Protective Relaying
Protective Relaying

Author: J. Lewis Blackburn

Publisher: CRC Press

Published: 2014-02-11

Total Pages: 678

ISBN-13: 1439888124

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For many years, Protective Relaying: Principles and Applications has been the go-to text for gaining proficiency in the technological fundamentals of power system protection. Continuing in the bestselling tradition of the previous editions by the late J. Lewis Blackburn, the Fourth Edition retains the core concepts at the heart of power system analysis. Featuring refinements and additions to accommodate recent technological progress, the text: Explores developments in the creation of smarter, more flexible protective systems based on advances in the computational power of digital devices and the capabilities of communication systems that can be applied within the power grid Examines the regulations related to power system protection and how they impact the way protective relaying systems are designed, applied, set, and monitored Considers the evaluation of protective systems during system disturbances and describes the tools available for analysis Addresses the benefits and problems associated with applying microprocessor-based devices in protection schemes Contains an expanded discussion of intertie protection requirements at dispersed generation facilities Providing information on a mixture of old and new equipment, Protective Relaying: Principles and Applications, Fourth Edition reflects the present state of power systems currently in operation, making it a handy reference for practicing protection engineers. And yet its challenging end-of-chapter problems, coverage of the basic mathematical requirements for fault analysis, and real-world examples ensure engineering students receive a practical, effective education on protective systems. Plus, with the inclusion of a solutions manual and figure slides with qualifying course adoption, the Fourth Edition is ready-made for classroom implementation.

Simulation Solution Manual (Part I)
Simulation Solution Manual (Part I)

Author: Denis Hallulli

Publisher: Denis Hallulli

Published: 2020-10-15

Total Pages: 66

ISBN-13:

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This is one of a two part series, in which all the exercises of Simulation by Sheldon M. Ross (5th Ed.) are explained thoroughly. The first part will cover Chapters 1 through 6, while the second part the remaining ones. The exercises that involve simulation, are done using C++11.

Student Solutions Manual
Student Solutions Manual

Author: Pearson

Publisher: Addison Wesley Longman

Published: 2004-11

Total Pages: 0

ISBN-13: 9780321226464

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Contains carefully worked-out solutions to all the odd-numbered exercises in the text. Part I corresponds to Chapters 1-11 in Thomas' Calculus, 11e.

Stochastic Calculus for Finance I
Stochastic Calculus for Finance I

Author: Steven Shreve

Publisher: Springer Science & Business Media

Published: 2005-06-28

Total Pages: 212

ISBN-13: 9780387249681

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Developed for the professional Master's program in Computational Finance at Carnegie Mellon, the leading financial engineering program in the U.S. Has been tested in the classroom and revised over a period of several years Exercises conclude every chapter; some of these extend the theory while others are drawn from practical problems in quantitative finance

Game Theory
Game Theory

Author: Steve Tadelis

Publisher: Princeton University Press

Published: 2013-01-06

Total Pages: 416

ISBN-13: 0691129088

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The definitive introduction to game theory This comprehensive textbook introduces readers to the principal ideas and applications of game theory, in a style that combines rigor with accessibility. Steven Tadelis begins with a concise description of rational decision making, and goes on to discuss strategic and extensive form games with complete information, Bayesian games, and extensive form games with imperfect information. He covers a host of topics, including multistage and repeated games, bargaining theory, auctions, rent-seeking games, mechanism design, signaling games, reputation building, and information transmission games. Unlike other books on game theory, this one begins with the idea of rationality and explores its implications for multiperson decision problems through concepts like dominated strategies and rationalizability. Only then does it present the subject of Nash equilibrium and its derivatives. Game Theory is the ideal textbook for advanced undergraduate and beginning graduate students. Throughout, concepts and methods are explained using real-world examples backed by precise analytic material. The book features many important applications to economics and political science, as well as numerous exercises that focus on how to formalize informal situations and then analyze them. Introduces the core ideas and applications of game theory Covers static and dynamic games, with complete and incomplete information Features a variety of examples, applications, and exercises Topics include repeated games, bargaining, auctions, signaling, reputation, and information transmission Ideal for advanced undergraduate and beginning graduate students Complete solutions available to teachers and selected solutions available to students

Fundamentals of Machine Learning for Predictive Data Analytics, second edition
Fundamentals of Machine Learning for Predictive Data Analytics, second edition

Author: John D. Kelleher

Publisher: MIT Press

Published: 2020-10-20

Total Pages: 853

ISBN-13: 0262361108

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The second edition of a comprehensive introduction to machine learning approaches used in predictive data analytics, covering both theory and practice. Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context. This second edition covers recent developments in machine learning, especially in a new chapter on deep learning, and two new chapters that go beyond predictive analytics to cover unsupervised learning and reinforcement learning.