Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis PDF Download
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Author: Uffe B. Kjærulff
Publisher: Springer Science & Business Media
ISBN: 0387741011
Category : Computers
Languages : en
Pages : 325
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Book Description
Probabilistic networks, also known as Bayesian networks and influence diagrams, have become one of the most promising technologies in the area of applied artificial intelligence. This book provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. Intended primarily for practitioners, this book does not require sophisticated mathematical skills. The theory and methods presented are illustrated through more than 140 examples, and exercises are included for the reader to check his/her level of understanding.
Author: Uffe B. Kjærulff
Publisher: Springer Science & Business Media
ISBN: 0387741011
Category : Computers
Languages : en
Pages : 325
Get Book
Book Description
Probabilistic networks, also known as Bayesian networks and influence diagrams, have become one of the most promising technologies in the area of applied artificial intelligence. This book provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. Intended primarily for practitioners, this book does not require sophisticated mathematical skills. The theory and methods presented are illustrated through more than 140 examples, and exercises are included for the reader to check his/her level of understanding.
Author: Uffe B. Kjærulff
Publisher: Springer Science & Business Media
ISBN: 1461451043
Category : Computers
Languages : en
Pages : 388
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Book Description
Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis, Second Edition, provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. This new edition contains six new sections, in addition to fully-updated examples, tables, figures, and a revised appendix. Intended primarily for practitioners, this book does not require sophisticated mathematical skills or deep understanding of the underlying theory and methods nor does it discuss alternative technologies for reasoning under uncertainty. The theory and methods presented are illustrated through more than 140 examples, and exercises are included for the reader to check his or her level of understanding. The techniques and methods presented for knowledge elicitation, model construction and verification, modeling techniques and tricks, learning models from data, and analyses of models have all been developed and refined on the basis of numerous courses that the authors have held for practitioners worldwide.
Author: Finn V. Jensen
Publisher: Springer Science & Business Media
ISBN: 9780387952598
Category : Business & Economics
Languages : en
Pages : 288
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Book Description
A practical guide to normative systems: Causal and bayesian networks; Building models; learning, adaptation, and tuning; Decision graphs. Algorithms ofr normative systems: Belief updating in bayesian networks; Bayesian network analysis tools; Algorithms ofr influence diagrams. List of notation.
Author: Norman Fenton
Publisher: CRC Press
ISBN: 1351978977
Category : Mathematics
Languages : en
Pages : 638
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Book Description
Since the first edition of this book published, Bayesian networks have become even more important for applications in a vast array of fields. This second edition includes new material on influence diagrams, learning from data, value of information, cybersecurity, debunking bad statistics, and much more. Focusing on practical real-world problem-solving and model building, as opposed to algorithms and theory, it explains how to incorporate knowledge with data to develop and use (Bayesian) causal models of risk that provide more powerful insights and better decision making than is possible from purely data-driven solutions. Features Provides all tools necessary to build and run realistic Bayesian network models Supplies extensive example models based on real risk assessment problems in a wide range of application domains provided; for example, finance, safety, systems reliability, law, forensics, cybersecurity and more Introduces all necessary mathematics, probability, and statistics as needed Establishes the basics of probability, risk, and building and using Bayesian network models, before going into the detailed applications A dedicated website contains exercises and worked solutions for all chapters along with numerous other resources. The AgenaRisk software contains a model library with executable versions of all of the models in the book. Lecture slides are freely available to accredited academic teachers adopting the book on their course.
Author: Lesley Walls
Publisher: CRC Press
ISBN: 149878898X
Category : Technology & Engineering
Languages : en
Pages : 2983
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Book Description
Risk, Reliability and Safety contains papers describing innovations in theory and practice contributed to the scientific programme of the European Safety and Reliability conference (ESREL 2016), held at the University of Strathclyde in Glasgow, Scotland (25—29 September 2016). Authors include scientists, academics, practitioners, regulators and other key individuals with expertise and experience relevant to specific areas. Papers include domain specific applications as well as general modelling methods. Papers cover evaluation of contemporary solutions, exploration of future challenges, and exposition of concepts, methods and processes. Topics include human factors, occupational health and safety, dynamic and systems reliability modelling, maintenance optimisation, uncertainty analysis, resilience assessment, risk and crisis management.
Author: Marco Scutari
Publisher: CRC Press
ISBN: 1000410382
Category : Computers
Languages : en
Pages : 275
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Book Description
Explains the material step-by-step starting from meaningful examples Steps detailed with R code in the spirit of reproducible research Real world data analyses from a Science paper reproduced and explained in detail Examples span a variety of fields across social and life sciences Overview of available software in and outside R
Author: Douglas McNair
Publisher:
ISBN: 1839623225
Category :
Languages : en
Pages : 138
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Book Description
Author: Luca Podofillini
Publisher: CRC Press
ISBN: 1315648415
Category : Technology & Engineering
Languages : en
Pages : 730
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Book Description
Safety and Reliability of Complex Engineered Systems contains the Proceedings of the 25th European Safety and Reliability Conference, ESREL 2015, held 7-10 September 2015 in Zurich, Switzerland. It includes about 570 papers accepted for presentation at the conference. These contributions focus on theories and methods in the area of risk, safety and
Author: Marie-Jean Meurs
Publisher: Springer
ISBN: 303018305X
Category : Computers
Languages : en
Pages : 637
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Book Description
This book constitutes the refereed proceedings of the 32nd Canadian Conference on Artificial Intelligence, Canadian AI 2019, held in Kingston, ON, Canada, in May 2019. The 27 regular papers and 34 short papers presented together with 8 Graduate Student Symposium papers and 4 Industry Track papers were carefully reviewed and selected from 132 submissions. The focus of the conference was on artificial intelligence research and advanced information and communications technology.
Author: Weiru Liu
Publisher: Springer Science & Business Media
ISBN: 3642221513
Category : Computers
Languages : en
Pages : 775
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Book Description
This book constitutes the refereed proceedings of the 11th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, ECSQARU 2011, held in Belfast, UK, in June/July 2011. The 60 revised full papers presented together with 3 invited talks were carefully reviewed and selected from 108 submissions. The papers are organized in topical sections on argumentation; Bayesian networks and causal networks; belief functions; belief revision and inconsistency handling; classification and clustering; default reasoning and logics for reasoning under uncertainty; foundations of reasoning and decision making under uncertainty; fuzzy sets and fuzzy logic; implementation and applications of uncertain systems; possibility theory and possibilistic logic; and uncertainty in databases.
