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Books on the topic 'Fuzzy processes'

Author: Grafiati
Published: 4 June 2021
Last updated: 9 February 2022

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1

1959-, Nishizaki Ichiro, and Katagiri Hideki, eds. Fuzzy stochastic multiobjective programming. New York: Springer, 2011.

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2

O, Esogbue Augustine, ed. Decision criteria and optimal inventory processes. Boston: Kluwer Academic, 1999.

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3

Kuiński, Jacek. Rozmyte procesy gałązkowe. Poznań: Wydawn. Politechniki Poznańskiej, 1988.

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4

Meier, Andreas, Edy Portmann, Kilian Stoffel, and Luis Terán, eds. The Application of Fuzzy Logic for Managerial Decision Making Processes. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-54048-1.

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5

Liu, Baoding. Decision Criteria and Optimal Inventory Processes. Boston, MA: Springer US, 1999.

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6

Abdel-Kader, Magdy G. Investment decisions in advanced manufacturing technology: A fuzzy set theory approach. Brookfield, VT: Ashgate Pub., 1998.

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7

International Conference on Intelligent Processing and Manufacturing of Materials (2nd 1999 Honolulu, Hawaii). Proceedings of the Second International Conference on Intelligent Processing and Manufacturing of Materials: IPMM'99 : Hilton Hawaiian Village Hotel, Honolulu, Hawaii, July 10-15, 1999. Edited by Meech John A. Piscataway, N.J: IEEE, 1999.

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8

Vasil'eva, Natal'ya. Mathematical models in the management of copper production: ideas, methods, examples. ru: INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1014071.

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Presents the current status in modelling of metallurgical processes considered by the model the mathematical model used in the description of the processes of copper production and their classification. Set out a system of methods and models in the field of mathematical modeling of technological processes, including balance sheet, statistics, optimization models, forecasting models and predictive models. For specific technological processes are developed: the model of the balance of the cycle of pyrometallurgical production of copper, polynomial model for prediction of matte composition on the basis of the passive experiment, predictive model of quantitative estimation of the copper content in the matte based on fuzzy logic. Of interest to students, postgraduates, teachers of technical universities, engineers and research workers who use mathematical methods for processing of data of laboratory and industrial experiments.
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9

Aliev, R. A. Fuzzy process control and knowledge engineering in petrochemical and robotic manufacturing. Köln: Verlag TÜV Rheinland, 1991.

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10

Karr, C. L. An adaptive system for process control. [Washington, D.C.?]: U.S. Dept. of the Interior, Bureau of Mines, 1995.

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11

Karr, C. L. An adaptive system for process control. [Washington, D.C.?]: U.S. Dept. of the Interior, Bureau of Mines, 1995.

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12

Kaviani, Alireza S. A fuzzy logic approach for processor allocation in application scheduling of multiprocessors. Ottawa: National Library of Canada, 1993.

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13

Hasemann, Jorg-Michael. Planning and monitoring in dynamic environments. Espoo, Finland: VTT, Technical Research Centre of Finland, 1995.

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14

Adrian, Axel. Grundprobleme einer juristischen (gemeinschaftsrechtlichen) Methodenlehre: Die begrifflichen und ("fuzzy"-)logischen Grenzen der Befugnisnormen zur Rechtsprechung des Europäischen Gerichtshofes und die Maastricht-Entscheidung des Bundesverfassungsgerichtes. Berlin: Duncker & Humblot, 2009.

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15

Roman, Słowiński, and Teghem Jacques 1948-, eds. Stochastic versus fuzzy approaches to multiobjective mathematical programming under uncertainty. Dordrecht: Kluwer Academic, 1990.

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16

Willson, Ian Alexander *. Fuzzy sets and uncertain choice processes: an empirical test of models. 1991.

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17

Ernest, Czogała, and Hirota Kaoru, eds. Probabilistic sets: Fuzzy and stochastic approach to decision, control and recognition processes. Köln: TUV Rheinland, 1986.

