Výsledky vyhledávání - "Power Curve Model"
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1
Autoři: Ding, Yu
Témata: Bayesian Additive Regression Trees, SVM Model, Power Curve Model, Wind Speed, GEV Distribution, PACF Plot, Wind Turbine, Binning Method, Local Wind Field, ARMA Model, Wind Field Analysis, Ahead Forecast, Wind Speed Forecast, Power Curve, Wind Farm, Data Science Methods, Test Turbine, Importance Sampling Density, Be, GMRF Model, Computer Simulators, CMC, Power Coefficient, Importance Sampling Method, Posterior Predictive Distribution, Data mining, Alternative and renewable energy sources and technology, Artificial intelligence, Probability and statistics
Popis souboru: application/pdf
Přístupová URL adresa: https://library.oapen.org/handle/20.500.12657/101466
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2
Autoři:
Zdroj: Emitter: International Journal of Engineering Technology, Vol 6, Iss 2 (2018)
Témata: 0209 industrial biotechnology, Wind turbine cost, 0211 other engineering and technologies, Multi-rotor wind turbine, 02 engineering and technology, TA1-2040, Engineering (General). Civil engineering (General), Wind energy, Wind turbine, 7. Clean energy, Power curve model
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3
Autoři: Ding, Yu
Témata: PACF Plot, Binning Method, Ahead Forecast, Bayesian Additive Regression Trees, SVM Model, data mining, Power Curve Model, data analytics, Wind Speed, renewable energy, GEV Distribution, wind turbines, machine learning, Wind Turbine, bayesian methods, data science methods, Local Wind Field, wind energy applications, ARMA Model, turbine reliability assessment, Wind Field Analysis, near-ground wind field analysis, Wind Speed Forecast, Power Curve, Wind Farm, Test Turbine, Importance Sampling Density, Be, GMRF Model, CMC, thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics, thema EDItEUR::U Computing and Information Technology::UN Databases, thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence, thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TQ Environmental science, engineering and technology, thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TH Energy technology and engineering::THV Alternative and renewable energy sources and technology, Computer Simulators, Posterior Predictive Distribution, Power Coefficient, Data Science Methods, Importance Sampling Method
Popis souboru: image/jpeg; application/pdf
Přístupová URL adresa: https://zenodo.org/record/5516528/files/DSWE_Datasets_Description.pdf
https://library.oapen.org/handle/20.500.12657/87420
https://directory.doabooks.org/handle/20.500.12854/133841
https://library.oapen.org/bitstream/20.500.12657/87420/1/9780429956515.pdf
https://www.taylorfrancis.com/books/9780429490972
https://library.oapen.org/handle/20.500.12657/101466 -
4
Autoři: Ding, Yu
Témata: Bayesian Additive Regression Trees, SVM Model, data mining, Power Curve Model, data analytics, Wind Speed, renewable energy, GEV Distribution, wind turbines, PACF Plot, machine learning, Wind Turbine, bayesian methods, Binning Method, data science methods, Local Wind Field, wind energy applications, ARMA Model, turbine reliability assessment, Wind Field Analysis, near-ground wind field analysis, Ahead Forecast, Wind Speed Forecast, Power Curve, Wind Farm, Test Turbine, Importance Sampling Density, Be, GMRF Model
Popis souboru: application/pdf
Relation: OCN: 1103917723
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5
Autoři: Ding, Yu
Témata: Bayesian Additive Regression Trees, SVM Model, data mining, Power Curve Model, data analytics, Wind Speed, renewable energy, GEV Distribution, wind turbines, PACF Plot, machine learning, Wind Turbine, bayesian methods, Binning Method, data science methods, Local Wind Field, wind energy applications, ARMA Model, turbine reliability assessment, Wind Field Analysis, near-ground wind field analysis, Ahead Forecast, Wind Speed Forecast, Power Curve, Wind Farm, Test Turbine, Importance Sampling Density, Be, GMRF Model, thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence
Popis souboru: image/jpeg
Relation: https://library.oapen.org/handle/20.500.12657/87420; https://library.oapen.org/bitstream/20.500.12657/87420/1/9780429956515.pdf
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