Author: Publisher:
ISBN:
Category :
Languages : en
Pages : 160
Book Description
Special Issue on Extreme Learning Machine with Uncertainty
Artificial Intelligence: Methodology, Systems, and Applications
Author: Gennady AgrePublisher: Springer
ISBN: 331910554X
Category : Computers
Languages : en
Pages : 317
Book Description
This book constitutes the refereed proceedings of the 16th International Conference on Artificial Intelligence: Methodology, Systems, and Applications, AIMSA 2014, held in Varna, Bulgaria in September 2014. The 14 revised full papers and 9 short papers presented were carefully reviewed and selected from 53 submissions. The range of topics is almost equally broad, from traditional areas such as computer vision and natural language processing to emerging areas such as mining the behavior of Web-based communities.
Multistrategy Learning
Author: Ryszard S. MichalskiPublisher: Springer Science & Business Media
ISBN: 9780792393740
Category : Computers
Languages : en
Pages : 174
Book Description
Most machine learning research has been concerned with the development of systems that implememnt one type of inference within a single representational paradigm. Such systems, which can be called monostrategy learning systems, include those for empirical induction of decision trees or rules, explanation-based generalization, neural net learning from examples, genetic algorithm-based learning, and others. Monostrategy learning systems can be very effective and useful if learning problems to which they are applied are sufficiently narrowly defined. Many real-world applications, however, pose learning problems that go beyond the capability of monostrategy learning methods. In view of this, recent years have witnessed a growing interest in developing multistrategy systems, which integrate two or more inference types and/or paradigms within one learning system. Such multistrategy systems take advantage of the complementarity of different inference types or representational mechanisms. Therefore, they have a potential to be more versatile and more powerful than monostrategy systems. On the other hand, due to their greater complexity, their development is significantly more difficult and represents a new great challenge to the machine learning community. Multistrategy Learning contains contributions characteristic of the current research in this area.
Safety, Reliability, Risk and Life-Cycle Performance of Structures and Infrastructures
Author: George DeodatisPublisher: CRC Press
ISBN: 1315884887
Category : Technology & Engineering
Languages : en
Pages : 1112
Book Description
Safety, Reliability, Risk and Life-Cycle Performance of Structures and Infrastructures contains the plenary lectures and papers presented at the 11th International Conference on STRUCTURAL SAFETY AND RELIABILITY (ICOSSAR2013, New York, NY, USA, 16-20 June 2013), and covers major aspects of safety, reliability, risk and life-cycle performance of str
Machine Learning for Energy Systems
Author: Denis SidorovPublisher: MDPI
ISBN: 3039433822
Category : Technology & Engineering
Languages : en
Pages : 272
Book Description
This volume deals with recent advances in and applications of computational intelligence and advanced machine learning methods in power systems, heating and cooling systems, and gas transportation systems. The optimal coordinated dispatch of the multi-energy microgrids with renewable generation and storage control using advanced numerical methods is discussed. Forecasting models are designed for electrical insulator faults, the health of the battery, electrical insulator faults, wind speed and power, PV output power and transformer oil test parameters. The loads balance algorithm for an offshore wind farm is proposed. The information security problems in the energy internet are analyzed and attacked using information transmission contemporary models, based on blockchain technology. This book will be of interest, not only to electrical engineers, but also to applied mathematicians who are looking for novel challenging problems to focus on.
Special Issue: Uncertainty in Artificial Intelligence and Databases
Author: Hydro-Environmental Analysis
Author: James L. MartinPublisher: CRC Press
ISBN: 1138000868
Category : Science
Languages : en
Pages : 5742
Book Description
Focusing on fundamental principles, Hydro-Environmental Analysis: Freshwater Environments presents in-depth information about freshwater environments and how they are influenced by regulation. It provides a holistic approach, exploring the factors that impact water quality and quantity, and the regulations, policy and management methods that are necessary to maintain this vital resource. It offers a historical viewpoint as well as an overview and foundation of the physical, chemical, and biological characteristics affecting the management of freshwater environments. The book concentrates on broad and general concepts, providing an interdisciplinary foundation. The author covers the methods of measurement and classification; chemical, physical, and biological characteristics; indicators of ecological health; and management and restoration. He also considers common indicators of environmental health; characteristics and operations of regulatory control structures; applicable laws and regulations; and restoration methods. The text delves into rivers and streams in the first half and lakes and reservoirs in the second half. Each section centers on the characteristics of those systems and methods of classification, and then moves on to discuss the physical, chemical, and biological characteristics of each. In the section on lakes and reservoirs, it examines the characteristics and operations of regulatory structures, and presents the methods commonly used to assess the environmental health or integrity of these water bodies. It also introduces considerations for restoration, and presents two unique aquatic environments: wetlands and reservoir tailwaters. Written from an engineering perspective, the book is an ideal introduction to the aquatic and limnological sciences for students of environmental science, as well as students of environmental engineering. It also serves as a reference for engineers and scientists involved in the management, regulation, or restoration of freshwater environments.
Principles of Uncertainty
Author: Joseph B. KadanePublisher: CRC Press
ISBN: 1351683365
Category : Mathematics
Languages : en
Pages : 525
Book Description
Praise for the first edition: Principles of Uncertainty is a profound and mesmerising book on the foundations and principles of subjectivist or behaviouristic Bayesian analysis. ... the book is a pleasure to read. And highly recommended for teaching as it can be used at many different levels. ... A must-read for sure!—Christian Robert, CHANCE It's a lovely book, one that I hope will be widely adopted as a course textbook. —Michael Jordan, University of California, Berkeley, USA Like the prize-winning first edition, Principles of Uncertainty, Second Edition is an accessible, comprehensive text on the theory of Bayesian Statistics written in an appealing, inviting style, and packed with interesting examples. It presents an introduction to the subjective Bayesian approach which has played a pivotal role in game theory, economics, and the recent boom in Markov Chain Monte Carlo methods. This new edition has been updated throughout and features new material on Nonparametric Bayesian Methods, the Dirichlet distribution, a simple proof of the central limit theorem, and new problems. Key Features: First edition won the 2011 DeGroot Prize Well-written introduction to theory of Bayesian statistics Each of the introductory chapters begins by introducing one new concept or assumption Uses "just-in-time mathematics"—the introduction to mathematical ideas just before they are applied
Problem Solving and Uncertainty Modeling through Optimization and Soft Computing Applications
Author: Saxena, PratikshaPublisher: IGI Global
ISBN: 1466698861
Category : Mathematics
Languages : en
Pages : 424
Book Description
Optimization techniques have developed into a modern-day solution for real-world problems in various industries. As a way to improve performance and handle issues of uncertainty, optimization research becomes a topic of special interest across disciplines. Problem Solving and Uncertainty Modeling through Optimization and Soft Computing Applications presents the latest research trends and developments in the area of applied optimization methodologies and soft computing techniques for solving complex problems. Taking a multi-disciplinary approach, this critical publication is an essential reference source for engineers, managers, researchers, and post-graduate students.
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