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18

Dostál, Petr, and Chia-Yang Lin. Business Applications of Fuzzy Logic. Edited by Shu-Heng Chen, Mak Kaboudan, and Ye-Rong Du. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780199844371.013.14.

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The chapter focuses on the use of fuzzy logic, or soft computing, among the different methods used as supports for decision making in business applications. The processes are focused on private corporate attempts at making money or decreasing expenses; therefore, the details of applications, successful or not, are not published very often. Fuzzy logic helps in decentralization of decisionmaking processes that are to be standardized, reproduced, and documented. Fuzzy logic plays very important roles, especially in business, because it helps reduce costs. It differs from conventional (hard) computing in that it is tolerant of imprecision, uncertainty, partial truth, and approximation. In effect, the role model for fuzzy logic is the human mind. The guiding principle of fuzzy logic is to exploit this tolerance to achieve tractability, robustness, and low solution cost.
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19

Singh, Bhupinder, Jagdeep Singh, and Harwinder Singh. Prioritization of Failure Modes in Manufacturing Processes: A Fuzzy Logic-Based Approach. Emerald Publishing Limited, 2020.

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20

Singh, Bhupinder, Jagdeep Singh, and Harwinder Singh. Prioritization of Failure Modes in Manufacturing Processes: A Fuzzy Logic-Based Approach. Emerald Publishing Limited, 2020.

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21

Singh, Bhupinder, Jagdeep Singh, and Harwinder Singh. Prioritization of Failure Modes in Manufacturing Processes: A Fuzzy Logic-Based Approach. Emerald Publishing Limited, 2020.

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22

Sessa, Salvatore, and Ferdinando Di Martino. Fuzzy Transforms for Image Processing and Data Analysis: Core Concepts, Processes and Applications. Springer, 2020.

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23

Tatjewski, Piotr. Advanced Control of Industrial Processes: Structures and Algorithms. Springer, 2010.

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24

Meier, Andreas, Edy Portmann, Kilian Stoffel, and Luis Terán. The Application of Fuzzy Logic for Managerial Decision Making Processes: Latest Research and Case Studies. Springer, 2017.

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25

Meier, Andreas, Edy Portmann, Kilian Stoffel, and Luis Terán. The Application of Fuzzy Logic for Managerial Decision Making Processes: Latest Research and Case Studies. Springer, 2018.

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26

Advanced Control of Industrial Processes: Structures and Algorithms (Advances in Industrial Control). Springer, 2006.

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27

R, Parsaei H., and Jamshidi Mohammad, eds. Design and implementation of intelligent manufacturing systems: From expert systems, neural networks, to fuzzy logic. Upper Saddle River, N.J: Prentice Hall PTR, 1995.

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28

Cosma, Cristina. Development of a systematic approach for uncertainty assessment in scheduling multiple repetitive construction processes by using fuzzy set theory. 2003.

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29

(Editor), H. F. Chen, K. J. Hunt (Editor), Y. Hashimoto (Editor), I. Farkas (Editor), and H. Murase (Editor), eds. Proceedings of the 14th World Congress of IFAC (18-Volume Set) : Fuzzy and Neural Systems II, Control in Agricultural Processes (Proceedings of the 14th World Congress of Ifac). Pergamon, 1999.

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30

1935-, Lasker G. E., International Institute for Advanced Studies in Systems Research and Cybernetics., and International Conference on Systems Research, Informatics and Cybernetics (7th : 1994 : Baden-Baden, Germany), eds. Advances in computer cybernetics: Intelligent information systems, knowledge transmission and representation, software development, self-organizing production processes, fuzzy systems, virtual environment, advanced computer graphics, synesthetic art, advanced simulation, neural networks, intelligent control, advanced robotics. Windsor, Ont: International Institute for Advanced Studies in Systems Research and Cybernetics, 1995.

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31

Holzapfel, Frank G. Fuzzy logic control of an inverted pendulum with vision feedback. 1994.

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32

1939-, Tzafestas S. G., and Venetsanopoulos A. N. 1941-, eds. Fuzzy reasoning in information, decision, and control systems. Dordrecht: Kluwer Academic, 1994.

