Natural gas consumption forecasting: A discussion on forecasting history and future challenges
J Liu, S Wang, N Wei, X Chen, H Xie, J Wang - Journal of Natural Gas …, 2021 - Elsevier
Natural gas consumption forecasting technology has been researched for 70 years. This
paper reviews the history of natural gas consumption forecasting, and discusses the …
paper reviews the history of natural gas consumption forecasting, and discusses the …
Modeling energy demand—a systematic literature review
PA Verwiebe, S Seim, S Burges, L Schulz… - Energies, 2021 - mdpi.com
In this article, a systematic literature review of 419 articles on energy demand modeling,
published between 2015 and 2020, is presented. This provides researchers with an …
published between 2015 and 2020, is presented. This provides researchers with an …
A short-term load forecasting method using integrated CNN and LSTM network
In this study, a new technique is proposed to forecast short-term electrical load. Load
forecasting is an integral part of power system planning and operation. Precise forecasting …
forecasting is an integral part of power system planning and operation. Precise forecasting …
A deep neural network model for short-term load forecast based on long short-term memory network and convolutional neural network
C Tian, J Ma, C Zhang, P Zhan - Energies, 2018 - mdpi.com
Accurate electrical load forecasting is of great significance to help power companies in
better scheduling and efficient management. Since high levels of uncertainties exist in the …
better scheduling and efficient management. Since high levels of uncertainties exist in the …
Short-term natural gas consumption prediction based on Volterra adaptive filter and improved whale optimization algorithm
W Qiao, Z Yang, Z Kang, Z Pan - Engineering Applications of Artificial …, 2020 - Elsevier
Short-term natural gas consumption prediction is an important indicator of natural gas
pipeline network planning and design, which is of great significance. The purpose of this …
pipeline network planning and design, which is of great significance. The purpose of this …
Genetic algorithm approach to design of multi-layer perceptron for combined cycle power plant electrical power output estimation
In this paper a genetic algorithm (GA) approach to design of multi-layer perceptron (MLP) for
combined cycle power plant power output estimation is presented. Dataset used in this …
combined cycle power plant power output estimation is presented. Dataset used in this …
A novel hybrid prediction model for hourly gas consumption in supply side based on improved whale optimization algorithm and relevance vector machine
W Qiao, K Huang, M Azimi, S Han - IEEE access, 2019 - ieeexplore.ieee.org
Accurate short-term prediction of the natural gas load is of great significance to the operation
and allocation of the pipeline network. Because the short-term natural gas load has obvious …
and allocation of the pipeline network. Because the short-term natural gas load has obvious …
[HTML][HTML] Deep neural network algorithm for estimating maize biomass based on simulated Sentinel 2A vegetation indices and leaf area index
Accurate estimation of biomass is necessary for evaluating crop growth and predicting crop
yield. Biomass is also a key trait in increasing grain yield by crop breeding. The aims of this …
yield. Biomass is also a key trait in increasing grain yield by crop breeding. The aims of this …
Experimental study and numerical modeling of the thermo-hydro-mechanical processes in soil freezing with different frost penetration directions
AH Sweidan, K Niggemann, Y Heider, M Ziegler… - Acta Geotechnica, 2022 - Springer
This research work presents an experimental and numerical study of the coupled thermo-
hydro-mechanical (THM) processes that occur during soil freezing. With focusing on the …
hydro-mechanical (THM) processes that occur during soil freezing. With focusing on the …
Deep learning based short term load forecasting with hybrid feature selection
SS Subbiah, J Chinnappan - Electric Power Systems Research, 2022 - Elsevier
The reliable and an economic operation of the power system rely on an accurate prediction
of short term load. In this paper, a deep learning based Long Short Term Memory (LSTM) …
of short term load. In this paper, a deep learning based Long Short Term Memory (LSTM) …