Optimizing Time-Series forecasting using stacked deep learning framework with enhanced adaptive moment estimation and error correction-Reference-Cited by-同舟云学术

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Optimizing Time-Series forecasting using stacked deep learning framework with enhanced adaptive moment estimation and error correction

Published:2024-09 Issue: Volume:249 Page:123487
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Varshney Ravi Prakash,Sharma Dilip Kumar

Publisher

Elsevier BV

Reference43 articles.

1. Australian Energy Market Operator. (n.d.). National Electricity Market (NEM) data dashboard. Retrieved from https://www.aemo.com.au/energy-systems/electricity/national-electricity-market-nem/data-nem/data-dashboard-nem. Accessed July 10, 2022.

2. Short term forecasting of electricity prices for MISO hubs: Evidence from ARIMA-EGARCH models;Bowden;Energy Economics,2008

3. Time series analysis: Forecasting and control;Box,2015

4. Wind speed forecasting using nonlinear-learning ensemble of deep learning time series prediction and extremal optimization;Chen;Energy conversion and management,2018

5. Natural language processing (almost) from scratch;Collobert;Journal of Machine Learning Research,2011

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