Applied Data Analysis and Modeling for Energy Engineers and Scientists
- 14h 52m
- T. Agami Reddy
- Springer
- 2011
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.
In this Book
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Mathematical Models and Data Analysis
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Probability Concepts and Probability Distributions
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Data Collection and Preliminary Data Analysis
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Making Statistical Inferences from Samples
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Estimation of Linear Model Parameters Using Least squares
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Design of Experiments
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Optimization Methods
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Classification and Clustering Methods
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Analysis of Time Series Data
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Parameter Estimation Methods
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Inverse Methods
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Risk Analysis and Decision-Making
