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Applied Data Analysis and Modeling for Energy Engineers and Scientists

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Release : 2011-08-09
Genre : Technology & Engineering
Kind : eBook
Book Rating : 133/5 ( reviews)

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Book Synopsis Applied Data Analysis and Modeling for Energy Engineers and Scientists by : T. Agami Reddy

Download or read book Applied Data Analysis and Modeling for Energy Engineers and Scientists written by T. Agami Reddy. This book was released on 2011-08-09. Available in PDF, EPUB and Kindle. Book excerpt: 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

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Release : 2023-10-18
Genre : Business & Economics
Kind : eBook
Book Rating : 699/5 ( reviews)

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Book Synopsis Applied Data Analysis and Modeling for Energy Engineers and Scientists by : T. Agami Reddy

Download or read book Applied Data Analysis and Modeling for Energy Engineers and Scientists written by T. Agami Reddy. This book was released on 2023-10-18. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Expanding Boundaries: Systems Thinking in the Built Environment

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Author :
Release : 2016-08-15
Genre :
Kind : eBook
Book Rating : 74X/5 ( reviews)

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Book Synopsis Expanding Boundaries: Systems Thinking in the Built Environment by : Guillaume Habert

Download or read book Expanding Boundaries: Systems Thinking in the Built Environment written by Guillaume Habert. This book was released on 2016-08-15. Available in PDF, EPUB and Kindle. Book excerpt: Consuming over 40% of total primary energy, the built environment is in the centre of worldwide strategies and measures towards a more sustainable future. To provide resilient solutions, a simple optimisation of individual technologies will not be sufficient. In contrast, whole system thinking reveals and exploits connections between parts. Each system interacts with others on different scales (materials, components, buildings, cities) and domains (ecology, economy and social). Whole-system designers optimize the performance of such systems by understanding interconnections and identifying synergies. The more complete the design integration, the better the result. In this book, the reader will find the proceedings of the 2016 Sustainable Built Environment (SBE) Regional Conference in Zurich. Papers have been written by academics and practitioners from all continents to bring forth the latest understanding on systems thinking in the built environment.

Predictive Modelling for Energy Management and Power Systems Engineering

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Release : 2020-09-30
Genre : Science
Kind : eBook
Book Rating : 73X/5 ( reviews)

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Book Synopsis Predictive Modelling for Energy Management and Power Systems Engineering by : Ravinesh Deo

Download or read book Predictive Modelling for Energy Management and Power Systems Engineering written by Ravinesh Deo. This book was released on 2020-09-30. Available in PDF, EPUB and Kindle. Book excerpt: Predictive Modeling for Energy Management and Power Systems Engineering introduces readers to the cutting-edge use of big data and large computational infrastructures in energy demand estimation and power management systems. The book supports engineers and scientists who seek to become familiar with advanced optimization techniques for power systems designs, optimization techniques and algorithms for consumer power management, and potential applications of machine learning and artificial intelligence in this field. The book provides modeling theory in an easy-to-read format, verified with on-site models and case studies for specific geographic regions and complex consumer markets. Presents advanced optimization techniques to improve existing energy demand system Provides data-analytic models and their practical relevance in proven case studies Explores novel developments in machine-learning and artificial intelligence applied in energy management Provides modeling theory in an easy-to-read format

Data-Driven Modeling for Sustainable Engineering

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Release : 2019-06-21
Genre : Technology & Engineering
Kind : eBook
Book Rating : 973/5 ( reviews)

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Book Synopsis Data-Driven Modeling for Sustainable Engineering by : Kondo H. Adjallah

Download or read book Data-Driven Modeling for Sustainable Engineering written by Kondo H. Adjallah. This book was released on 2019-06-21. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers the proceedings of the 1st International Conference on Engineering, Applied Sciences and System Modeling (ICEASSM), a four-day event (18th–21st April 2017) held in Accra, Ghana. It focuses on research work promoting a better understanding of engineering problems through applied sciences and modeling, and on solutions generated in an African setting but with relevance to the world as a whole. The book provides a holistic overview of challenges facing Africa, and addresses various areas from research and development perspectives. Presenting contributions by scientists, engineers and experts hailing from a host of international institutions, the book offers original approaches and technological solutions to help solve real-world problems through research and knowledge sharing. Further, it explores promising opportunities for collaborative research on issues of scientific, economic and social development, making it of interest to researchers, scientists and practitioners looking to conduct research in disciplines such as water supply, control, civil engineering, statistical modeling, renewable energy and sustainable urban development.

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