Advances in Probabilistic Databases for Uncertain Information Management, Zongmin Ma; Li Yan

Автор: Thrun, Sebastian
Название: Probabilistic robotics
ISBN: 0262201623 ISBN-13(EAN): 9780262201629
Издательство: MIT Press
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Цена: 95930.00 T
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Описание:

An introduction to the techniques and algorithms of the newest field in robotics.

Probabilistic robotics is a new and growing area in robotics, concerned with perception and control in the face of uncertainty. Building on the field of mathematical statistics, probabilistic robotics endows robots with a new level of robustness in real-world situations. This book introduces the reader to a wealth of techniques and algorithms in the field. All algorithms are based on a single overarching mathematical foundation. Each chapter provides example implementations in pseudo code, detailed mathematical derivations, discussions from a practitioner's perspective, and extensive lists of exercises and class projects. The book's Web site, www.probabilistic-robotics.org, has additional material. The book is relevant for anyone involved in robotic software development and scientific research. It will also be of interest to applied statisticians and engineers dealing with real-world sensor data.

Автор: Christian Servin; Vladik Kreinovich
Название: Propagation of Interval and Probabilistic Uncertainty in Cyberinfrastructure-related Data Processing and Data Fusion
ISBN: 3319385879 ISBN-13(EAN): 9783319385877
Издательство: Springer
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Цена: 87060.00 T
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Описание: On various examples ranging from geosciences to environmental sciences, thisbook explains how to generate an adequate description of uncertainty, how to justifysemiheuristic algorithms for processing uncertainty, and how to make these algorithmsmore computationally efficient.

Автор: J?rgen Sturm
Название: Approaches to Probabilistic Model Learning for Mobile Manipulation Robots
ISBN: 3642437141 ISBN-13(EAN): 9783642437144
Издательство: Springer
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Цена: 113180.00 T
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Описание: This book presents novel learning techniques that enable mobile platforms with one or more robotic manipulators to autonomously adapt to new or changing situations.

Автор: Weiru Liu
Название: Propositional, Probabilistic and Evidential Reasoning
ISBN: 3790824933 ISBN-13(EAN): 9783790824933
Издательство: Springer
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Цена: 130430.00 T
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Описание: This facilitates purely symbolic reasoning using the possible worlds and numeric reasoning via the probabilities of those possible worlds. The consequence is a unified mechanism which includes both symbolic and numeric mechanisms as special cases.

Автор: Zongmin Ma; Li Yan
Название: Advances in Probabilistic Databases for Uncertain Information Management
ISBN: 3642375081 ISBN-13(EAN): 9783642375088
Издательство: Springer
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Цена: 121890.00 T
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Описание:

1 Research in Probabilistic Spatiotemporal Databases:
The SPOT Framework.-

2 A Probabilistic Object-Oriented Database Model with
Fuzzy Measures.-

3 Probabilistic XML: Models and Complexity.-

4 Uncertain Data: Representations, Query Processing,
and Applications.-

5 A Theoretically-Sound Approach for OLAPing Uncertain
and Imprecise Multidimensional Data Streams.-

6 Tractable Probabilistic Description Logic Programs.

Название: Probabilistic prognostics and health management of energy systems.
ISBN: 331955851X ISBN-13(EAN): 9783319558516
Издательство: Springer
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Цена: 111790.00 T
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Описание: This book proposes the formulation of an efficient methodology that estimates energy system uncertainty and predicts Remaining Useful Life (RUL) accurately with significantly reduced RUL prediction uncertainty.

Автор: Milan Studeny
Название: Probabilistic Conditional Independence Structures
ISBN: 1849969485 ISBN-13(EAN): 9781849969482
Издательство: Springer
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Цена: 130430.00 T
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Описание: Probabilistic Conditional Independence Structures provides the mathematical description of probabilistic conditional independence structures; The monograph presents the methods of structural imsets and supermodular functions, and deals with independence implication and equivalence of structural imsets.

Автор: Hiromitsu Kumamoto
Название: Satisfying Safety Goals by Probabilistic Risk Assessment
ISBN: 1849966419 ISBN-13(EAN): 9781849966412
Издательство: Springer
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Цена: 130590.00 T
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Описание: This book is a methodological approach to the goal-based safety design procedure that will soon be an international requirement. This is the first single volume book to describe how to satisfy safety goals by modern reliability engineering. Its focus is on the quantitative aspects of the international standards using a methodological approach.

Автор: Ben Goertzel; Matthew Ikl?; Izabela Freire Goertze
Название: Probabilistic Logic Networks
ISBN: 1441945784 ISBN-13(EAN): 9781441945785
Издательство: Springer
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Цена: 144410.00 T
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Описание: This comprehensive book describes Probabilistic Logic Networks (PLN), a novel conceptual, mathematical and computational approach to uncertain inference. A broad scope of reasoning types are considered.

Автор: Enrique Castillo; Jose M. Gutierrez; Ali S. Hadi
Название: Expert Systems and Probabilistic Network Models
ISBN: 1461274818 ISBN-13(EAN): 9781461274810
Издательство: Springer
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Цена: 111790.00 T
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Описание: Artificial intelligence and expert systems have seen a great deal of research in recent years, much of which has been devoted to methods for incorporating uncertainty into models. This book is devoted to providing a thorough and up-to-date survey of this field for researchers and students.

Автор: Ivan Kramosil
Название: Probabilistic Analysis of Belief Functions
ISBN: 1461351456 ISBN-13(EAN): 9781461351450
Издательство: Springer
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Цена: 93160.00 T
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Автор: Paul Kree; W. Wedig
Название: Probabilistic Methods in Applied Physics
ISBN: 3662140063 ISBN-13(EAN): 9783662140062
Издательство: Springer
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Цена: 46570.00 T
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Описание: This book is an outcome of a European collaboration on applications of stochastical methods to problems of science and engineering. In particular the volume covers: simulation, stability theory, Lyapounov exponents, stochastic modelling, statistics on trajectories, parametric stochastic control, Fokker Planck equations, and Wiener filtering.