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33

J, Gentry E., and Stanley D. A, eds. An adaptive system for process control. [Washington, D.C.?]: U.S. Dept. of the Interior, Bureau of Mines, 1995.

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34

Mauranen, Anna. Second-Order Language Contact. Edited by Markku Filppula, Juhani Klemola, and Devyani Sharma. Oxford University Press, 2014. http://dx.doi.org/10.1093/oxfordhb/9780199777716.013.010.

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This chapter discusses the nature of English as a lingua franca (ELF) as uniquely complex ‘second order language contact’, which arises from contact between ‘similects’ of speakers from given first language backgrounds. The data is drawn from speech in academic communities. ELF is best understood as operating on three levels: the macro-social, the micro-social, and the cognitive. English as a lingua franca is largely similar to English as a native language in comparable social circumstances, but it also manifests lexico-grammatical features that are clearly different: nonstandard grammatical and lexical forms are relatively common, together with lexical simplification in a statistical sense. As speakers make competent use of discourse phenomena for communicative success, it seems that lexico-grammatical accuracy may be less crucial to communication. The findings lend support to modelling language processes as discourse-driven, fuzzy and approximate, with a high level of tolerance for variability in form.
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35

Morphy, Howard. Art as Action, Art as Evidence. Edited by Dan Hicks and Mary C. Beaudry. Oxford University Press, 2012. http://dx.doi.org/10.1093/oxfordhb/9780199218714.013.0011.

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This article is a strong defence of the idea of ‘art’, but it also recognizes its complexity and the fact that as a concept, ‘art’ is fuzzy around the edges. It uses a concept of family resemblance and sees art objects as forming polythetic sets. The category contains within it an immense diversity and includes objects that have little in common with each other and require very different methods of analysis. However, at the heart of this concept of art lies a set of loosely connected features or themes around which the idea of art coalesces: art is a form of action, art production is integral to meaning creating processes and requires a sense of form, and art is associated with aesthetic experience. This article proceeds to explain ideas of art and material culture. An analysis of art as cross-cultural category concludes this article.
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36

Anderson, James A. Brain Theory. Oxford University Press, 2018. http://dx.doi.org/10.1093/acprof:oso/9780199357789.003.0013.

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The elementary particles of cognition are concepts. Simple, accurate association alone can be misleading. Cognitive concepts work as valuable cognitive data compression, for example, giving a set of related items the same class name: tables, chairs, birds. Cognitive concepts also contain internal structure with good and bad examples and have fuzzy edges. Concepts can be associatively linked in semantic networks to store and retrieve information. Cognition using networks is an active search process and need not require further learning to be useful. Low-level concepts can lead to the formation of higher level abstractions. An experiment by Deidre Gentner involves perception of identity in pairs of items; some pairs the same and some not. Seeing many identical pairs allows the abstraction of “identity.” The abstract relationship “identity” can then become more powerful than the details of any single example pair.
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37

Livermore, Roy. Poles Apart. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198717867.003.0004.

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In just a few years, the magnetic bar-code secreted beneath the world’s oceans had provided detailed intelligence on the motions of the plates. When combined with other data from the sea floor, this allowed geophysicists to reconstruct the history of entire ocean basins following the rifting of Pangea. Some folk, however, are never happy, and ‘glass-half-empty’ types might well have complained that, impressive as all this was, it accounted for less than 200 million of the 4500 million years of Earth history, i.e. just 4%. What about that other 96%? Did plate tectonics operate through part or all of this long history and, in any case, how could you ever know, since the evidence had all been shredded by the closure of earlier oceans? There was hope: the same process that had so conveniently sequestered the recent history of the plates in the sea floor had also been at work throughout much of earlier geological time, recording the story in rocks onshore. By comparison with the high-definition picture of plate motions offered by bar-codes and fracture zones, this recording was monochrome, fuzzy, and incomplete. Yet, by the mid-1950s, it had already provided conclusive evidence that continents were truly mobile. Curiously, hardly anyone noticed.
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