首页|Studies from Center for Energy Research Have Provided New Data on Machine Learning (Comparative Assessment of Physical and Machine Learning Models for Wind Power Estimation: a Case Study for Hungary)
Studies from Center for Energy Research Have Provided New Data on Machine Learning (Comparative Assessment of Physical and Machine Learning Models for Wind Power Estimation: a Case Study for Hungary)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is the subject of a report. According to news reporting from Budapest, Hungary, by NewsRx journalists, research stated, “In the context of the planned mid-term development of wind power plants in Hungary, the authors evaluated the applicability of a physical-based model and several machine-learning models for wind power production estimation and wind resource availability assessments based on wind speed time series retrieved from climate reanalysis. While the physical-based model relies on a national wind power plant database and follows a bottom -up approach transforming wind speed time series into aggregate power output by using type-specific power curves, the machine learning models estimate the aggregate wind power production directly from climate data.”
BudapestHungaryEuropeCyborgsEmerging TechnologiesMachine LearningCenter for Energy Research
NETL
NSTL
