A novel hybrid model to forecast seasonal and chaotic time series

Author:

Abbasimehr HosseinORCID,Behboodi AmirrezaORCID,Bahrini AramORCID

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference59 articles.

1. A novel time series clustering method with fine-tuned support vector regression for customer behavior analysis;Abbasimehr;Expert Systems with Applications,2022

2. Prediction of COVID-19 confirmed cases combining deep learning methods and Bayesian optimization;Abbasimehr;Chaos, Solitons & Fractals,2021

3. Improving time series forecasting using LSTM and attention models;Abbasimehr;Journal of Ambient Intelligence and Humanized Computing,2022

4. A novel approach based on combining deep learning models with statistical methods for COVID-19 time series forecasting;Abbasimehr;Neural Computing and Applications,2022

5. A novel XGBoost-based featurization approach to forecast renewable energy consumption with deep learning models;Abbasimehr;Sustainable Computing: Informatics and Systems,2023

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