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Benefits Of Bayesian Network Models


Benefits Of Bayesian Network Models
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Benefits Of Bayesian Network Models


Benefits Of Bayesian Network Models
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Author : Philippe Weber
language : en
Publisher: John Wiley & Sons
Release Date : 2016-08-29

Benefits Of Bayesian Network Models written by Philippe Weber 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 2016-08-29 with Mathematics categories.


The application of Bayesian Networks (BN) or Dynamic Bayesian Networks (DBN) in dependability and risk analysis is a recent development. A large number of scientific publications show the interest in the applications of BN in this field. Unfortunately, this modeling formalism is not fully accepted in the industry. The questions facing today's engineers are focused on the validity of BN models and the resulting estimates. Indeed, a BN model is not based on a specific semantic in dependability but offers a general formalism for modeling problems under uncertainty. This book explains the principles of knowledge structuration to ensure a valid BN and DBN model and illustrate the flexibility and efficiency of these representations in dependability, risk analysis and control of multi-state systems and dynamic systems. Across five chapters, the authors present several modeling methods and industrial applications are referenced for illustration in real industrial contexts.



Benefits Of Bayesian Network Models


Benefits Of Bayesian Network Models
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Author : Philippe Weber
language : en
Publisher: John Wiley & Sons
Release Date : 2016-08-23

Benefits Of Bayesian Network Models written by Philippe Weber 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 2016-08-23 with Mathematics categories.


The application of Bayesian Networks (BN) or Dynamic Bayesian Networks (DBN) in dependability and risk analysis is a recent development. A large number of scientific publications show the interest in the applications of BN in this field. Unfortunately, this modeling formalism is not fully accepted in the industry. The questions facing today's engineers are focused on the validity of BN models and the resulting estimates. Indeed, a BN model is not based on a specific semantic in dependability but offers a general formalism for modeling problems under uncertainty. This book explains the principles of knowledge structuration to ensure a valid BN and DBN model and illustrate the flexibility and efficiency of these representations in dependability, risk analysis and control of multi-state systems and dynamic systems. Across five chapters, the authors present several modeling methods and industrial applications are referenced for illustration in real industrial contexts.



Bayesian Networks


Bayesian Networks
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Author : Olivier Pourret
language : en
Publisher: John Wiley & Sons
Release Date : 2008-04-30

Bayesian Networks written by Olivier Pourret 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 2008-04-30 with Mathematics categories.


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.



Innovations In Bayesian Networks


Innovations In Bayesian Networks
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Author : Dawn E. Holmes
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-10-02

Innovations In Bayesian Networks written by Dawn E. Holmes 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 2008-10-02 with Mathematics categories.


Bayesian networks currently provide one of the most rapidly growing areas of research in computer science and statistics. In compiling this volume we have brought together contributions from some of the most prestigious researchers in this field. Each of the twelve chapters is self-contained. Both theoreticians and application scientists/engineers in the broad area of artificial intelligence will find this volume valuable. It also provides a useful sourcebook for Graduate students since it shows the direction of current research.



Modeling And Reasoning With Bayesian Networks


Modeling And Reasoning With Bayesian Networks
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Author : Adnan Darwiche
language : en
Publisher: Cambridge University Press
Release Date : 2009-04-06

Modeling And Reasoning With Bayesian Networks written by Adnan Darwiche and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-04-06 with Computers categories.


This book provides a thorough introduction to the formal foundations and practical applications of Bayesian networks. It provides an extensive discussion of techniques for building Bayesian networks that model real-world situations, including techniques for synthesizing models from design, learning models from data, and debugging models using sensitivity analysis. It also treats exact and approximate inference algorithms at both theoretical and practical levels. The author assumes very little background on the covered subjects, supplying in-depth discussions for theoretically inclined readers and enough practical details to provide an algorithmic cookbook for the system developer.



Bayesian Networks And Bayesialab


Bayesian Networks And Bayesialab
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Author : Stefan Conrady
language : en
Publisher:
Release Date : 2015-07-01

Bayesian Networks And Bayesialab written by Stefan Conrady and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-07-01 with categories.




