Applied Data Analysis and Modeling for Energy Engineers and Scientists

Applied Data Analysis and Modeling for Energy Engineers and Scientists fills an identified gap in engineering and science education and practice for both students and practitioners. It demonstrates how to apply concepts and methods learned in disparate courses such as mathematical modeling, probabil...

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書誌詳細
第一著者: Reddy, T. Agami
フォーマット: Livre numérique
言語:Anglais
出版事項: New York, NY : Springer US : Imprint: Springer [20..].
Cham : Springer Nature
版:1st ed. 2011.
オンライン・アクセス:Accès sur la plateforme de l'éditeur
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注記: Archives Springer e-books (Licence nationale)
Archives Springer e-books (Licence nationale)
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Edition sous un autre format:• Applied Data Analysis and Modeling for Energy Engineers and Scientists, Texte imprimé, 9781441996121
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245 1 0 |a Applied Data Analysis and Modeling for Energy Engineers and Scientists   |c by T. Agami Reddy. 
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505 1 |a Models, data analysis and decision making Probability concepts and probability distributions Data collection and preliminary data analysis Making statistical inferences from samples Estimation of linear model parameters using least squares Designed experiments and analysis of non-intrusive data Time series models Topics in optimization, parameter estimation and clustering methods Inverse problems and illustrative examples Decision analysis and risk modeling 
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506 |a Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 
520 |a Applied Data Analysis and Modeling for Energy Engineers and Scientists fills an identified gap in engineering and science education and practice for both students and practitioners. It demonstrates how to apply concepts and methods learned in disparate courses such as mathematical modeling, probability,statistics, experimental design, regression, model building, optimization, risk analysis and decision-making to actual engineering processes and systems. The text provides a formal structure that offers a basic, broad and unified perspective,while imparting the knowledge, skills and confidence to work in data analysis and modeling. This volume uses numerous solved examples, published case studies from the author s own research, and well-conceived problems in order to enhance comprehension levels among readers and their understanding of the processes along with the tools. Applied Data Analysis and Modeling for Energy Engineers and Scientists is an ideal volume for researchers, practitioners, and senior level or graduate students working in energy engineering, mathematical modeling and other related areas.   
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