Applied Data Analysis and Modeling for Energy Engineers and Scientists

Applied Data Analysis and Modeling for Energy Engineers and Scientists
Title Applied Data Analysis and Modeling for Energy Engineers and Scientists PDF eBook
Author T. Agami Reddy
Publisher Springer Science & Business Media
Pages 446
Release 2011-08-09
Genre Technology & Engineering
ISBN 1441996133

Download Applied Data Analysis and Modeling for Energy Engineers and Scientists Book in PDF, Epub and Kindle

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

Applied Data Analysis and Modeling for Energy Engineers and Scientists
Title Applied Data Analysis and Modeling for Energy Engineers and Scientists PDF eBook
Author T. Agami Reddy
Publisher Springer Nature
Pages 622
Release 2023-10-18
Genre Business & Economics
ISBN 3031348699

Download Applied Data Analysis and Modeling for Energy Engineers and Scientists Book in PDF, Epub and Kindle

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

Expanding Boundaries: Systems Thinking in the Built Environment
Title Expanding Boundaries: Systems Thinking in the Built Environment PDF eBook
Author Guillaume Habert
Publisher vdf Hochschulverlag AG
Pages 760
Release 2016-08-15
Genre
ISBN 372813774X

Download Expanding Boundaries: Systems Thinking in the Built Environment Book in PDF, Epub and Kindle

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.

Data Science Applied to Sustainability Analysis

Data Science Applied to Sustainability Analysis
Title Data Science Applied to Sustainability Analysis PDF eBook
Author Jennifer Dunn
Publisher Elsevier
Pages 312
Release 2021-05-11
Genre Science
ISBN 0128179775

Download Data Science Applied to Sustainability Analysis Book in PDF, Epub and Kindle

Data Science Applied to Sustainability Analysis focuses on the methodological considerations associated with applying this tool in analysis techniques such as lifecycle assessment and materials flow analysis. As sustainability analysts need examples of applications of big data techniques that are defensible and practical in sustainability analyses and that yield actionable results that can inform policy development, corporate supply chain management strategy, or non-governmental organization positions, this book helps answer underlying questions. In addition, it addresses the need of data science experts looking for routes to apply their skills and knowledge to domain areas. - Presents data sources that are available for application in sustainability analyses, such as market information, environmental monitoring data, social media data and satellite imagery - Includes considerations sustainability analysts must evaluate when applying big data - Features case studies illustrating the application of data science in sustainability analyses

Data-Driven Science and Engineering

Data-Driven Science and Engineering
Title Data-Driven Science and Engineering PDF eBook
Author Steven L. Brunton
Publisher Cambridge University Press
Pages 615
Release 2022-05-05
Genre Computers
ISBN 1009098489

Download Data-Driven Science and Engineering Book in PDF, Epub and Kindle

A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.

Fiscal year 1985 Department of Energy authorization

Fiscal year 1985 Department of Energy authorization
Title Fiscal year 1985 Department of Energy authorization PDF eBook
Author United States. Congress. House. Committee on Science and Technology. Subcommittee on Energy Development and Applications
Publisher
Pages 1698
Release 1984
Genre United States
ISBN

Download Fiscal year 1985 Department of Energy authorization Book in PDF, Epub and Kindle

Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry

Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry
Title Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry PDF eBook
Author Chkoniya, Valentina
Publisher IGI Global
Pages 653
Release 2021-06-25
Genre Computers
ISBN 1799869865

Download Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry Book in PDF, Epub and Kindle

The contemporary world lives on the data produced at an unprecedented speed through social networks and the internet of things (IoT). Data has been called the new global currency, and its rise is transforming entire industries, providing a wealth of opportunities. Applied data science research is necessary to derive useful information from big data for the effective and efficient utilization to solve real-world problems. A broad analytical set allied with strong business logic is fundamental in today’s corporations. Organizations work to obtain competitive advantage by analyzing the data produced within and outside their organizational limits to support their decision-making processes. This book aims to provide an overview of the concepts, tools, and techniques behind the fields of data science and artificial intelligence (AI) applied to business and industries. The Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry discusses all stages of data science to AI and their application to real problems across industries—from science and engineering to academia and commerce. This book brings together practice and science to build successful data solutions, showing how to uncover hidden patterns and leverage them to improve all aspects of business performance by making sense of data from both web and offline environments. Covering topics including applied AI, consumer behavior analytics, and machine learning, this text is essential for data scientists, IT specialists, managers, executives, software and computer engineers, researchers, practitioners, academicians, and students.