Fundamentals of Relational Database Management Systems, Sumathi S., Esakkirajan S.
Автор: Ogiela, Lidia Dominika Название: Cognitive Information Systems in Management Sciences ISBN: 0128038039 ISBN-13(EAN): 9780128038031 Издательство: Elsevier Science Рейтинг: Цена: 9713 р. Наличие на складе: Поставка под заказ.
Описание: Cognitive Information Systems in Management Sciences summarizes the body of work in this area, taking an analytical approach to interpreting the data, while also providing an approach that can be used for practical implementation in the fields of computing, economics, and engineering. . Using numerous illustrative examples, and following both theoretical and practical results, Dr. Lidia Ogiela discusses the concepts and principles of cognitive information systems, the relationship between intelligent computer data analysis, and how to utilize computational intelligent approaches to enhance information retrieval. . Real world implantation use cases round out the book, with valuable scenarios covering management science, computer science, and engineering. Indexing: The books of this series are submitted to EI-Compendex and SCOPUS
Автор: Aiguier Название: Complex Systems Design & Management ISBN: 3642156533 ISBN-13(EAN): 9783642156533 Издательство: Springer Рейтинг: Цена: 32291 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A book that contains various refereed papers that were accepted to the `Complex Systems Design & Management` (CSDM 2010) international conference that took place in Paris (France), October 27 - 29, 2010.
Автор: Ulises Cort?s; Manel Poch (Eds.) Название: Advanced Agent-Based Environmental Management Systems ISBN: 3764388978 ISBN-13(EAN): 9783764388973 Издательство: Springer Рейтинг: Цена: 7323 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Presents ways in which adaptive information technologies, techniques, protocols and architectures, such as software agent technologies and multi-agent systems, can be used to support the development of real-world agent-based systems in the area of e-Environment.
Описание: Human error plays a significant role in many accidents involving safety-critical systems, and it is now a standard requirement in both the US and Europe for Human Factors (HF) to be taken into account in system design and safety assessment. This book will be an essential guide for anyone who uses HF in their everyday work, providing them with consistent and ready-to-use procedures and methods that can be applied to real-life problems. The first part of the book looks at the theoretical framework, methods and techniques that the engineer or safety analyst needs to use when working on a HF-related project. The second part presents four case studies that show the reader how the above framework and guidelines work in practice. The case studies are based on real-life projects carried out by the author for a major European railway system, and in collaboration with international companies such as the International Civil Aviation Organisation, Volvo, Daimler-Chrysler and FIAT.
Описание: This book presents a systematic study on the inherent complexity in fuzzy systems, resulting from the large number and the poor transparency of the fuzzy rules. The study uses a novel approach for complexity management, aimed at compressing the fuzzy rule base by removing the redundancy while preserving the solution. The compression is based on formal methods for presentation, manipulation, transformation and simplification of fuzzy rule bases, which are illustrated by algorithms as well as results from numerous examples and two case studies. The results are directly applicable or easily extendable to a wide class of fuzzy systems and detailed benchmarks for expanding these systems to new areas such as fuzzy networks and fuzzy multi-agent systems are introduced. The intended readers are people from both academia and industry, who would be interested in building and implementing advanced fuzzy systems.
Описание: The Handbook of Defeasible Reasoning and Uncertainty Management Systems is unique in its masterly survey of the computational and algorithmic problems of systems of applied reasoning. The various theoretical and modelling aspects of defeasible reasoning were dealt with in the first four volumes, and Volume 5 now turns to the algorithmic aspect. Topics covered include: Computation in valuation algebras; consequence finding algorithms; possibilistic logic; probabilistic argumentation systems, networks and satisfiability; algorithms for imprecise probabilities, for Dempster-Shafer, and network based decisions.
Описание: Describes and reviews the concept, process and framework of modern maintenance management of complex systems; focusing on modern modelling tools for maintenance planning and scheduling. This book is suitable for engineers and professionals involved in maintenance management, maintenance engineering, operations management, and quality.
Описание: This last volume of the Handbook of Defeasible Reasoning and Uncertainty Management Systems is - together with Volume 6 - devoted to the topics Reasoning and Dynamics, covering both the topics of "Dynamics of Reasoning", where reasoning is viewed as a process, and "Reasoning about Dynamics", which must be understood as pertaining to how both designers of, and agents within dynamic systems may reason about these systems. The present volume presents work done in this context and is more focused on "reasoning about dynamics", viz. how (human and artificial) agents reason about (systems in) dynamic environments in order to control them. In particular modelling frameworks and generic agent models for modelling these dynamic systems and formal approaches to these systems such as logics for agents and formal means to reason about agent-based and compositional systems, and action & change more in general are considered.
Описание: This volume is focused on the dynamics of reasoning processes. It covers both the topics of 'Dynamics of Reasoning', where reasoning is viewed as a process, and 'Reasoning about Dynamics', which must be understood as pertaining to how both designers of, and agents within dynamic systems may reason about these systems. In this volume real-life applications of the modelling techniques are also considered, as the research during the DRUMS (Defeasible Reasoning and Uncertainty Management Systems) project was aimed at bridging the gap between theory and practice. In order to give the book a broader perspective, a number of well-known researchers outside the project but working on similar topics, have been invited to contribute as well.
Описание: Focuses on the problem of managing the resource allocation taking place within the operational context of many contemporary technological applications, including flexibly automated production systems, automated railway and/or monorail transportation systems, electronic workflow management systems, and business transaction supporting systems.
Описание: Describes advanced statistical modeling and knowledge representation techniques for an area of machine learning and probabilistic reasoning. This volume includes introductory material, tutorials for different proposed approaches, and applications.
Автор: M?ller Название: Relational Knowledge Discovery ISBN: 052112204X ISBN-13(EAN): 9780521122047 Издательство: Cambridge Academ Рейтинг: Цена: 4140 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: What is knowledge and how is it represented? This book focuses on the idea of formalising knowledge as relations, interpreting knowledge represented in databases or logic programs as relational data and discovering new knowledge by identifying hidden and defining new relations. After a brief introduction to representational issues, the author develops a relational language for abstract machine learning problems. He then uses this language to discuss traditional methods such as clustering and decision tree induction, before moving onto two previously underestimated topics that are just coming to the fore: rough set data analysis and inductive logic programming. Its clear and precise presentation is ideal for undergraduate computer science students. The book will also interest those who study artificial intelligence or machine learning at the graduate level. Exercises are provided and each concept is introduced using the same example domain, making it easier to compare the individual properties of different approaches.
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