Machine learning in energy economics and finance: A review

Energy Economics, Journal Year: 2019, Volume and Issue: 81, P. 709 - 727

Published: May 21, 2019

Language: Английский

---

Forecasting methods in energy planning models

Renewable and Sustainable Energy Reviews, Journal Year: 2018, Volume and Issue: 88, P. 297 - 325

Published: March 16, 2018

Language: Английский

---

Conventional models and artificial intelligence-based models for energy consumption forecasting: A review

Journal of Petroleum Science and Engineering, Journal Year: 2019, Volume and Issue: 181, P. 106187 - 106187

Published: June 20, 2019

Language: Английский

---

Day-ahead natural gas demand forecasting based on the combination of wavelet transform and ANFIS/genetic algorithm/neural network model

Energy, Journal Year: 2016, Volume and Issue: 118, P. 231 - 245

Published: Dec. 20, 2016

Language: Английский

---

Intelligent techniques for forecasting electricity consumption of buildings

Energy, Journal Year: 2018, Volume and Issue: 157, P. 886 - 893

Published: May 24, 2018

Language: Английский

---

Short-term natural gas consumption prediction based on Volterra adaptive filter and improved whale optimization algorithm

Engineering Applications of Artificial Intelligence, Journal Year: 2019, Volume and Issue: 87, P. 103323 - 103323

Published: Nov. 11, 2019

Language: Английский

---

Forecasting energy demand in China and India: Using single-linear, hybrid-linear, and non-linear time series forecast techniques

Energy, Journal Year: 2018, Volume and Issue: 161, P. 821 - 831

Published: July 26, 2018

Language: Английский

---

A comparative assessment of SARIMA, LSTM RNN and Fb Prophet models to forecast total and peak monthly energy demand for India

Energy Policy, Journal Year: 2022, Volume and Issue: 168, P. 113097 - 113097

Published: June 24, 2022

Language: Английский

---

Short-term electric vehicle charging demand prediction: A deep learning approach

Applied Energy, Journal Year: 2023, Volume and Issue: 340, P. 121032 - 121032

Published: April 6, 2023

Language: Английский

---

Natural gas consumption forecasting using a novel two-stage model based on improved sparrow search algorithm

Journal of Pipeline Science and Engineering, Journal Year: 2024, Volume and Issue: 5(1), P. 100220 - 100220

Published: Aug. 23, 2024

The foundation of natural gas intelligent scheduling is the accurate prediction consumption (NGC). However, because its volatility, this brings difficulties and challenges in accurately predicting NGC. To address problem, an improved model developed combining sparrow search algorithm (ISSA), long short-term memory (LSTM), wavelet transform (WT). First, performance ISSA tested. Second, NGC divided into several high- low-frequency components applying different layers Coilfets', Fejer-Korovkins', Symletss', Haars', Discretes' orders. In addition, LSTM applied to forecast decomposed view one- multi-step, hyper-parameters are optimized by ISSA. At last, final results reconstructed. research indicate that: (1) Comparing other machine algorithms (e.g. fuzzy neural network), convergence speed stability stronger standard deviation mean; (2) better than that forecasting models; (3) single-step superior two-, three-, four- step; (4) computational load proposed highest compared models, accuracy still excellent on extended time series.

Language: Английский

---