Bayesian Networks And Decision Graphs


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.



Handbook Of Hydroinformatics


Handbook Of Hydroinformatics
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Author : Saeid Eslamian
language : en
Publisher: Elsevier
Release Date : 2022-11-30

Handbook Of Hydroinformatics written by Saeid Eslamian and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-30 with Technology & Engineering categories.


Classic Soft-Computing Techniques is the first volume of the three, in the Handbook of HydroInformatics series. Through this comprehensive, 34-chapters work, the contributors explore the difference between traditional computing, also known as hard computing, and soft computing, which is based on the importance given to issues like precision, certainty and rigor. The chapters go on to define fundamentally classic soft-computing techniques such as Artificial Neural Network, Fuzzy Logic, Genetic Algorithm, Supporting Vector Machine, Ant-Colony Based Simulation, Bat Algorithm, Decision Tree Algorithm, Firefly Algorithm, Fish Habitat Analysis, Game Theory, Hybrid Cuckoo–Harmony Search Algorithm, Honey-Bee Mating Optimization, Imperialist Competitive Algorithm, Relevance Vector Machine, etc. It is a fully comprehensive handbook providing all the information needed around classic soft-computing techniques. This volume is a true interdisciplinary work, and the audience includes postgraduates and early career researchers interested in Computer Science, Mathematical Science, Applied Science, Earth and Geoscience, Geography, Civil Engineering, Engineering, Water Science, Atmospheric Science, Social Science, Environment Science, Natural Resources, and Chemical Engineering. - Key insights from global contributors in the fields of data management research, climate change and resilience, insufficient data problem, etc. - Offers applied examples and case studies in each chapter, providing the reader with real world scenarios for comparison. - Introduces classic soft-computing techniques, necessary for a range of disciplines.



Building Information Modeling For A Smart And Sustainable Urban Space


Building Information Modeling For A Smart And Sustainable Urban Space
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Author : Rafika Hajji
language : en
Publisher: John Wiley & Sons
Release Date : 2021-12-21

Building Information Modeling For A Smart And Sustainable Urban Space written by Rafika Hajji 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 2021-12-21 with Architecture categories.


Urban spaces are being called upon to develop a capacity for resilience and sustainability in order to meet the major challenges they face. To achieve such a goal, a practical development framework must be implemented in order to take advantage of the technological innovations that characterize the field of construction and urban engineering. Today, multi-scale BIM is bringing about significant changes that are redefining the paradigms of urban management. It facilitates simulations of the sustainability of urban spaces with respect to several criteria; most notably relating to energy, the economy and the environment. Building Information Modeling for a Smart and Sustainable Urban Space proposes a theoretical and practical framework for implementing BIM models for the creation of sustainable and intelligent urban spaces. It addresses the issues of acquisition, modeling, interoperability, and BIM and GIS integration for the production of BIM models. Case studies are presented, providing a practical dimension that demonstrates the production process of the urban model and its contribution to multiscale simulations, particularly in real estate evaluation and urban renewal.



Analysis Modeling And Stability Of Fractional Order Differential Systems 1


Analysis Modeling And Stability Of Fractional Order Differential Systems 1
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Author : Jean-Claude Trigeassou
language : en
Publisher: John Wiley & Sons
Release Date : 2019-08-06

Analysis Modeling And Stability Of Fractional Order Differential Systems 1 written by Jean-Claude Trigeassou 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 2019-08-06 with Technology & Engineering categories.


This book introduces an original fractional calculus methodology (‘the infinite state approach’) which is applied to the modeling of fractional order differential equations (FDEs) and systems (FDSs). Its modeling is based on the frequency distributed fractional integrator, while the resulting model corresponds to an integer order and infinite dimension state space representation. This original modeling allows the theoretical concepts of integer order systems to be generalized to fractional systems, with a particular emphasis on a convolution formulation.