Download or read book Bayesian Networks and Influence Diagrams A Guide to Construction and Analysis written by Uffe B. Kjærulff and published by Springer Science & Business Media. This book was released on 2012-11-30 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Bayesian Networks and Influence Diagrams A Guide to Construction and Analysis written by Uffe B. Kjærulff and published by Springer Science & Business Media. This book was released on 2007-12-20 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Bayesian Networks and Decision Graphs written by Finn V. Jensen and published by Springer Science & Business Media. This book was released on 2001 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Bayesian Networks written by Olivier Pourret and published by John Wiley & Sons. This book was released on 2008-04-30 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian Networks, the result of the convergence of artificial intelligence with statistics, are growing in popularity. Their versatility and modelling power is now employed across a variety of fields for the purposes of analysis, simulation, prediction and diagnosis. This book provides a general introduction to Bayesian networks, defining and illustrating the basic concepts with pedagogical examples and twenty real-life case studies drawn from a range of fields including medicine, computing, natural sciences and engineering. Designed to help analysts, engineers, scientists and professionals taking part in complex decision processes to successfully implement Bayesian networks, this book equips readers with proven methods to generate, calibrate, evaluate and validate Bayesian networks. The book: Provides the tools to overcome common practical challenges such as the treatment of missing input data, interaction with experts and decision makers, determination of the optimal granularity and size of the model. Highlights the strengths of Bayesian networks whilst also presenting a discussion of their limitations. Compares Bayesian networks with other modelling techniques such as neural networks, fuzzy logic and fault trees. Describes, for ease of comparison, the main features of the major Bayesian network software packages: Netica, Hugin, Elvira and Discoverer, from the point of view of the user. Offers a historical perspective on the subject and analyses future directions for research. Written by leading experts with practical experience of applying Bayesian networks in finance, banking, medicine, robotics, civil engineering, geology, geography, genetics, forensic science, ecology, and industry, the book has much to offer both practitioners and researchers involved in statistical analysis or modelling in any of these fields.
Download or read book Risk Assessment and Decision Analysis with Bayesian Networks written by Norman Fenton and published by CRC Press. This book was released on 2018-09-03 with total page 638 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Risk Reliability and Safety Innovating Theory and Practice written by Lesley Walls and published by CRC Press. This book was released on 2016-11-25 with total page 2983 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Bayesian Networks written by Marco Scutari and published by CRC Press. This book was released on 2021-07-28 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Bayesian Networks written by Douglas McNair and published by . This book was released on 2019-11-06 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Safety and Reliability of Complex Engineered Systems written by Luca Podofillini and published by CRC Press. This book was released on 2015-09-03 with total page 730 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Advances in Artificial Intelligence written by Marie-Jean Meurs and published by Springer. This book was released on 2019-05-21 with total page 637 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Symbolic and Quantitative Approaches to Reasoning with Uncertainty written by Weiru Liu and published by Springer Science & Business Media. This book was released on 2011-06-24 with total page 775 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Symbolic and Quantitative Approaches to Reasoning with Uncertainty written by Zied Bouraoui and published by Springer Nature. This book was released on 2023-12-20 with total page 481 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 17th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, ECSQARU 2023, held in Arras, France, in September 2023. The 35 full papers presented in this volume were carefully reviewed and selected from 46 submissions. The papers are organized in topical sections about Complexity and Database Theory; Formal Concept Analysis: Theoretical Advances; Formal Concept Analysis: Applications; Modelling and Explanation; Semantic Web and Graphs; Posters.
Download or read book Advances in Artificial Intelligence From Theory to Practice written by Salem Benferhat and published by Springer. This book was released on 2017-06-10 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNCS 10350 and 10351 constitutes the thoroughly refereed proceedings of the 30th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2017, held in Arras, France, in June 2017. The 70 revised full papers presented together with 45 short papers and 3 invited talks were carefully reviewed and selected from 180 submissions. They are organized in topical sections: constraints, planning, and optimization; data mining and machine learning; sensors, signal processing, and data fusion; recommender systems; decision support systems; knowledge representation and reasoning; navigation, control, and autonome agents; sentiment analysis and social media; games, computer vision; and animation; uncertainty management; graphical models: from theory to applications; anomaly detection; agronomy and artificial intelligence; applications of argumentation; intelligent systems in healthcare and mhealth for health outcomes; and innovative applications of textual analysis based on AI.
