Cargando…

Supervised machine learning in wind forecasting and ramp event prediction

Detalles Bibliográficos
Autores principales:	Dhiman, Harsh S, Deb, Dipankar, Balas, Valentina Emilia
Lenguaje:	eng
Publicado:	Elsevier Science & Technology 2020
Materias:	Computing and Computers
Acceso en línea:	http://cds.cern.ch/record/2716602

Ejemplares similares

Supervised machine learning with Python: develop rich Python coding practices while exploring supervised machine learning
por: Smith, Taylor
Publicado: (2019)

Machine learning: a theoretical approach
por: Natarajan, Balas K
Publicado: (2014)

Semi-supervised and unsupervised machine learning: novel strategies
por: Albalate, Amparo, et al.
Publicado: (2011)

Decision and control in hybrid wind farms
por: S Dhiman, Harsh, et al.
Publicado: (2019)

Telemedicine technologies: big data, deep learning, robotics, mobile and remote applications for global healthcare
por: Hemanth, D Jude, et al.
Publicado: (2019)

Machine learning with Go quick start guide: hands-on techniques for building supervised and unsupervised machine learning workflows
por: Bironneau, Michael, et al.
Publicado: (2019)

Applied supervised learning with R: use machine learning libraries of R to build models that solve business problems and predict future trends
por: Ramasubramanian, Karthik, et al.
Publicado: (2019)

Applied supervised learning with Python: use scikit-learn to build predictive models from real-world datasets and prepare yourself for the future of machine learning
por: Johnston, Benjamin, et al.
Publicado: (2019)

Statistics for machine learning: build supervised, unsupervised, and reinforcement learning models using both Python and R
por: Dangeti, Pratap
Publicado: (2017)

Supervised learning with quantum computers
por: Schuld, Maria, et al.
Publicado: (2018)

Nature inspired optimization techniques for image processing applications
por: Hemanth, Jude, et al.
Publicado: (2018)

Supervised and unsupervised learning for data science
por: Berry, Michael W, et al.
Publicado: (2020)

Stability and stabilization of linear and fuzzy time-delay systems: a linear matrix inequality approach
por: Dey, Rajeeb, et al.
Publicado: (2017)

Advances in computing applications
por: Chakrabarti, Amlan, et al.
Publicado: (2017)

Real-time data analytics for large scale sensor data
por: Das, Himansu, et al.
Publicado: (2019)

Intelligent data analysis for biomedical applications: challenges and solutions
por: Hemanth, D Jude, et al.
Publicado: (2019)

The path to predictive analytics and machine learning
por: Doherty, Conor
Publicado: (2017)

Threat forecasting: leveraging big data for predictive analysis
por: Pirc, John, et al.
Publicado: (2016)

Machine learning algorithms for datasets popularity prediction
por: Kancys, Kipras
Publicado: (2016)

Python machine learning: unlock deeper insights into machine learning with this vital guide to cutting-edge predictive analytics
por: Raschka, Sebastian, et al.
Publicado: (2015)

Machine learning in Python: essential techniques for predictive analysis
por: Bowles, Michael
Publicado: (2015)

Large scale machine learning with Python: learn to build powerful machine learning models quickly and deploy large-scale predictive applications
por: Sjardin, Bastiaan, et al.
Publicado: (2016)

Go machine learning projects: eight projects demonstrating end-to-end machine learning and predictive analytics applications in Go
por: Chew, Xuanyi
Publicado: (2018)

Effective Amazon machine learning: machine learning in the Cloud
por: Perrier, Alexis
Publicado: (2017)

Machine learning with Spark and Python: essential techniques for predictive analytics
por: Bowles, Michael
Publicado: (2019)

Conformal prediction for reliable machine learning: theory, adaptations and applications
por: Balasubramanian, Vineeth, et al.
Publicado: (2014)

Practical time series analysis: prediction with statistics and machine learning
por: Nielson, Aileen
Publicado: (2019)

Cybernetics and forecasting techniques
por: Ivakhnenko, A G, et al.
Publicado: (1967)

Forecasting Oracle Performance
por: Shallahamer, Craig
Publicado: (2007)

Machine learning
por: Inge, Roger, et al.
Publicado: (2017)

Machine Learning
por: Mitchell, Tom Michael
Publicado: (1997)

Mastering machine learning with scikit-learn: learn to implement and evaluate machine learning solutions with scikit-learn
por: Hackeling, Gavin
Publicado: (2017)

Python machine learning: machine learning and deep learning with Python, scikit-learn, and TensorFlow
por: Raschka, Sebastian, et al.
Publicado: (2017)

SolarWinds Orion network performance monitor
por: Dissmeyer, Joe
Publicado: (2013)

Supervised descriptive pattern mining
por: Ventura, Sebastián, et al.
Publicado: (2018)

Machine learning with R cookbook: analyze data and build predictive models
por: Bhatia, AshishSingh, et al.
Publicado: (2017)

Mastering predictive analytics with R: machine learning techniques for advanced models
por: Miller, James D, et al.
Publicado: (2017)

Mastering machine learning with R: advanced prediction, algorithms, and learning methods with R 3.x
por: Lesmeister, Cory
Publicado: (2017)

Machine learning algorithms: popular algorithms for data science and machine learning
por: Bonaccorso, Giuseppe
Publicado: (2018)

Agile machine learning: effective machine learning inspired by the agile manifesto
por: Carter, Eric, et al.
Publicado: (2019)

Cannot write session to /tmp/vufind_sessions/sess_hg5rg9lv4rcgp5mu3dn47hcn7j