[PDF] Modeling Uncertainty With Fuzzy Logic eBook

Author : Asli Celikyilmaz
Publisher : Springer Science & Business Media
Page : 443 pages
File Size : 46,33 MB
Release : 2009-04-08
Category : Computers
ISBN : 3540899235

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The world we live in is pervaded with uncertainty and imprecision. Is it likely to rain this afternoon? Should I take an umbrella with me? Will I be able to find parking near the campus? Should I go by bus? Such simple questions are a c- mon occurrence in our daily lives. Less simple examples: What is the probability that the price of oil will rise sharply in the near future? Should I buy Chevron stock? What are the chances that a bailout of GM, Ford and Chrysler will not s- ceed? What will be the consequences? Note that the examples in question involve both uncertainty and imprecision. In the real world, this is the norm rather than exception. There is a deep-seated tradition in science of employing probability theory, and only probability theory, to deal with uncertainty and imprecision. The mon- oly of probability theory came to an end when fuzzy logic made its debut. H- ever, this is by no means a widely accepted view. The belief persists, especially within the probability community, that probability theory is all that is needed to deal with uncertainty. To quote a prominent Bayesian, Professor Dennis Lindley, “The only satisfactory description of uncertainty is probability.

Author : Rómulo Antão
Publisher : Springer
Page : 136 pages
File Size : 36,34 MB
Release : 2017-07-23
Category : Technology & Engineering
ISBN : 9811046336

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This book focuses on a particular domain of Type-2 Fuzzy Logic, related to process modeling and control applications. It deepens readers’understanding of Type-2 Fuzzy Logic with regard to the following three topics: using simpler methods to train a Type-2 Takagi-Sugeno Fuzzy Model; using the principles of Type-2 Fuzzy Logic to reduce the influence of modeling uncertainties on a locally linear n-step ahead predictor; and developing model-based control algorithms according to the Generalized Predictive Control principles using Type-2 Fuzzy Sets. Throughout the book, theory is always complemented with practical applications and readers are invited to take their learning process one step farther and implement their own applications using the algorithms’ source codes (provided). As such, the book offers avaluable referenceguide for allengineers and researchers in the field ofcomputer science who are interested in intelligent systems, rule-based systems and modeling uncertainty.

Author : Bilal M. Ayyub
Publisher : Springer Science & Business Media
Page : 376 pages
File Size : 17,62 MB
Release : 2012-12-06
Category : Computers
ISBN : 146155473X

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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.

Author : Bilal Ayyub
Publisher : Springer
Page : 371 pages
File Size : 13,64 MB
Release : 2011-09-28
Category : Computers
ISBN : 9781461554745

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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.

Author : Bilal M. Ayyub
Publisher : World Scientific
Page : 382 pages
File Size : 28,96 MB
Release : 1997
Category : Technology & Engineering
ISBN : 9810231342

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This book gives an overview of the current state of uncertainty modeling in vibration, control, and fuzzy analysis of structural and mechanical systems. It is a coherent compendium written by leading experts and offers the reader a sampling of exciting research areas in several fast-growing branches in this field. Uncertainty modeling and analysis are becoming an integral part of system definition and modeling in many fields. The book consists of ten chapters that report the work of researchers, scientists and engineers on theoretical developments and diversified applications in engineering systems. They deal with modeling for vibration, control, and fuzzy analysis of structural and mechanical systems under uncertain conditions. The book designed for readers who are familiar with the fundamentals and wish to study a particular topic or use the book as an authoritative reference. It gives readers a sophisticated toolbox for tackling modeling problems in mechanical and structural systems in real-world situations. The book is part of a series on Stability, Vibration and Control of Structures, and provides vital information in these areas.

Author : Ondrej Linda
Publisher :
Page : 0 pages
File Size : 16,63 MB
Release : 2012
Category : Fuzzy logic
ISBN :

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Type-1 Fuzzy Logic (T1 FL) has been successfully applied in various engineering areas over the past 40 years. This fact can be attributed to the ability of T1 FL to cope with the linguistic uncertainty originating in the imprecise and vague meaning of words. However, when various kinds of data uncertainties are encountered, the performance of TI FL based systems can deteriorate. To address this issue, the concept of Type-2 (T2) FL was proposed by Lofti Zadeh in 1975 as an extension to T1 FL. The fundamental difference between T1 and T2 FL is in the model of individual Fuzzy Sets (FSs), where T2 FSs employ membership degrees that are themselves fuzzy. T2 FL has experienced a widespread of research interest in the past decade and it constitutes evolving and very active area of research. Some of the major challenges of the currently developed theory of T2 FL can be identified as follows: i) high computational complexity of T2 FL algorithms, ii) lack of established design methodology for creating robust T2 FL systems, and iii) lack of understanding of the uncertainty modeling capabilities of T2 FL systems.

Author : Cengiz Kahraman
Publisher : World Scientific
Page : 1373 pages
File Size : 46,74 MB
Release : 2012-08-10
Category : Computers
ISBN : 9814417750

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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.

Author : Jerry M. Mendel
Publisher : Springer
Page : 701 pages
File Size : 33,71 MB
Release : 2017-05-17
Category : Technology & Engineering
ISBN : 3319513702

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The second edition of this textbook provides a fully updated approach to fuzzy sets and systems that can model uncertainty — i.e., “type-2” fuzzy sets and systems. The author demonstrates how to overcome the limitations of classical fuzzy sets and systems, enabling a wide range of applications from time-series forecasting to knowledge mining to control. In this new edition, a bottom-up approach is presented that begins by introducing classical (type-1) fuzzy sets and systems, and then explains how they can be modified to handle uncertainty. The author covers fuzzy rule-based systems – from type-1 to interval type-2 to general type-2 – in one volume. For hands-on experience, the book provides information on accessing MatLab and Java software to complement the content. The book features a full suite of classroom material.

Author : Zengchang Qin
Publisher : Springer
Page : 303 pages
File Size : 13,2 MB
Release : 2014-10-30
Category : Computers
ISBN : 3642412513

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Machine learning and data mining are inseparably connected with uncertainty. The observable data for learning is usually imprecise, incomplete or noisy. Uncertainty Modeling for Data Mining: A Label Semantics Approach introduces 'label semantics', a fuzzy-logic-based theory for modeling uncertainty. Several new data mining algorithms based on label semantics are proposed and tested on real-world datasets. A prototype interpretation of label semantics and new prototype-based data mining algorithms are also discussed. This book offers a valuable resource for postgraduates, researchers and other professionals in the fields of data mining, fuzzy computing and uncertainty reasoning. Zengchang Qin is an associate professor at the School of Automation Science and Electrical Engineering, Beihang University, China; Yongchuan Tang is an associate professor at the College of Computer Science, Zhejiang University, China.