Books on the topic 'Neural-genetic algorithm'

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1

Kobayashi, Takahisa. A hybrid neural network-genetic algorithm technique for aircraft engine performance diagnostics. [Cleveland, Ohio]: National Aeronautics and Space Administration, Glenn Research Center, 2001.

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2

Kobayashi, Takahisa. A hybrid neural network-genetic algorithm technique for aircraft engine performance diagnostics. [Cleveland, Ohio]: National Aeronautics and Space Administration, Glenn Research Center, 2001.

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3

Kobayashi, Takahisa. A hybrid neural network-genetic algorithm technique for aircraft engine performance diagnostics. [Cleveland, Ohio]: National Aeronautics and Space Administration, Glenn Research Center, 2001.

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4

Kobayashi, Takahisa. A hybrid neural network-genetic algorithm technique for aircraft engine performance diagnostics. [Cleveland, Ohio]: National Aeronautics and Space Administration, Glenn Research Center, 2001.

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5

Vas, Peter. Artificial-intelligence-based electrical machines and drives: Application of fuzzy, neural, fuzzy-neural, and genetic-algorithm-based techniques. Oxford: Oxford University Press, 1999.

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6

C, Jain L., and Johnson R. P, eds. Neural network training using genetic algorithms. Singapore: World Scientific, 1996.

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7

Albrecht, Rudolf F., Colin R. Reeves, and Nigel C. Steele, eds. Artificial Neural Nets and Genetic Algorithms. Vienna: Springer Vienna, 1993. http://dx.doi.org/10.1007/978-3-7091-7533-0.

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8

Pearson, David W., Nigel C. Steele, and Rudolf F. Albrecht. Artificial Neural Nets and Genetic Algorithms. Vienna: Springer Vienna, 1995. http://dx.doi.org/10.1007/978-3-7091-7535-4.

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9

Dobnikar, Andrej, Nigel C. Steele, David W. Pearson, and Rudolf F. Albrecht. Artificial Neural Nets and Genetic Algorithms. Vienna: Springer Vienna, 1999. http://dx.doi.org/10.1007/978-3-7091-6384-9.

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10

Kůrková, Věra, Roman Neruda, Miroslav Kárný, and Nigel C. Steele, eds. Artificial Neural Nets and Genetic Algorithms. Vienna: Springer Vienna, 2001. http://dx.doi.org/10.1007/978-3-7091-6230-9.

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11

Pearson, David W., Nigel C. Steele, and Rudolf F. Albrecht, eds. Artificial Neural Nets and Genetic Algorithms. Vienna: Springer Vienna, 2003. http://dx.doi.org/10.1007/978-3-7091-0646-4.

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12

Smith, George D., Nigel C. Steele, and Rudolf F. Albrecht. Artificial Neural Nets and Genetic Algorithms. Vienna: Springer Vienna, 1998. http://dx.doi.org/10.1007/978-3-7091-6492-1.

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13

Lee, Jae-Woo. Evolving neural networks using parallel genetic algorithms. Manchester: UMIST, 1998.

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14

Caplan, J. An investigation into genetic algorithms with neural networks. Manchester: UMIST, 1993.

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15

Adeli, Hojjat. Machine learning: Neural networks, genetic algorithms, and fuzzy systems. New York: Wiley, 1995.

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16

Furuhashi, Takeshi, ed. Advances in Fuzzy Logic, Neural Networks and Genetic Algorithms. Berlin, Heidelberg: Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/3-540-60607-6.

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17

Rogers, David. G/SPINES: A hybird of friedman's multivariate adaptive regression splines (MARS) algorithm with Holland's genetic algorithm. [Moffett Field, Calif.]: Research Institute for Advanced Computer Science, NASA Ames Research Center, 1991.

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18

Ruan, Da. Intelligent Hybrid Systems: Fuzzy Logic, Neural Networks, and Genetic Algorithms. Boston, MA: Springer US, 1997.

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19

D, Karaboga, ed. Intelligent Optimisation Techniques: Genetic Algorithms, Tabu Search, Simulated Annealing and Neural Networks. London: Springer London, 2000.

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20

1965-, Karaboga Dervis, ed. Intelligent optimisation techniques: Genetic algorithms, tabu search, simulated annealing and neural networks. London: Springer, 2000.

