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Energy price prediction using data-driven models: A decade review · Study

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ArticleEnergy price prediction using data-driven models: A decade review

Hongfang Lü2020

Article2020

Energy price prediction using data-driven models: A decade review

Hongfang Lü · Xin Ma · Minda Ma · Senlin Zhu

91 citations·0/0 files stored·Computer Science Review

No readable copy stored yet — this record is metadata only.

Stock Market Forecasting Methods Forecasting Techniques and Applications Energy Load and Power Forecasting

Abstract

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Citations in this library

Stored only when both papers are in the corpus — 91 citations exist upstream.

References

20132013 IEEE International Conference on Big Data 1995THE GARCH OPTION PRICING MODEL 1982Industrial and business forecasting methods : a practical guide to exponential smoothing and curve fitting 2017A deep learning ensemble approach for crude oil price forecasting 2012Carbon price forecasting with a novel hybrid ARIMA and least squares support vector machines methodology 2012Real-Time Forecasts of the Real Price of Oil 2017Forecasting carbon price using empirical mode decomposition and evolutionary least squares support vector regression 2018Text-based crude oil price forecasting: A deep learning approach

Cited by

2021Historical carbon abatement in the commercial building operation: China versus the US 2024A secondary decomposition-ensemble framework for interval carbon price forecasting 2023A hybrid machine learning model for predicting crater width formed by explosions of natural gas pipelines

Details

Year2020

Typearticle

Published2020-12-25

VenueComputer Science Review

ISSN-L1574-0137

Languageen

Citations91

Files0 public / 0

ShelfStock Market Forecasting Methods

Identifiers

doi10.1016/j.cosrev.2020.100356

openalex_workW3114493467

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