Conventional models and artificial intelligence-based models for energy consumption forecasting: A review
Conventional models and artificial intelligence (AI)-based models have been widely applied
for energy consumption forecasting over the past decades. This paper reviews conventional …
for energy consumption forecasting over the past decades. This paper reviews conventional …
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 …
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 …
A new hybrid algorithm model for prediction of internal corrosion rate of multiphase pipeline
S Peng, Z Zhang, E Liu, W Liu, W Qiao - Journal of Natural Gas Science …, 2021 - Elsevier
Pipeline plays an important role in the oil and gas transportation industry. In recent years,
more and more pipeline damages and breakdowns are caused by corrosion, which hurts the …
more and more pipeline damages and breakdowns are caused by corrosion, which hurts the …
A novel fractional structural adaptive grey Chebyshev polynomial Bernoulli model and its application in forecasting renewable energy production of China
Accurate mid-to-long term China's renewable energy forecasting is becoming more and
more important for integrating renewable energy systems with smart grid and energy …
more important for integrating renewable energy systems with smart grid and energy …
Daily natural gas consumption forecasting via the application of a novel hybrid model
In daily natural gas consumption forecasting, the accuracy of forecasting models is
vulnerably affected by the noise data in historical time series. Singular spectrum analysis …
vulnerably affected by the noise data in historical time series. Singular spectrum analysis …
A MFO-based conformable fractional nonhomogeneous grey Bernoulli model for natural gas production and consumption forecasting
C Zheng, WZ Wu, W Xie, Q Li - Applied Soft Computing, 2021 - Elsevier
The demand for natural gas is expected to continuously increase due to its significant role in
the transition towards a low-carbon energy structure. Based on the nonhomogeneous grey …
the transition towards a low-carbon energy structure. Based on the nonhomogeneous grey …
A knowledge-enhanced graph-based temporal-spatial network for natural gas consumption prediction
The accurate prediction of natural gas consumption plays a central role in long-distance
pipeline system production and transportation planning, and it becomes even more …
pipeline system production and transportation planning, and it becomes even more …
A review on short‐term load forecasting models for micro‐grid application
VY Kondaiah, B Saravanan… - The Journal of …, 2022 - Wiley Online Library
Load forecasting (LF), particularly short‐term load forecasting (STLF), plays a vital role
throughout the operation of the conventional power system. The precise modelling and …
throughout the operation of the conventional power system. The precise modelling and …
Forecasting the daily natural gas consumption with an accurate white-box model
Compared with artificial intelligence black-box models, statistical white-box models have
less application and lower accuracy in forecasting daily natural gas consumption that …
less application and lower accuracy in forecasting daily natural gas consumption that …