Data science wind energy de ding (36 resultados)

Paperback. Condición: Very Good. Book cover shows faint rubbing and one light crease to bottom edge, otherwise looks largely clean, bright, and sharp. One small stain to bottom of textblock. Strong, square binding, pages are clean and bright. Overall a sharp copy with interior in excellent shape.

Paperback. Condición: New. Brand new book, sourced directly from publisher. Dispatch time is 7-8 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

Condición: New.

Condición: As New. Unread book in perfect condition.

Condición: New.

Condición: New.

Condición: New.

Condición: As New. Unread book in perfect condition.

Condición: New. 1st edition NO-PA16APR2015-KAP.

Paperback / softback. Condición: New. New copy - Usually dispatched within 4 working days.

Condición: New.

Paperback. Condición: Brand New. 424 pages. 9.00x6.00x1.00 inches. In Stock.

Taschenbuch. Condición: Neu. Data Science for Wind Energy | Yu Ding | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2020 | Chapman and Hall/CRC | EAN 9780367729097 | Verantwortliche Person für die EU: Taylor and Francis, Taylor & Francis Verlag Gmbh, Kaufingerstr 24, 80331 München, gpsr[at]taylorandfrancis[dot]com | Anbieter: preigu. …

Hardcover. Condición: New. Brand new book, sourced directly from publisher. Dispatch time is 7-8 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

Condición: New.

Condición: As New. Unread book in perfect condition.

Paperback. Condición: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Condición: New.

Condición: New.

Condición: As New. Unread book in perfect condition.

Hardback. Condición: New. New copy - Usually dispatched within 4 working days.

Condición: New.

Hardcover. Condición: new. Hardcover. Data Science for Wind Energy provides an in-depth discussion on how data science methods can improve decision making for wind energy applications, near-ground wind field analysis and forecast, turbine power curve fitting and performance analysis, turbine reliability assessment, and maintenance optimization for wind turbines and wind farms. A broad set of data science methods covered, including time series models, spatio-temporal analysis, kernel regression, decision trees, kNN, splines, Bayesian inference, and importance sampling. More importantly, the data science methods are described in the context of wind energy applications, with specific wind energy examples and case studies. Please also visit the authors book site at FeaturesProvides an integral treatment of data science methods and wind energy applicationsIncludes specific demonstration of particular data science methods and their use in the context of addressing wind energy needsPresents real data, case studies and computer codes from wind energy research and industrial practiceCovers material based on the author's ten plus years of academic research and insights This book shows how data science methods can improve decision making for wind energy applications. A broad set of data science methods will be covered, and the data science methods will be described in the context of wind energy applications, with specific wind energy examples and case studies. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Condición: New.

Condición: New. 2019. 1st Edition. Hardcover. . . . . .

Gebunden. Condición: New. Yu Ding is the Mike and Sugar Barnes Professor of Industrial and Systems Engineering and Professor of Electrical and Computer Engineering at Texas A&ampM University, and a Fellow of the Institute of Industrial &amp Systems Engineers an.

Hardcover. Condición: Brand New. 400 pages. 9.25x6.25x1.00 inches. In Stock.

Condición: New. 2019. 1st Edition. Hardcover. . . . . . Books ship from the US and Ireland.

Hardcover. Condición: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Hardcover. Condición: new. Hardcover. Data Science for Wind Energy provides an in-depth discussion on how data science methods can improve decision making for wind energy applications, near-ground wind field analysis and forecast, turbine power curve fitting and performance analysis, turbine reliability assessment, and maintenance optimization for wind turbines and wind farms. A broad set of data science methods covered, including time series models, spatio-temporal analysis, kernel regression, decision trees, kNN, splines, Bayesian inference, and importance sampling. More importantly, the data science methods are described in the context of wind energy applications, with specific wind energy examples and case studies. Please also visit the authors book site at FeaturesProvides an integral treatment of data science methods and wind energy applicationsIncludes specific demonstration of particular data science methods and their use in the context of addressing wind energy needsPresents real data, case studies and computer codes from wind energy research and industrial practiceCovers material based on the author's ten plus years of academic research and insights This book shows how data science methods can improve decision making for wind energy applications. A broad set of data science methods will be covered, and the data science methods will be described in the context of wind energy applications, with specific wind energy examples and case studies. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…