Bayesian Networks And Decision Graphs

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Bayesian Networks And Decision Graphs

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Author : Finn V. Jensen
language : en
Publisher: Springer Science & Business Media
Release Date : 2001

Bayesian Networks And Decision Graphs written by Finn V. Jensen and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Business & Economics categories.

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.

Bayesian Networks And Decision Graphs

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Author : Thomas Dyhre Nielsen
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-03-17

Bayesian Networks And Decision Graphs written by Thomas Dyhre Nielsen and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-03-17 with Science categories.

This is a brand new edition of an essential work on Bayesian networks and decision graphs. It is an introduction to probabilistic graphical models including Bayesian networks and influence diagrams. The reader is guided through the two types of frameworks with examples and exercises, which also give instruction on how to build these models. Structured in two parts, the first section focuses on probabilistic graphical models, while the second part deals with decision graphs, and in addition to the frameworks described in the previous edition, it also introduces Markov decision process and partially ordered decision problems.

Bayesian Networks And Decision Graphs

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Author : Thomas Dyhre Nielsen
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-06-29

Bayesian Networks And Decision Graphs written by Thomas Dyhre Nielsen and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-29 with Mathematics categories.

Bayesian networks and decision graphs are formal graphical languages for representation and communication of decision scenarios requiring reasoning under uncertainty. Their strengths are two-sided. It is easy for humans to construct and to understand them, and when communicated to a computer, they can easily be compiled. Furthermore, handy algorithms are developed for analyses of the models and for providing responses to a wide range of requests such as belief updating, determining optimal strategies, conflict analyses of evidence, and most probable explanation. The book emphasizes both the human and the computer sides. Part I gives a thorough introduction to Bayesian networks as well as decision trees and infulence diagrams, and through examples and exercises, the reader is instructed in building graphical models from domain knowledge. This part is self-contained and it does not require other background than standard secondary school mathematics. Part II is devoted to the presentation of algorithms and complexity issues. This part is also self-contained, but it requires that the reader is familiar with working with texts in the mathematical language. The author also: - provides a well-founded practical introduction to Bayesian networks, decision trees and influence diagrams; - gives several examples and exercises exploiting the computer systems for Bayesian netowrks and influence diagrams; - gives practical advice on constructiong Bayesian networks and influence diagrams from domain knowledge; - embeds decision making into the framework of Bayesian networks; - presents in detail the currently most efficient algorithms for probability updating in Bayesian networks; - discusses a wide range of analyes tools and model requests together with algorithms for calculation of responses; - gives a detailed presentation of the currently most efficient algorithm for solving influence diagrams.

Advances In Bayesian Networks

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Author : José A. Gámez
language : en
Publisher: Springer
Release Date : 2013-06-29

Advances In Bayesian Networks written by José A. Gámez and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-29 with Mathematics categories.

In recent years probabilistic graphical models, especially Bayesian networks and decision graphs, have experienced significant theoretical development within areas such as artificial intelligence and statistics. This carefully edited monograph is a compendium of the most recent advances in the area of probabilistic graphical models such as decision graphs, learning from data and inference. It presents a survey of the state of the art of specific topics of recent interest of Bayesian Networks, including approximate propagation, abductive inferences, decision graphs, and applications of influence. In addition, Advances in Bayesian Networks presents a careful selection of applications of probabilistic graphical models to various fields such as speech recognition, meteorology or information retrieval.

Bayesian Networks And Influence Diagrams A Guide To Construction And Analysis

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Author : Uffe B. Kjærulff
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-11-30

Bayesian Networks And Influence Diagrams A Guide To Construction And Analysis written by Uffe B. Kjærulff and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-11-30 with Computers categories.

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.

Hierarchical Bayesian Optimization Algorithm

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Author : Martin Pelikan
language : en
Publisher: Springer Science & Business Media
Release Date : 2005-02

Hierarchical Bayesian Optimization Algorithm written by Martin Pelikan and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-02 with Computers categories.

