Data driven decision making using analytics, Parul Gandhi; Surbhi Bhatia; Kapil Dev;
Автор: Stimmel Carol L. Название: Big Data Analytics Strategies for the Smart Grid ISBN: 1482218283 ISBN-13(EAN): 9781482218282 Издательство: Taylor&Francis Рейтинг: Цена: 14545.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
By implementing a comprehensive data analytics program, utility companies can meet the continually evolving challenges of modern grids that are operationally efficient, while reconciling the demands of greenhouse gas legislation and establishing a meaningful return on investment from smart grid deployments.
Readable and accessible, Big Data Analytics Strategies for the Smart Grid addresses the needs of applying big data technologies and approaches, including Big Data cybersecurity, to the critical infrastructure that makes up the electrical utility grid. It supplies industry stakeholders with an in-depth understanding of the engineering, business, and customer domains within the power delivery market. The book explores the unique needs of electrical utility grids, including operational technology, IT, storage, processing, and how to transform grid assets for the benefit of both the utility business and energy consumers. It not only provides specific examples that illustrate how analytics work and how they are best applied, but also describes how to avoid potential problems and pitfalls. Discussing security and data privacy, it explores the role of the utility in protecting their customers' right to privacy while still engaging in forward-looking business practices. The book includes discussions of:
SAS for asset management tools
The AutoGrid approach to commercial analytics
Space-Time Insight's work at the California ISO (CAISO)
This book is an ideal resource for mid- to upper-level utility executives who need to understand the business value of smart grid data analytics. It explains critical concepts in a manner that will better position executives to make the right decisions about building their analytics programs.
At the same time, the book provides sufficient technical depth that it is useful for data analytics professionals who need to better understand the nuances of the engineering and business challenges unique to the utilities industry.
Автор: Gallagher Alyssa, Thordarson Kami Название: Design Thinking in Play: An Action Guide for Educators ISBN: 1416628851 ISBN-13(EAN): 9781416628859 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 4019.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Design thinking is a person-centered, problem-solving process that's a go-to for innovative businesses and gaining traction with school leaders interested in positive change. But understanding design thinking is one thing; actually putting it in play is something else.
Authors Alyssa Gallagher and Kami Thordarson offer educators a practical guide for navigating design thinking's invigorating challenges and reaping its considerable rewards. They dig deep into the five-stage design thinking process, highlighting risk factors and recommending specific steps to keep you moving forward. The 25 downloadable and reproducible tools provide prompts and supports that will help you and your team:
Identify change opportunities.
Dig deeper into complex problems.
Analyze topics to isolate specific challenges.
Connect with and solve for user needs.
Apply what you've learned about users to design challenges.
Maximize brainstorming power.
Create and employ solution prototypes.
Pitch solutions and secure buy-in from stakeholders.
Organize and analyze user feedback.
Map out a solution's specific actions and resource requirements.
Design Thinking in Play is a must-have for education leaders who are tired of waiting for someone else to solve their problems and ready to take action, have fun, and leverage collective insight to figure out what will really work for their school, their colleagues, and their students.
Автор: Cengiz Kahraman; ?rem Otay Название: Fuzzy Multi-criteria Decision-Making Using Neutrosophic Sets ISBN: 3030000443 ISBN-13(EAN): 9783030000448 Издательство: Springer Рейтинг: Цена: 20733.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book offers a comprehensive guide to the use of neutrosophic sets in multiple criteria decision making problems. It shows how neutrosophic sets, which have been developed as an extension of fuzzy and paraconsistent logic, can help in dealing with certain types of uncertainty that classical methods could not cope with. The chapters, written by well-known researchers, report on cutting-edge methodologies they have been developing and testing on a variety of engineering problems. The book is unique in its kind as it reports for the first time and in a comprehensive manner on the joint use of neutrosophic sets together with existing decision making methods to solve multi-criteria decision-making problems, as well as other engineering problems that are complex, hard to model and/or include incomplete and vague data. By providing new ideas, suggestions and directions for the solution of complex problems in engineering and decision making, it represents an excellent guide for researchers, lecturers and postgraduate students pursuing research on neutrosophic decision making, and more in general in the area of industrial and management engineering.
Автор: Walters Edward J. Название: Data-Driven Law: Data Analytics and the New Legal Services ISBN: 1032095008 ISBN-13(EAN): 9781032095004 Издательство: Taylor&Francis Рейтинг: Цена: 7654.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Data has reshaped industries around the world, from finance and medicine to sports. Law has trailed behind other industries, but is quickly following suit. For many years, law firms made important decisions - including very large decisions - based on limited experience (at best), or hunches (at worst). Data science is growing quickly in law firm
Описание: This text is a coherent account of the science of decision making. It includes the models of operations research and those models of probability that relate to decision making. An emphasis in placed between these connections and relates these models to nearly all of the professions.
Автор: Surafel Luleseged Tilahun, Jean Medard T. Ngnotchouye Название: Optimization Techniques for Problem Solving in Uncertainty ISBN: 1522550917 ISBN-13(EAN): 9781522550914 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 28413.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: When it comes to optimization techniques, in some cases, the available information from real models may not be enough to construct either a probability distribution or a membership function for problem solving. In such cases, there are various theories that can be used to quantify the uncertain aspects.Optimization Techniques for Problem Solving in Uncertainty is a scholarly reference resource that looks at uncertain aspects involved in different disciplines and applications. Featuring coverage on a wide range of topics including uncertain preference, fuzzy multilevel programming, and metaheuristic applications, this book is geared towards engineers, managers, researchers, and post-graduate students seeking emerging research in the field of optimization.
Описание: Explores the principles underpinning data science. The book considers the how and why of modern data science. It goes further than existing books by applying data to decision making. Not only is the book useful for undergraduates, but it can also help business owners in improving their decision making.
Описание: Big Data analytics relates to the strategies used by enterprises to process and analyze large amounts of data to bring out hidden insights. With the help of open source and enterprise tools, such as R, Python, Hadoop, and Spark, you will learn how to effectively mine your Big Data. By the end of this book, you will have a clear understanding ...
Описание: To start with you will cover the basics of graph analytics, Cypher querying language, components of graph architecture, and more. You will implement Neo4j techniques to understand various graph analytics methods to reveal complex relationships in data. You will understand how machine learning can be used to perform smarter graph analytics.
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