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21

Kwaśnicka, Halina. Ewolucyjne projektowanie sieci neuronowych. Wrocław: Oficyna Wydawnicza Politechniki Wrocławskiej, 2007.

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22

Zalzala, A. M. S. Explorations in real-time robotics using parallel processing,neural networks and genetic algorithms. Sheffield: University of Sheffield, Dept. of Automatic Control and Systems Engineering, 1994.

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23

Mohebbi, Ali. Modeling of thermodynamic properties of refrigerants using artificial neural networks and genetic algorithms. Hauppauge, N.Y: Nova Science Publishers, 2010.

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24

Chaiyaratana, N. Hybridisation of neural networks and genetic algorithms in an application of time-optimal control. Sheffield: University of Sheffield, Dept. of Automatic Control and Systems Engineering, 1998.

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25

Soft computing in water resources engineering: Artificial neural networks, fuzzy logic and genetic algorithms. Southampton: WIT Press, 2012.

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26

COGANN-92 (1992 Baltimore, Md.). COGANN-92, International Workshop on Combinations of Genetic Algorithms and Neural Networks, June 6, 1992, Baltimore, Maryland. Edited by Whitley L. Darrell, Schaffer J. David, IEEE Neural Networks Council, and International Society for Genetic Algorithms. Los Alamitos, Calif: IEEE Computer Society Press, 1992.

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27

J, Eshelman Larry, ed. Proceedings of the Sixth International Conference on Genetic Algorithms: University of Pittsburgh, July 15-19, 1995. San Francisco, Calif: M. Kaufman, 1995.

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28

Artificial Neural Nets and Genetic Algorithms (Conference) (4th 1999 Portorož, Slovenia). Artificial neural nets and genetic algorithms: Proceedings of the international conference in Portorož, Slovenia, 1999. Wien: Springer, 1999.

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29

name, No. Artificial neural nets and genetic algorithms: Proceedings of the international conference in Roanne, France, 2003. Wien: Springer Verlag, 2003.

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30

Hunger, Johannes. Künstlich intelligente Entwicklung von Kraftfeldparametern: Eine Komposition am Beispiel tripodaler Metallkomplexe. Berlin: Springer, 2000.

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31

IEEE/Nagoya University World Wisepersons Workshop (1994 Nagoya-shi, Japan). Advances in fuzzy logic, neural networks, and genetic algorithms: IEEE/Nagoya University World Wisepersons Workshop, Nagoya, Japan, August 9-10, 1994 : selected papers. Berlin: Springer, 1995.

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32

Alberto, Gómez Gómez, and Abajo Martínez Nicolás de, eds. Introducción a la inteligencia artificial: Sistemas expertos, redes neuronales artificiales y computación evolutiva. Oviedo: Universidad de Oviedo, Servicio de Publicaciones, 2001.

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33

IEEE/Nagoya-University World Wisepersons Workshop on Fuzzy Logic and Neural Networks/Evolutionary Computation (1995 Nagoya, Japan). Proceedings of the 1995 IEEE/Nagoya-University World Wisepersons Workshop (WWW '95) on Fuzzy Logic and Neural Networks/Evolutionary Computation: November 14 and 15, 1995, Rubrum Ohzan, Nagoya, Japan. Nagoya, Japan: Nagoya University, 1995.

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34

IEEE International Conference on Evolutionary Computation (1995 Perth, W.A.). 1995 IEEE International Conference on Evolutionary Computation, the University of Western Australia, Perth, Western Australia, 29 November-1 December, 1995. [New York]: Institute of Electrical and Electronics Engineers, 1995.

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35

Tucci, Mario, and Marco Garetti, eds. Proceedings of the third International Workshop of the IFIP WG5.7. Florence: 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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36

Council, IEEE Neural Networks, and Evolutionary Programming Society, eds. Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97): April 13-16, 1997, University Place Hotel, Indianapolis, IN USA. Piscataway, N.J: Institute of Electrical and Electronics Engineers, 1997.

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37

IEEE International Conference on Evolutionary Computation (1996 Nagoya University). Proceedings of 1996 IEEE International Conference on Evolutionary Computation (ICEC '96): May 20-22, 1996, Symposion & Toyoda Auditorium, Nagoya University, Japan. Piscataway, N.J: Institute of Electrical and Electronics Engineers, 1996.