Download or read book Probabilistic Graphical Models written by Linda C. van der Gaag and published by Springer. This book was released on 2014-09-11 with total page 609 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 7th International Workshop on Probabilistic Graphical Models, PGM 2014, held in Utrecht, The Netherlands, in September 2014. The 38 revised full papers presented in this book were carefully reviewed and selected from 44 submissions. The papers cover all aspects of graphical models for probabilistic reasoning, decision making, and learning.
Download or read book Risk Assessment written by Marvin Rausand and published by John Wiley & Sons. This book was released on 2013-06-12 with total page 467 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to risk assessment that utilizes key theory and state-of-the-art applications With its balanced coverage of theory and applications along with standards and regulations, Risk Assessment: Theory, Methods, and Applications serves as a comprehensive introduction to the topic. The book serves as a practical guide to current risk analysis and risk assessment, emphasizing the possibility of sudden, major accidents across various areas of practice from machinery and manufacturing processes to nuclear power plants and transportation systems. The author applies a uniform framework to the discussion of each method, setting forth clear objectives and descriptions, while also shedding light on applications, essential resources, and advantages and disadvantages. Following an introduction that provides an overview of risk assessment, the book is organized into two sections that outline key theory, methods, and applications. Introduction to Risk Assessment defines key concepts and details the steps of a thorough risk assessment along with the necessary quantitative risk measures. Chapters outline the overall risk assessment process, and a discussion of accident models and accident causation offers readers new insights into how and why accidents occur to help them make better assessments. Risk Assessment Methods and Applications carefully describes the most relevant methods for risk assessment, including preliminary hazard analysis, HAZOP, fault tree analysis, and event tree analysis. Here, each method is accompanied by a self-contained description as well as workflow diagrams and worksheets that illustrate the use of discussed techniques. Important problem areas in risk assessment, such as barriers and barrier analysis, human errors, and human reliability, are discussed along with uncertainty and sensitivity analysis. Each chapter concludes with a listing of resources for further study of the topic, and detailed appendices outline main results from probability and statistics, related formulas, and a listing of key terms used in risk assessment. A related website features problems that allow readers to test their comprehension of the presented material and supplemental slides to facilitate the learning process. Risk Assessment is an excellent book for courses on risk analysis and risk assessment at the upper-undergraduate and graduate levels. It also serves as a valuable reference for engineers, researchers, consultants, and practitioners who use risk assessment techniques in their everyday work.
Download or read book Oil and Gas Processing Equipment written by G. Unnikrishnan and published by CRC Press. This book was released on 2020-09-14 with total page 153 pages. Available in PDF, EPUB and Kindle. Book excerpt: Oil and gas industries apply several techniques for assessing and mitigating the risks that are inherent in its operations. In this context, the application of Bayesian Networks (BNs) to risk assessment offers a different probabilistic version of causal reasoning. Introducing probabilistic nature of hazards, conditional probability and Bayesian thinking, it discusses how cause and effect of process hazards can be modelled using BNs and development of large BNs from basic building blocks. Focus is on development of BNs for typical equipment in industry including accident case studies and its usage along with other conventional risk assessment methods. Aimed at professionals in oil and gas industry, safety engineering, risk assessment, this book Brings together basics of Bayesian theory, Bayesian Networks and applications of the same to process safety hazards and risk assessment in the oil and gas industry Presents sequence of steps for setting up the model, populating the model with data and simulating the model for practical cases in a systematic manner Includes a comprehensive list on sources of failure data and tips on modelling and simulation of large and complex networks Presents modelling and simulation of loss of containment of actual equipment in oil and gas industry such as Separator, Storage tanks, Pipeline, Compressor and risk assessments Discusses case studies to demonstrate the practicability of use of Bayesian Network in routine risk assessments
Download or read book Bayesian Network written by Ahmed Rebai and published by BoD – Books on Demand. This book was released on 2010-08-18 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian networks are a very general and powerful tool that can be used for a large number of problems involving uncertainty: reasoning, learning, planning and perception. They provide a language that supports efficient algorithms for the automatic construction of expert systems in several different contexts. The range of applications of Bayesian networks currently extends over almost all fields including engineering, biology and medicine, information and communication technologies and finance. This book is a collection of original contributions to the methodology and applications of Bayesian networks. It contains recent developments in the field and illustrates, on a sample of applications, the power of Bayesian networks in dealing the modeling of complex systems. Readers that are not familiar with this tool, but have some technical background, will find in this book all necessary theoretical and practical information on how to use and implement Bayesian networks in their own work. There is no doubt that this book constitutes a valuable resource for engineers, researchers, students and all those who are interested in discovering and experiencing the potential of this major tool of the century.
