Uncertainty Modeling in Knowledge Engineering and Decision Making

Uncertainty Modeling in Knowledge Engineering and Decision Making
Title Uncertainty Modeling in Knowledge Engineering and Decision Making PDF eBook
Author
Publisher World Scientific
Pages 1373
Release 2012
Genre Computers
ISBN 9814417742

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FLINS, originally an acronym for Fuzzy Logic and Intelligent Technologies in Nuclear Science, is now extended to Computational Intelligence for applied research. The contributions to the 10th of FLINS conference cover state-of-the-art research, development, and technology for computational intelligence systems, both from the foundations and the applications points-of-view. Sample Chapter(s). Foreword (55 KB). Evaluation of Manufacturing Technology of Photovoltaic Cells (124 KB). Contents: Decision Making and Decision Support Systems; Uncertainty Modeling; Foundations of Computational Intelligence; Statistics, Data Analysis and Data Mining; Intelligent Information Processing; Productivity and Reliability; Applied Research. Readership: Graduate students, researchers, and academics in artificial intelligence/machine learning, information management, decision sciences, databases/information sciences and fuzzy logic.

Uncertainty Analysis in Engineering and Sciences: Fuzzy Logic, Statistics, and Neural Network Approach

Uncertainty Analysis in Engineering and Sciences: Fuzzy Logic, Statistics, and Neural Network Approach
Title Uncertainty Analysis in Engineering and Sciences: Fuzzy Logic, Statistics, and Neural Network Approach PDF eBook
Author Bilal Ayyub
Publisher Springer Science & Business Media
Pages 414
Release 1997-10-31
Genre Computers
ISBN 9780792380306

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Uncertainty has been of concern to engineers, managers and . scientists for many centuries. In management sciences there have existed definitions of uncertainty in a rather narrow sense since the beginning of this century. In engineering and uncertainty has for a long time been considered as in sciences, however, synonymous with random, stochastic, statistic, or probabilistic. Only since the early sixties views on uncertainty have ~ecome more heterogeneous and more tools to model uncertainty than statistics have been proposed by several scientists. The problem of modeling uncertainty adequately has become more important the more complex systems have become, the faster the scientific and engineering world develops, and the more important, but also more difficult, forecasting of future states of systems have become. The first question one should probably ask is whether uncertainty is a phenomenon, a feature of real world systems, a state of mind or a label for a situation in which a human being wants to make statements about phenomena, i. e. , reality, models, and theories, respectively. One cart also ask whether uncertainty is an objective fact or just a subjective impression which is closely related to individual persons. Whether uncertainty is an objective feature of physical real systems seems to be a philosophical question. This shall not be answered in this volume.

Uncertainty Modelling In Knowledge Engineering And Decision Making - Proceedings Of The 12th International Flins Conference (Flins 2016)

Uncertainty Modelling In Knowledge Engineering And Decision Making - Proceedings Of The 12th International Flins Conference (Flins 2016)
Title Uncertainty Modelling In Knowledge Engineering And Decision Making - Proceedings Of The 12th International Flins Conference (Flins 2016) PDF eBook
Author Xianyi Zeng
Publisher World Scientific
Pages 1207
Release 2016-07-14
Genre Computers
ISBN 9813146982

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FLINS, originally an acronym for Fuzzy Logic and Intelligent Technologies in Nuclear Science, is now extended to include Computational Intelligence for applied research. The contributions to the 12th of FLINS conference cover state-of-the-art research, development, and technology for computational intelligence systems, both from the foundations and the applications points-of-view.

Mathematics of Uncertainty Modeling in the Analysis of Engineering and Science Problems

Mathematics of Uncertainty Modeling in the Analysis of Engineering and Science Problems
Title Mathematics of Uncertainty Modeling in the Analysis of Engineering and Science Problems PDF eBook
Author Chakraverty, S.
Publisher IGI Global
Pages 442
Release 2014-01-31
Genre Mathematics
ISBN 1466649925

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"This book provides the reader with basic concepts for soft computing and other methods for various means of uncertainty in handling solutions, analysis, and applications"--Provided by publisher.

Data Science And Knowledge Engineering For Sensing Decision Support - Proceedings Of The 13th International Flins Conference

Data Science And Knowledge Engineering For Sensing Decision Support - Proceedings Of The 13th International Flins Conference
Title Data Science And Knowledge Engineering For Sensing Decision Support - Proceedings Of The 13th International Flins Conference PDF eBook
Author Jun Liu
Publisher World Scientific
Pages 1625
Release 2018-07-30
Genre Computers
ISBN 9813273240

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FLINS, originally an acronym for Fuzzy Logic and Intelligent Technologies in Nuclear Science, is now extended to include Computational Intelligence for applied research. The contributions of the FLINS conference cover state-of-the-art research, development, and technology for computational intelligence systems, with special focuses on data science and knowledge engineering for sensing decision support, both from the foundations and the applications points-of-view.

Uncertainty Modeling in Knowledge Engineering and Decision Making

Uncertainty Modeling in Knowledge Engineering and Decision Making
Title Uncertainty Modeling in Knowledge Engineering and Decision Making PDF eBook
Author Cengiz Kahraman
Publisher
Pages 278
Release 2014
Genre
ISBN

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What Every Engineer Should Know About Decision Making Under Uncertainty

What Every Engineer Should Know About Decision Making Under Uncertainty
Title What Every Engineer Should Know About Decision Making Under Uncertainty PDF eBook
Author John X. Wang
Publisher CRC Press
Pages 342
Release 2002-07-01
Genre Technology & Engineering
ISBN 9780203910757

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Covering the prediction of outcomes for engineering decisions through regression analysis, this succinct and practical reference presents statistical reasoning and interpretational techniques to aid in the decision making process when faced with engineering problems. The author emphasizes the use of spreadsheet simulations and decision trees as important tools in the practical application of decision making analyses and models to improve real-world engineering operations. He offers insight into the realities of high-stakes engineering decision making in the investigative and corporate sectors by optimizing engineering decision variables to maximize payoff.