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Books on the topic 'Fuzzy logic simulation'

Author: Grafiati
Published: 5 June 2025
Last updated: 16 July 2025

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1

Starczewski, Janusz T. Advanced Concepts in Fuzzy Logic and Systems with Membership Uncertainty. Springer Berlin Heidelberg, 2013.

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2

Rotshtein, Alexander P. Fuzzy Evidence in Identification, Forecasting and Diagnosis. Springer Berlin Heidelberg, 2012.

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3

Robyns, Benoit. Vector Control of Induction Machines: Desensitisation and Optimisation Through Fuzzy Logic. Springer London, 2012.

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4

Taylor, Cynthia. A programmer's guide to the fuzzy logic ramp metering algorithm: Software design, integration, testing, and evaluation. Washington State Dept. of Transportation, 2000.

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5

Taylor, Cynthia. Algorithm design, user interface, and optimization procedure for a fuzzy logic ramp metering algorithm: A training manual for freeway operations engineers. Washington State Dept. of Transportation, 2000.

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6

Taylor, Cynthia. Evaluation of a fuzzy logic ramp metering algorithm: A comparative study among three ramp metering algorithms used in the greater Seattle area. Washington State Dept. of Transportation, 2000.

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7

Silov, V. B. Prini͡a︡tie strategicheskikh resheniĭ v nechetkoĭ obstanovke: V politike, makroėkonomike, sot͡s︡iologii, menedzhmente, medit͡s︡ine, ėkologii. INPRO-RES, 1995.

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8

Tucci, Mario, and Marco Garetti, eds. Proceedings of the third International Workshop of the IFIP WG5.7. Firenze University Press, 2002. http://dx.doi.org/10.36253/88-8453-042-3.

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Contents of the papers presented at the international workshop deal with the wide variety of new and computer-based techniques for production planning and control that has become available to the scientific and industrial world in the past few years: formal modeling techniques, artificial neural networks, autonomous agent theory, genetic algorithms, chaos theory, fuzzy logic, simulated annealing, tabu search, simulation and so on. The approach, while being scientifically rigorous, is focused on the applicability to industrial environment.
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9

Kacprzyk, Janusz, and Oscar Castillo. Evolutionary design of intelligent systems in modeling, simulation and control. Springer, 2009.

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10

Vermeir, Dirk, Steven Schockaert, Martine De Cock, and Jeroen Janssen. Answer Set Programming for Continuous Domains: A Fuzzy Logic Approach. Atlantis Press (Zeger Karssen), 2014.

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11

Answer Set Programming for Continuous Domains: A Fuzzy Logic Approach. Springer, 2012.

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12

Goyal, Neeraj Kumar, and Ajeet Kumar Pandey. Early Software Reliability Prediction: A Fuzzy Logic Approach. Springer, 2015.

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13

Goyal, Neeraj Kumar, and Ajeet Kumar Pandey. Early Software Reliability Prediction: A Fuzzy Logic Approach. Springer London, Limited, 2013.

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14

Starczewski, Janusz T. Advanced Concepts in Fuzzy Logic and Systems with Membership Uncertainty. Springer, 2012.

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15

Starczewski, Janusz T. Advanced Concepts in Fuzzy Logic and Systems with Membership Uncertainty. Springer, 2014.

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16

Rakytyanska, Hanna B., and Alexander P. Rotshtein. Fuzzy Evidence in Identification, Forecasting and Diagnosis. Springer, 2014.

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17

Hoang, Patrick. Design and analysis of an adaptive fuzzy power system stabilizer. 1994.

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18

Hellendoorn, Hans, and Dimiter Driankov. Fuzzy Model Identification: Selected Approaches. Springer London, Limited, 2012.

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19

(Editor), Hans Hellendoorn, and Dimiter Driankov (Editor), eds. Fuzzy Model Identification: Selected Approaches. Springer, 1998.

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20

Prasad, Nadipuram R., and Hung T. Nguyen. Fuzzy Modeling and Control: Selected Works of Sugeno. CRC, 1999.

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21

Chaos theory in the financial markets: Applying fractals, fuzzy logic, genetic algorithms, swarm simulation & the Monte Carlo method to manage market chaos & volatility. Probus Pub. Co., 1994.

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22

Flexible Robot Manipulators: Modelling, simulation and control. The Institution of Engineering and Technology, 2017.

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23

Yadav, Vikash, Parashu Ram Pal, and Chuan-Ming Liu, eds. Recent Developments in Artificial Intelligence and Communication Technologies. BENTHAM SCIENCE PUBLISHERS, 2022. http://dx.doi.org/10.2174/97816810896761220101.

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This book is a review of recent artificial intelligence approaches, initiatives and applications in engineering and science fields. It features contributions that highlight the use of techniques such as machine learning, mining engineering, modeling and simulation, and fuzzy logic methods in the fields of communication, networking and information engineering. The collection of chapters should inspire scholars involved in theoretical and applied sciences to contribute to research using computational intelligence principles and methods in their respective research communities. Professionals work
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24

Bernstein, Herbert. PC- Simulation der Regelungstechnik und Fuzzy- Logik. Entwurf und Synthese elektronischer Systeme. VDE-Verlag, 1998.

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25

Kasabov, Nikola. Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering. The MIT Press, 1996. http://dx.doi.org/10.7551/mitpress/3071.001.0001.

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In a clear and accessible style, Kasabov describes rule-based and connectionist techniques and then their combinations, with fuzzy logic included, showing the application of the different techniques to a set of simple prototype problems, which makes comparisons possible. A particularly strong feature of the text is that it is filled with applications in engineering, business, and finance. AI problems that cover most of the application-oriented research in the field (pattern recognition, speech and image processing, classification, planning, optimization, prediction, control, decision making, a
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