Applied Data Analysis and Modeling for Energy Engineers and Scientists

Name: Applied Data Analysis and Modeling for Energy Engineers and Scientists
Brand: Springer, Berlin
SKU: 9783031348686
Price: 755.48 RON
Availability: InStock

Autor: T. Agami Reddy, Gregor P. Henze

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Legare: Copertă tare

Editura: Springer, Berlin

Disponibilitate: În depozitul extern

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Now in a thoroughly revised and expanded second edition, this classroom-tested text demonstrates and...

Informații despre carte

Autor

T. Agami Reddy, Gregor P. Henze

Limbă

engleză

Legare

Carte - Copertă tare

Publicat

2023

Pagini

465

EAN

9783031348686

Enbook ID

43360460

Editura

Springer, Berlin

Greutate

1771

Dimensiuni

210 x 279

Descriere completă

Now in a thoroughly revised and expanded second edition, this classroom-tested text demonstrates and illustrates how to apply concepts and methods learned in disparate courses such as mathematical modeling, probability, statistics, experimental design, regression, optimization, parameter estimation, inverse modeling, risk analysis, decision-making, and sustainability assessment methods to energy processes and systems. It provides a formal structure that offers a broad and integrative perspective to enhance knowledge, skills, and confidence to work in applied data analysis and modeling problems. This new edition also reflects recent trends and advances in statistical modeling as applied to energy and building processes and systems. It includes numerous examples from recently published technical papers to nurture and stimulate a more research-focused mindset. How the traditional stochastic data modeling approaches are complemented by data analytic algorithmic models such as machine learning and data mining are also discussed. The important societal issues related to the sustainability of energy systems are presented, and a formal structure is proposed meant to classify the various assessment methods found in the literature. Applied Data Analysis and Modeling for Energy Engineers and Scientists is designed for senior-level undergraduate and graduate instruction in energy engineering and mathematical modeling, for continuing education professional courses, and as a self-study reference book for working professionals. In order for readers to have exposure and proficiency with performing hands-on analysis, the open-source Python and R programming languages have been adopted in the form of Jupyter notebooks and R markdown files, and numerous data sets and sample computer code reflective of real-world problems are available online.

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