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Author: Ibrahimovi?, Semir
Publisher: IGI Global
ISBN: 1522522697
Category : Computers
Languages : en
Pages : 180
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Book Description
Technological tools have enhanced the available opportunities and activities in the realm of e-business. In organizations that support real-time business-critical operations, the proper use and maintenance of relevant technology is crucial. Maximizing Information System Availability Through Bayesian Belief Network Approaches: Emerging Research and Opportunities is a pivotal book that features the latest research perspectives on the implementation of effective information systems in business contexts. Highlighting relevant topics such as data security, investment viability, and operational risk management, this book is ideally designed for managers, professionals, academics, practitioners, and students interested in novel techniques for maintaining and measuring information system availability.
Author: Ibrahimovi?, Semir
Publisher: IGI Global
ISBN: 1522522697
Category : Computers
Languages : en
Pages : 180
Get Book
Book Description
Technological tools have enhanced the available opportunities and activities in the realm of e-business. In organizations that support real-time business-critical operations, the proper use and maintenance of relevant technology is crucial. Maximizing Information System Availability Through Bayesian Belief Network Approaches: Emerging Research and Opportunities is a pivotal book that features the latest research perspectives on the implementation of effective information systems in business contexts. Highlighting relevant topics such as data security, investment viability, and operational risk management, this book is ideally designed for managers, professionals, academics, practitioners, and students interested in novel techniques for maintaining and measuring information system availability.
Author: Olga Dolinina
Publisher: Springer
ISBN: 3030120724
Category : Technology & Engineering
Languages : en
Pages : 771
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Book Description
This book constitutes the full papers and short monographs developed on the base of the refereed proceedings of the International Conference on Information Technologies: Information and Communication Technologies for Research and Industry (ICIT-2019), held in Saratov, Russia in February 2019. The book brings accepted papers which present new approaches and methods of solving problems in the sphere of control engineering and decision making for the various fields of studies: industry and research, ontology-based data simulation, smart city technologies, theory and use of digital signal processing, cognitive systems, robotics, cybernetics, automation control theory, image recognition technologies, and computer vision. Particular emphasis is laid on modern trends, new approaches, algorithms and methods in selected fields of interest. The presented papers were accepted after careful reviews made by at least three independent reviewers in a double-blind way. The acceptance level was about 60%. The chapters are organized thematically in several areas within the following tracks: • Models, Methods & Approaches in Decision Making Systems • Mathematical Modelling for Industry & Research • Smart City Technologies The conference is focused on development and globalization of information and communication technologies (ICT), methods of control engineering and decision making along with innovations and networking, ICT for sustainable development and technological change, and global challenges. Moreover, the ICIT-2019 served as a discussion area for the actual above-mentioned topics. The editors believe that the readers will find the proceedings interesting and useful for their own research work.
Author: Vasant, Pandian
Publisher: IGI Global
ISBN: 1522529918
Category : Computers
Languages : en
Pages : 812
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Book Description
Modern optimization approaches have attracted an increasing number of scientists, decision makers, and researchers. As new issues in this field emerge, different optimization methodologies must be developed and implemented. The Handbook of Research on Emergent Applications of Optimization Algorithms is an authoritative reference source for the latest scholarly research on modern optimization techniques for solving complex problems of global optimization and their applications in economics and engineering. Featuring coverage on a broad range of topics and perspectives such as hybrid systems, non-cooperative games, and cryptography, this publication is ideally designed for students, researchers, and engineers interested in emerging developments in optimization algorithms.
Author: Strang, Kenneth David
Publisher: IGI Global
ISBN: 152254755X
Category : Business & Economics
Languages : en
Pages : 418
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Book Description
Risk management is a vital concern in any organization. In order to succeed in the competitive modern business environment, the decision-making process must be effectively governed and managed. Research, Practices, and Innovations in Global Risk and Contingency Management is a critical scholarly resource that provides an all-encompassing holistic discussion of risk management and perception, while giving readers innovations on empirical risk-contingency management research and case studies. Featuring coverage on a broad range of topics, such as contingency planning, project management, and risk mitigation, this book is geared towards academicians, practitioners, and researchers seeking current research on risk and contingency management issues.
Author: Risso, Mario
Publisher: IGI Global
ISBN: 1522531483
Category : Business & Economics
Languages : en
Pages : 398
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Book Description
Business retains a large influence over the progression of society. Thus, shared goals among corporations could lead to a larger positive impact on the resilience of social and economic expansions. Value Sharing for Sustainable and Inclusive Development is a critical academic resource that explores the opportunities through which businesses can contribute to sustainable and inclusive development. Featuring coverage on a broad range of topics such as the value sharing model, corporate social responsibility, and multi-sided markets, this book is geared toward academicians, researchers, policy makers, and students seeking current research on the importance of collaborative efforts on the part of businesses and entities to achieve functional progression.
