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Applied Data Analysis and Modeling for Energy Engineers and Scientists

  • Book
  • © 2011

Overview

Authors:
  1. T. Agami Reddy

    1. The Design Sch. & Sch. of Sust, Arizona State University, Tempe, USA

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  • Offers descriptions of numerous data analysis techniques, including but not limited to exploratory data analysis, estimation and model building, inferential methods and data compaction
  • Utilizes an effective combination of classical methods with the more recently developed machine learning and automated tools which have become more prevalent in recent years
  • Discusses data analysis and modeling issues that are relevant to thermal energy systems, building energy systems, renewable energy systems, energy efficiency, indoor air quality, and environmental engineering
  • Includes supplementary material: sn.pub/extras

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Table of contents (13 chapters)

  1. Front Matter

    Pages i-xxi
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  2. Mathematical Models and Data Analysis

    • T. Agami Reddy
    Pages 1-25

  3. Probability Concepts and Probability Distributions

    • T. Agami Reddy
    Pages 27-60

  4. Data Collection and Preliminary Data Analysis

    • T. Agami Reddy
    Pages 61-101

  5. Making Statistical Inferences from Samples

    • T. Agami Reddy
    Pages 103-140

  6. Estimation of Linear Model Parameters Using Least Squares

    • T. Agami Reddy
    Pages 141-182

  7. Design of Experiments

    • T. Agami Reddy
    Pages 183-205

  8. Optimization Methods

    • T. Agami Reddy
    Pages 207-230

  9. Classification and Clustering Methods

    • T. Agami Reddy
    Pages 231-251

  10. Analysis of Time Series Data

    • T. Agami Reddy
    Pages 253-288

  11. Parameter Estimation Methods

    • T. Agami Reddy
    Pages 289-325

  12. Inverse Methods

    • T. Agami Reddy
    Pages 327-357

  13. Risk Analysis and Decision-Making

    • T. Agami Reddy
    Pages 359-396

  14. ERRATUM

    • T. Agami Reddy
    Pages E1-E4

  15. Back Matter

    Pages 397-430
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Keywords

About this book

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.

Authors and Affiliations

  • The Design Sch. & Sch. of Sust, Arizona State University, Tempe, USA

    T. Agami Reddy

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