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 …

Application of forecasting strategies and techniques to natural gas consumption: A comprehensive review and comparative study

N Tian, B Shao, G Bian, H Zeng, X Li, W Zhao - Engineering Applications of …, 2024 - Elsevier
Accurate forecasting of natural gas consumption (NGC) plays an important role in energy
supply, energy trading, economic effects and environmental sustainability. NGC forecasts …

Natural gas consumption forecast with MARS and CMARS models for residential users

A Özmen, Y Yılmaz, GW Weber - Energy Economics, 2018 - Elsevier
Prediction natural gas consumption is indispensable for efficient system operation and
required for planning decisions at natural gas Local Distribution Companies (LDCs) …

Forecasting petroleum products consumption in Cameroon's household sector using a sequential GMC (1, n) model optimized by genetic algorithms

FE Sapnken, KA Ahmat, M Boukar, SLB Nyobe… - Heliyon, 2022 - cell.com
Forecasting energy consumption is a major concern for policymakers, oil industry
companies, and many other associated businesses. Though there exist many forecasting …

Forecasting day-ahead natural gas demand in Denmark

OA Karabiber, G Xydis - Journal of Natural Gas Science and Engineering, 2020 - Elsevier
Natural gas demand forecasting is important for all players in the natural gas market. This
work compares four possible day ahead natural gas consumption forecasting models in …

Forecasting natural gas consumption of China using a novel grey model

C Zheng, WZ Wu, J Jiang, Q Li - Complexity, 2020 - Wiley Online Library
As is known, natural gas consumption has been acted as an extremely important role in
energy market of China, and this paper is to present a novel grey model which is based on …

[HTML][HTML] A sigmoid regression and artificial neural network models for day-ahead natural gas usage forecasting

J Ravnik, J Jovanovac, A Trupej, N Vištica… - Cleaner and …, 2021 - Elsevier
Reliable and accurate day-ahead forecasting of natural gas consumption is vital for the
operation of the Energy sector. Three different forecasting models are developed in this …

Sparse regression modeling for short-and long‐term natural gas demand prediction

A Özmen - Annals of Operations Research, 2023 - Springer
The multivariate adaptive regression splines (MARS) model is a flexible non-parametric
sparse regression algorithm and provides an excellent promise to data fitting through …

A method for natural gas forecasting and preliminary allocation based on unique standard natural gas consumption profiles

J Ravnik, M Hriberšek - Energy, 2019 - Elsevier
The paper reports on the development of unique standard gas consumption profiles for the
end gas consumers and the preparation of a method for the implementation of the …

A Piecewise Linear Regression Model Ensemble for Large-Scale Curve Fitting

S Moreno-Carbonell, EF Sánchez-Úbeda - Algorithms, 2024 - mdpi.com
The Linear Hinges Model (LHM) is an efficient approach to flexible and robust one-
dimensional curve fitting under stringent high-noise conditions. However, it was initially …