粗鲁性质
发表于 2025-3-28 17:01:00
http://reply.papertrans.cn/27/2628/262706/262706_41.png
和蔼
发表于 2025-3-28 20:13:08
An Approach for Erosion and Power Loss Prediction of Wind Turbines Using Big Data Analytics,In this paper, we propose the Wind Turbine Erosion Predictor (WTEP) System that uses big data analytics to handle the data volume, variety, and veracity and estimate the turbines erosion rate, in addition to the total power loss. WTEP proposes an optimized flexible multiple regression technique. Exp
抗生素
发表于 2025-3-28 23:14:24
http://reply.papertrans.cn/27/2628/262706/262706_43.png
invulnerable
发表于 2025-3-29 04:06:48
,Improving Time-Series Rule Matching Performance for Detecting Energy Consumption Patterns,Euclidean distance to search candidate rules occurrences. However this distance is not adapted for energy consumption data because occurrences of patterns should have different duration. We propose to use more “elastic” distance measures. In this paper we will compare the detection performance of pr
ostrish
发表于 2025-3-29 09:24:04
Probabilistic Wind Power Forecasting by Using Quantile Regression Analysis,esents a probabilistic wind power forecasting method based on local quantile regression with Gaussian distribution. The method is applied to obtain probabilistic wind power forecasts, within the course of the Wind Power Monitoring and Forecast Center for Turkey (RİTM) project, which has been realize
无表情
发表于 2025-3-29 12:32:16
http://reply.papertrans.cn/27/2628/262706/262706_46.png
Parameter
发表于 2025-3-29 18:13:29
http://reply.papertrans.cn/27/2628/262706/262706_47.png
解脱
发表于 2025-3-29 20:05:54
I. Gohberg,M. A. Kaashoek,S. Goldbergire the resulting energy consumption, self-consumption, and self-sufficiency. The results show an increase of individual self-consumption between 17% and 348% and self-sufficiency between 18% and 72%. This results in an additional monetary benefit for the occupants based on the transition proposals
adjacent
发表于 2025-3-30 03:36:27
I. Gohberg,M. A. Kaashoek,S. GoldbergEuclidean distance to search candidate rules occurrences. However this distance is not adapted for energy consumption data because occurrences of patterns should have different duration. We propose to use more “elastic” distance measures. In this paper we will compare the detection performance of pr
Cocker
发表于 2025-3-30 04:40:49
I. Gohberg,M. A. Kaashoek,S. Goldbergesents a probabilistic wind power forecasting method based on local quantile regression with Gaussian distribution. The method is applied to obtain probabilistic wind power forecasts, within the course of the Wind Power Monitoring and Forecast Center for Turkey (RİTM) project, which has been realize