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38

IEEE International Conference on Evolutionary Computation (1998 Anchorage, Alaska). The 1998 IEEE International Conference on Evolutionary Computation proceedings : IEEE World Congress on Computational Intelligence : Anchorage, Alaska, May 4-9, 1998. Piscataway, New Jersey: IEEE, 1998.

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39

Inc, NetLibrary, ed. The nonlinear workbook: Chaos, fractals, cellular automata, neural networks, genetic algorithms, fuzzy logic : with C++, Java, SymbolicC++ and Reduce programs. Singapore: World Scientific, 2001.

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40

Minns, Anthony W. Artificial neural networks as subsymbolic process descriptors. Rotterdam: A.A. Balkema, 1998.

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41

P, Dhawan Atam, Meyer Claudia M, and United States. National Aeronautics and Space Administration., eds. Genetic algorithm based input selection for a neural network function approximator with application to SSME health monitoring. [Washington, DC: National Aeronautics and Space Administration, 1991.

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42

Raff, Lionel, Ranga Komanduri, Martin Hagan, and Satish Bukkapatnam. Neural Networks in Chemical Reaction Dynamics. Oxford University Press, 2012. http://dx.doi.org/10.1093/oso/9780199765652.001.0001.

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This monograph presents recent advances in neural network (NN) approaches and applications to chemical reaction dynamics. Topics covered include: (i) the development of ab initio potential-energy surfaces (PES) for complex multichannel systems using modified novelty sampling and feedforward NNs; (ii) methods for sampling the configuration space of critical importance, such as trajectory and novelty sampling methods and gradient fitting methods; (iii) parametrization of interatomic potential functions using a genetic algorithm accelerated with a NN; (iv) parametrization of analytic interatomic potential functions using NNs; (v) self-starting methods for obtaining analytic PES from ab inito electronic structure calculations using direct dynamics; (vi) development of a novel method, namely, combined function derivative approximation (CFDA) for simultaneous fitting of a PES and its corresponding force fields using feedforward neural networks; (vii) development of generalized PES using many-body expansions, NNs, and moiety energy approximations; (viii) NN methods for data analysis, reaction probabilities, and statistical error reduction in chemical reaction dynamics; (ix) accurate prediction of higher-level electronic structure energies (e.g. MP4 or higher) for large databases using NNs, lower-level (Hartree-Fock) energies, and small subsets of the higher-energy database; and finally (x) illustrative examples of NN applications to chemical reaction dynamics of increasing complexity starting from simple near equilibrium structures (vibrational state studies) to more complex non-adiabatic reactions. The monograph is prepared by an interdisciplinary group of researchers working as a team for nearly two decades at Oklahoma State University, Stillwater, OK with expertise in gas phase reaction dynamics; neural networks; various aspects of MD and Monte Carlo (MC) simulations of nanometric cutting, tribology, and material properties at nanoscale; scaling laws from atomistic to continuum; and neural networks applications to chemical reaction dynamics. It is anticipated that this emerging field of NN in chemical reaction dynamics will play an increasingly important role in MD, MC, and quantum mechanical studies in the years to come.
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43

Rajashekaran, S., and G. A. Vijayalksmi. Neural Networks, Fuzzy Logic and Genetic Algorithms. Prentice-Hall of India Pvt.Ltd, 2004.

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44

Drabble, Darren. Neural networks and genetic algorithms for control applications. 2004.

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45

Genetic Algorithms and Neural Networks Workshop...Combinations of. Ieee Computer Society, 1992.

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46

Applications Of Fuzzy Control Genetic Algorithms And Neural Networks. Springer, 2007.

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47

Rangarajan, Srikumar. Design of application-tailored neural networks using genetic algorithms. 1993.

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48

Adeli, Hojjat, and Shih-Lin Hung. Machine Learning: Neural Networks, Genetic Algorithms, and Fuzzy Systems. John Wiley & Sons, 1994.

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49

Jain, Lakhmi C., and N. M. Martin, eds. Fusion of Neural Networks, Fuzzy Systems, and Genetic Algorithms. CRC Press, 2020. http://dx.doi.org/10.1201/9780367811464.

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50

Gargano, Michael, and Lawrence Von Kellk. Neural Networks and Genetic Algorithms: Business Applications and Case Studies. Van Nostrand Reinhold Computer, 1994.

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