artificial neural network models in stock market index prediction (2011)Statistical and Machine Learning forecasting methods: Concerns and ways forward (2018)Forecasting methods and applications (1993)A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting (1997)Evaluation of statistical and machine learning models for time series prediction: Identifying the state-of-the-art and the best conditions for the use of each model (2019)An optimized model using LSTM network for demand forecasting (2020)Co-Integration and Error Correction: Representation, Estimation, and Testing (1987)Judgmental forecasting: A review of progress over the last 25years (2006)Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Recurrent Neural Networks for Time Series Forecasting: Current status and future directions (2020)Prediction with a Generalized Cost of Error Function (1969)The Prediction Performance of the FRB-MIT-PENN Model of the U.S. Economy (1972)Forecasting Output and Inflation: The Role of Asset Prices (2003)Chapter 4 Forecast Combinations (2006)Forecasting at Scale (2017)Stock price prediction using LSTM, RNN and CNN-sliding window model (2017)8 Forecast evaluation and combination (1996)
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References

  • 2003Time series forecasting using a hybrid ARIMA and neural network model4,583 cited
  • 200625 years of time series forecasting1,598 cited
  • 1984Improved methods of combining forecasts1,152 cited
  • 1983The Combination of Forecasts390 cited
  • 2008Improving artificial neural networks’ performance in seasonal time series forecasting281 cited
  • 2010Meta-learning for time series forecasting and forecast combination244 cited
  • 2007Simple robust averages of forecasts: Some empirical results242 cited
  • 2000Review of guidelines for the use of combined forecasts241 cited
  • 2008Comparison of direct and iterative artificial neural network forecast approaches in multi-periodic time series forecasting238 cited
  • 2002Combined forecasts from linear and nonlinear time series models206 cited
  • 1975A Bayesian Approach to the Linear Combination of Forecasts185 cited
  • 2011A novel neural network ensemble architecture for time series forecasting73 cited
  • 2012Performance evaluation of weights selection schemes for linear combination of multiple forecasts64 cited
  • 2005Model combination in neural-based forecasting52 cited
  • 2014Optimal sub-models selection algorithm for combination forecasting model

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