This book provides a framework for the design of competent optimization techniques by combining advanced evolutionary algorithms with state-of-the-art machine learning techniques. The book focuses on two algorithms that replace traditional variation operators of evolutionary algorithms by learning and sampling Bayesian networks: the Bayesian optimization algorithm (BOA) and the hierarchical BOA (hBOA). BOA and hBOA are theoretically and empirically shown to provide robust and scalable solution for broad classes of nearly decomposable and hierarchical problems. A theoretical model is developed that estimates the scalability and adequate parameter settings for BOA and hBOA. The performance of BOA and hBOA is analyzed on a number of artificial problems of bounded difficulty designed to test BOA and hBOA on the boundary of their design envelope. The algorithms are also extensively tested on two interesting classes of real-world problems: MAXSAT and Ising spin glasses with periodic boundary conditions in two and three dimensions. Experimental results validate the theoretical model and confirm that BOA and hBOA provide robust and scalable solution for nearly decomposable and hierarchical problems with only little problem-specific information.

Internet Of Things And Analytics For Agriculture Volume 2

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Author : Prasant Kumar Pattnaik
language : en
Publisher: Springer Nature
Release Date : 2019-10-24

Internet Of Things And Analytics For Agriculture Volume 2 written by Prasant Kumar Pattnaik and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-24 with Technology & Engineering categories.

This book addresses major challenges faced by farmers and the technological solutions based on Internet of Things (IoT). A major challenge in agriculture is cultivating and supplying high-quality produce at the best. Currently, around 50% of global farm produce never reaches the end consumer due to wastage and suboptimal prices. The book presents solutions that reduce the transport costs, improve the predictability of prices based on data analytics and the current market conditions, and reduce the number of middle steps and agents between the farmer and the end consumer. It discusses the design of an IoT-based monitoring system to analyze crop environments and a method to improve the efficiency of decision-making by analyzing harvest statistics. Further, it explores climate-smart methods, known as smart agriculture, that have been adopted by a number of Indian farmers.

Genetic And Evolutionary Computation Gecco 2004

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Author : Kalyanmoy Deb
language : en
Publisher: Springer
Release Date : 2004-06-01

Genetic And Evolutionary Computation Gecco 2004 written by Kalyanmoy Deb and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-06-01 with Computers categories.

The two volume set LNCS 3102/3103 constitutes the refereed proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2004, held in Seattle, WA, USA, in June 2004. The 230 revised full papers and 104 poster papers presented were carefully reviewed and selected from 460 submissions. The papers are organized in topical sections on artificial life, adaptive behavior, agents, and ant colony optimization; artificial immune systems, biological applications; coevolution; evolutionary robotics; evolution strategies and evolutionary programming; evolvable hardware; genetic algorithms; genetic programming; learning classifier systems; real world applications; and search-based software engineering.

Encyclopedia Of Quantitative Risk Analysis And Assessment

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Author :
language : en
Publisher: John Wiley & Sons
Release Date : 2008-09-02

Encyclopedia Of Quantitative Risk Analysis And Assessment written by and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-09-02 with Mathematics categories.

Leading the way in this field, the Encyclopedia of Quantitative Risk Analysis and Assessment is the first publication to offer a modern, comprehensive and in-depth resource to the huge variety of disciplines involved. A truly international work, its coverage ranges across risk issues pertinent to life scientists, engineers, policy makers, healthcare professionals, the finance industry, the military and practising statisticians. Drawing on the expertise of world-renowned authors and editors in this field this title provides up-to-date material on drug safety, investment theory, public policy applications, transportation safety, public perception of risk, epidemiological risk, national defence and security, critical infrastructure, and program management. This major publication is easily accessible for all those involved in the field of risk assessment and analysis. For ease-of-use it is available in print and online.

Computational Intelligence And Intelligent Systems

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Author : Kangshun Li
language : en
Publisher: Springer
Release Date : 2016-01-18

Computational Intelligence And Intelligent Systems written by Kangshun Li and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-01-18 with Computers categories.

This book constitutes the refereed proceedings of the 7th International Symposium on Intelligence Computation and Applications, ISICA 2015, held in Guangzhou, China, in November 2015. The 77 revised full papers presented were carefully reviewed and selected from 189 submissions. The papers feature the most up-to-date research in analysis and theory of evolutionary computation, neural network architectures and learning; neuro-dynamics and neuro-engineering; fuzzy logic and control; collective intelligence and hybrid systems; deep learning; knowledge discovery; learning and reasoning.