Author: Michael Irwin Jordan
Publisher: MIT Press
ISBN: 9780262600422
Category : Artificial intelligence
Languages : en
Pages : 450
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Book Description
This book exemplifies the interplay between the general formal framework of graphical models and the exploration of new algorithm and architectures. The selections range from foundational papers of historical importance to results at the cutting edge of research. Graphical models use graphs to represent and manipulate joint probability distributions. They have their roots in artificial intelligence, statistics, and neural networks. The clean mathematical formalism of the graphical models framework makes it possible to understand a wide variety of network-based approaches to computation, and in particular to understand many neural network algorithms and architectures as instances of a broader probabilistic methodology. It also makes it possible to identify novel features of neural network algorithms and architectures and to extend them to more general graphical models.This book exemplifies the interplay between the general formal framework of graphical models and the exploration of new algorithms and architectures. The selections range from foundational papers of historical importance to results at the cutting edge of research. Contributors H. Attias, C. M. Bishop, B. J. Frey, Z. Ghahramani, D. Heckerman, G. E. Hinton, R. Hofmann, R. A. Jacobs, Michael I. Jordan, H. J. Kappen, A. Krogh, R. Neal, S. K. Riis, F. B. Rodríguez, L. K. Saul, Terrence J. Sejnowski, P. Smyth, M. E. Tipping, V. Tresp, Y. Weiss
Author: Leszek Rutkowski
Publisher: Springer Science & Business Media
ISBN: 3790819026
Category : Computers
Languages : en
Pages : 935
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Book Description
This volume presents new trends and developments in soft computing techniques. Topics include: neural networks, fuzzy systems, evolutionary computation, knowledge discovery, rough sets, and hybrid methods. It also covers various applications of soft computing techniques in economics, mechanics, medicine, automatics and image processing. The book contains contributions from internationally recognized scientists, such as Zadeh, Bubnicki, Pawlak, Amari, Batyrshin, Hirota, Koczy, Kosinski, Novák, S.-Y. Lee, Pedrycz, Raudys, Setiono, Sincak, Strumillo, Takagi, Usui, Wilamowski and Zurada. An excellent overview of soft computing methods and their applications.
Author: Ke-Lin Du
Publisher: Springer Nature
ISBN: 1447174526
Category : Mathematics
Languages : en
Pages : 988
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Book Description
This book provides a broad yet detailed introduction to neural networks and machine learning in a statistical framework. A single, comprehensive resource for study and further research, it explores the major popular neural network models and statistical learning approaches with examples and exercises and allows readers to gain a practical working understanding of the content. This updated new edition presents recently published results and includes six new chapters that correspond to the recent advances in computational learning theory, sparse coding, deep learning, big data and cloud computing. Each chapter features state-of-the-art descriptions and significant research findings. The topics covered include: • multilayer perceptron; • the Hopfield network; • associative memory models;• clustering models and algorithms; • t he radial basis function network; • recurrent neural networks; • nonnegative matrix factorization; • independent component analysis; •probabilistic and Bayesian networks; and • fuzzy sets and logic. Focusing on the prominent accomplishments and their practical aspects, this book provides academic and technical staff, as well as graduate students and researchers with a solid foundation and comprehensive reference on the fields of neural networks, pattern recognition, signal processing, and machine learning.
Author: Garcia Marquez, Fausto Pedro
Publisher: IGI Global
ISBN: 1799801071
Category : Computers
Languages : en
Pages : 478
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Book Description
As organizations continue to develop, there is an increasing need for technological methods that can keep up with the rising amount of data and information that is being generated. Machine learning is a tool that has become powerful due to its ability to analyze large amounts of data quickly. Machine learning is one of many technological advancements that is being implemented into a multitude of specialized fields. An extensive study on the execution of these advancements within professional industries is necessary. The Handbook of Research on Big Data Clustering and Machine Learning is an essential reference source that synthesizes the analytic principles of clustering and machine learning to big data and provides an interface between the main disciplines of engineering/technology and the organizational, administrative, and planning abilities of management. Featuring research on topics such as project management, contextual data modeling, and business information systems, this book is ideally designed for engineers, economists, finance officers, marketers, decision makers, business professionals, industry practitioners, academicians, students, and researchers seeking coverage on the implementation of big data and machine learning within specific professional fields.
Author: Olivier Pourret
Publisher: John Wiley & Sons
ISBN: 9780470994542
Category : Mathematics
Languages : en
Pages : 446
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Book Description
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.
