A novel short-term load forecasting approach using Adaptive Neuro-Fuzzy Inference System
E Akarslan, FO Hocaoglu - … Grids and Cities Congress and Fair …, 2018 - ieeexplore.ieee.org
By developments on smart grid technologies, the management of the grid issue get more
importance. Load forecasting is one of the most important topics for managing the grid. In …
importance. Load forecasting is one of the most important topics for managing the grid. In …
[PDF][PDF] Multiple linear regression for technical outlook in telecom stock price
P Boonkrong, N Arjrith… - Proceedings of RSU …, 2020 - researchgate.net
In this paper, a multiple linear regression is employed as a technical tool to analyze the
relationship among gold price, Dow Jones industrial average, oil price and the trading …
relationship among gold price, Dow Jones industrial average, oil price and the trading …
Electric energy demand forecasting in an oil production company using artificial neural networks
A Manobanda, P Otero, N Granda - Latest Advances in Electrical …, 2022 - Springer
Electric energy demand forecasting is vital for the correct and efficient operation of any
industry, especially for those ones that need to purchase energy. Activities such as …
industry, especially for those ones that need to purchase energy. Activities such as …
Power Cost Optimization Using Data Analytics-Based Load Forecasting in Upstream O&G Operations
JT Hughes, S Silvia, W Ahmad - SPE Middle East Oil and Gas Show …, 2017 - onepetro.org
Oilfield power demand is extremely dynamic in both time and space, and a lack of accurate
forecasting causes increased cost for electric utilities to extend their grids to the field. It also …
forecasting causes increased cost for electric utilities to extend their grids to the field. It also …