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A neural network based linear ensemble framework for time series forecasting
16 references·6 citing·23 second hop
A neural network based linear ensemble framework for time series forecasting (2015)A neural network based linear ensemble fr…Chapter 4 Forecast Combinations (2006)Chapter 4 Forecast Combinatio…25 years of time series forecasting (2006)25 years of time series forec…Combination forecasts of output growth in a seven‐country data set (2004)Combination forecasts of outp…Time series forecasting using a hybrid ARIMA and neural network model (2003)Time series forecasting using…Principles of Forecasting (2001)Principles of ForecastingPrinciples of forecasting : a handbook for researchers and practitioners (2001)Principles of forecasting : a…The M3-Competition: results, conclusions and implications (2000)The M3-Competition: results, …Forecasting with artificial neural networks: (1998)Forecasting with artificial n…Combining forecasts: A review and annotated bibliography (1990)Combining forecasts: A review…Combining forecasts: A review and annotated bibliography (1989)Combining forecasts: A review…Improved methods of combining forecasts (1984)Improved methods of combining…Distribution of the Estimators for Autoregressive Time Series with a Unit Root (1979)Distribution of the Estimator…Time Series Analysis: Forecasting and Control. (1978)Time Series Analysis: Forecas…Time Series Analysis: Forecasting and Control (1977)Time Series Analysis: Forecas…Time Series Analysis Forecasting and Control. (1971)Time Series Analysis Forecast…The Combination of Forecasts (1969)The Combination of ForecastsOptimal forecast combination based on PSO-CS approach for daily agricultural future prices forecasting (2022)Optimal forecast combination …DERN: Deep Ensemble Learning Model for Short- and Long-Term Prediction of Baltic Dry Index (2020)DERN: Deep Ensemble Learning …Financial and Non-Stationary Time Series Forecasting using LSTM Recurrent Neural Network for Short and Long Horizon (2019)Financial and Non-Stationary …Comparison of Forecasting India’s Energy Demand Using an MGM, ARIMA Model, MGM-ARIMA Model, and BP Neural Network Model (2018)Comparison of Forecasting Ind…Combining LSTM Network Ensemble via Adaptive Weighting for Improved Time Series Forecasting (2018)Combining LSTM Network Ensemb…A hybrid evolutionary decomposition system for time series forecasting (2015)A hybrid evolutionary decompo…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)A Monetary History of the United States 1867-1960 (1964)Statistical analysis of cointegration vectors (1988)Testing for a Unit Root in Time Series Regression (1988)Bounds testing approaches to the analysis of level relationships (2001)Expert judgment: Some necessary conditions and an example. (1974)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)Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy (2009)Statistical and Machine Learning forecasting methods: Concerns and ways forward (2018)Recurrent Neural Networks for Time Series Forecasting: Current status and future directions (2020)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)Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root (1981)Generalized autoregressive conditional heteroskedasticity (1986)The politics of attention: how government prioritizes problems (2006)Some recent development in a concept of causality (1988)Unit root tests in panel data: asymptotic and finite-sample properties (2002)
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  • 2003Time series forecasting using a hybrid ARIMA and neural network model4,469 cited
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  • 2004Combination forecasts of output growth in a seven‐country data set1,138 cited
  • 2001Principles of forecasting : a handbook for researchers and practitioners

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Cited by

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  • 2020DERN: Deep Ensemble Learning Model for Short- and Long-Term Prediction of Baltic Dry Index58 cited
  • 2022Optimal forecast combination based on PSO-CS approach for daily agricultural future prices forecasting52 cited
  • 2019Financial and Non-Stationary Time Series Forecasting using LSTM Recurrent Neural Network for Short and Long Horizon51 cited
  • 2018Comparison of Forecasting India’s Energy Demand Using an MGM, ARIMA Model, MGM-ARIMA Model, and BP Neural Network Model39 cited