Journal ArticleDOI
Hybrid structures in time series modeling and forecasting: A review
Zahra Hajirahimi,Mehdi Khashei +1 more
TLDR
It can be observed that combined methods are viable and accurate approaches for time series forecasting and also the parallel–series hybrid structure can obtain more accurate and promising results than other those hybrid structures.About:
This article is published in Engineering Applications of Artificial Intelligence.The article was published on 2019-11-01. It has received 110 citations till now. The article focuses on the topics: Time series.read more
Citations
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Journal ArticleDOI
A machine learning forecasting model for COVID-19 pandemic in India.
TL;DR: This work has performed linear regression, Multilayer perceptron and Vector autoregression method for desire on the CO VID-19 Kaggle data to anticipate the epidemiological example of the ailment and pace of COVID-2019 cases in India.
Journal ArticleDOI
Solar Irradiance Forecasting Based on Deep Learning Methodologies and Multi-Site Data
Banalaxmi Brahma,Rajesh Wadhvani +1 more
TL;DR: The results indicate that the bidirectional long short-term memory (LSTM) and attention-based LSTM models can be used for forecasting daily solar irradiance data.
Journal ArticleDOI
Ensemble empirical mode decomposition and long short-term memory neural network for multi-step predictions of time series signals in nuclear power plants
TL;DR: A novel method based on the combined use of Ensemble Empirical Mode Decomposition and Long Short-Term Memory neural network for multi-step ahead time series signal prediction in the energy industry is developed with the aim of improving maintenance planning and minimizing unexpected shutdowns.
Journal ArticleDOI
Current status of hybrid structures in wind forecasting
Mehrnaz Ahmadi,Mehdi Khashei +1 more
TL;DR: Results indicate that the component combination-based category is the most diverse and extensive hybrid approach in the literature, and parallel hybrid models are more popular approaches in comparison with series hybrid models and more used for wind forecasting.
Journal ArticleDOI
Robust empirical wavelet fuzzy cognitive map for time series forecasting
Ruobin Gao,Liang Du,Kum Fai Yuen +2 more
TL;DR: A novel time series forecasting model based on fuzzy cognitive maps and empirical wavelet transformation and a novel learning method based on support vector regression is designed to enhance the robustness of high-order fuzzy Cognitive maps against outliers.
References
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Journal ArticleDOI
Bayesian Model Averaging: A Tutorial
TL;DR: Bayesian model averaging (BMA) provides a coherent mechanism for ac- counting for this model uncertainty and provides improved out-of- sample predictive performance.
Journal ArticleDOI
Time series forecasting using a hybrid ARIMA and neural network model
TL;DR: Experimental results with real data sets indicate that the combined model can be an effective way to improve forecasting accuracy achieved by either of the models used separately.
Journal ArticleDOI
The Combination of Forecasts
J. M. Bates,Clive W. J. Granger +1 more
TL;DR: In this article, two separate sets of forecasts of airline passenger data have been combined to form a composite set of forecasts, and different methods of deriving these weights have been examined.
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Combining forecasts: A review and annotated bibliography
TL;DR: In this article, the authors provide a review and annotated bibliography of that literature, including contributions from the forecasting, psychology, statistics, and management science literatures, providing a guide to the literature for students and researchers and to help researchers locate contributions in specific areas, both theoretical and applied.