Zobrazeno 1 - 10
of 52
pro vyhledávání: '"Guo-Feng Fan"'
Publikováno v:
Financial Innovation, Vol 10, Iss 1, Pp 1-37 (2024)
Abstract The new energy industry is strongly supported by the state, and accurate forecasting of stock price can lead to better understanding of its development. However, factors such as cost and ease of use of new energy, as well as economic situati
Externí odkaz:
https://doaj.org/article/357630bc68a74dd5b06fb7bef2465459
Publikováno v:
Energy Science & Engineering, Vol 11, Iss 7, Pp 2444-2468 (2023)
Abstract With the development of the electric market, electric load forecasting has been increasingly pursued by many scholars. Because the electric load is affected by many factors, it is characterized by volatility and uncertainty, and it cannot be
Externí odkaz:
https://doaj.org/article/b774c21c15804eb3b65dd1445999e818
Publikováno v:
Scientific Reports, Vol 10, Iss 1, Pp 1-17 (2020)
Abstract To detect substation faults for timely repair, this paper proposes a fault detection method that is based on the time series model and the statistical process control method to analyze the regulation and characteristics of the behavior in th
Externí odkaz:
https://doaj.org/article/13fd4eeca3a342eda09a412961502ac0
Publikováno v:
Energies, Vol 12, Iss 5, p 916 (2019)
In this paper, the historical power load data from the National Electricity Market (Australia) is used to analyze the characteristics and regulations of electricity (the average value of every eight hours). Then, considering the inverse of Euclidean
Externí odkaz:
https://doaj.org/article/892751cbf6454488acf80f9d2a3ec695
Autor:
Wei-Chiang Hong, Guo-Feng Fan
Publikováno v:
Energies, Vol 12, Iss 6, p 1093 (2019)
For operational management of power plants, it is desirable to possess more precise short-term load forecasting results to guarantee the power supply and load dispatch. The empirical mode decomposition (EMD) method and the particle swarm optimization
Externí odkaz:
https://doaj.org/article/a17dca1bde484b64bdeb5e51240e4a19
Publikováno v:
Energies, Vol 6, Iss 4, Pp 1887-1901 (2013)
Electric load forecasting is an important issue for a power utility, associated with the management of daily operations such as energy transfer scheduling, unit commitment, and load dispatch. Inspired by strong non-linear learning capability of suppo
Externí odkaz:
https://doaj.org/article/0b7c294e6cc0414b94c0b560e0e544fb
Publikováno v:
Energies, Vol 11, Iss 7, p 1625 (2018)
Along with the high growth rate of economy and fast increasing air pollution, clean energy, such as the natural gas, has played an important role in preventing the environment from discharge of greenhouse gases and harmful substances in China. It is
Externí odkaz:
https://doaj.org/article/40eb0f8b8c85464da558fbbf639b08cc
Publikováno v:
Energies, Vol 10, Iss 11, p 1713 (2017)
Providing accurate load forecasting plays an important role for effective management operations of a power utility. When considering the superiority of support vector regression (SVR) in terms of non-linear optimization, this paper proposes a novel S
Externí odkaz:
https://doaj.org/article/e4c45707861c4a71853cb497ce11e02c
Publikováno v:
Journal of Applied Mathematics, Vol 2014 (2014)
A series of smelting reduction experiments has been carried out with high-phosphorus iron ore of the different bases and heating rates by thermogravimetric analyzer. The derivative thermo gravimetric (DTG) data have been obtained from the experiments
Externí odkaz:
https://doaj.org/article/27d9c985a7be41e48a1c5e269ee7bee7
Publikováno v:
Energies, Vol 9, Iss 3, p 221 (2016)
Electric load forecasting is an important issue for a power utility, associated with the management of daily operations such as energy transfer scheduling, unit commitment, and load dispatch. Inspired by strong non-linear learning capability of suppo
Externí odkaz:
https://doaj.org/article/2c14365a1ae7415faa3b82eff4c0eb77