Relevant bibliographies by topics / Neural Networks method / Books

Books on the topic 'Neural Networks method'

To see the other types of publications on this topic, follow the link: Neural Networks method.
Author: Grafiati
Published: 10 December 2022
Last updated: 28 January 2023

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the top 50 books for your research on the topic 'Neural Networks method.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Browse books on a wide variety of disciplines and organise your bibliography correctly.

1

Zhang, Yunong. Zhang neural networks and neural-dynamic method. Hauppauge, N.Y: Nova Science Publishers, 2009.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
2

Harrison, R. F. A general method for the discovery and use of rules induced by feedforward artificial neural networks. Sheffield: University of Sheffield, Dept. of Automatic Control & Systems Engineering, 1995.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
3

Amezcua, Jonathan, Patricia Melin, and Oscar Castillo. New Classification Method Based on Modular Neural Networks with the LVQ Algorithm and Type-2 Fuzzy Logic. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-73773-7.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Cronley, Thomas J. The use of neural networks as a method of correlating thermal fluid data to provide useful information on thermal systems. Monterey, Calif: Naval Postgraduate School, 2000.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
5

Neural networks and simulation methods. New York: M. Dekker, 1994.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
6

Suzuki, T. Edge detection methods using neural networks. Manchester: UMIST, 1996.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
7

Kumar, Bose Deb, ed. Neural networks: Deterministic methods of analysis. London: International Thomson Computer Press, 1996.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
8

Shepherd, Adrian J. Second-Order Methods for Neural Networks. London: Springer London, 1997. http://dx.doi.org/10.1007/978-1-4471-0953-2.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Pabisek, Ewa. Systemy hybrydowe intergruja̜ce MES i SSN w analizie wybranych problemów mechaniki konstrukcji i materiałów. Kraków: Wydawn. Politechniki Krakowskiej, 2008.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
10

Pabisek, Ewa. Systemy hybrydowe intergruja̜ce MES i SSN w analizie wybranych problemów mechaniki konstrukcji i materiałów. Kraków: Wydawn. Politechniki Krakowskiej, 2008.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
11

Cirrincione, Giansalvo. Neural based orthogonal data fitting: The EXIN neural networks. Hoboken, NJ: Wiley, 2010.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
12

Shepherd, Adrian J. Second-order methods for neural networks: Fast and reliable training methods for multi-layer perceptrons. London: Springer, 1997.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
13

Advanced methods in neural computing. New York: Van Nostrand Reinhold, 1993.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
14

Zou, Fan. Cellular neural networks: Stability, dynamics and design methods. Aachen: Verlag Shaker, 1993.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
15

Goldberg, Yoav. Neural Network Methods for Natural Language Processing. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-031-02165-7.

Full text
APA, Harvard, Vancouver, ISO, and other styles
16

1956-, Koch Christof, and Segev Idan, eds. Methods in neuronal modeling: From synapses to networks. Cambridge, Mass: MIT Press, 1989.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
17

M, Poulton Mary, ed. Computational neural networks for geophysical data processing. New York: Pergamon, 2001.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
18

Bird, R. A. Baysian methods of identifying "novel data" in neural networks. Manchester: UMIST, 1995.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
19

Mathematical methods for neural network analysis and design. Cambridge, Mass: MIT Press, 1996.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
20

Baruque, Bruno. Fusion methods for unsupervised learning ensembles. Berlin: Springer, 2010.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
21

Yadav, Neha, Anupam Yadav, and Manoj Kumar. An Introduction to Neural Network Methods for Differential Equations. Dordrecht: Springer Netherlands, 2015. http://dx.doi.org/10.1007/978-94-017-9816-7.

Full text
APA, Harvard, Vancouver, ISO, and other styles
22

1954-, Docampo D., Figueiras-Vidal A. R, and Pérez-González F. 1967-, eds. Intelligent methods in signal processing and communications. Boston: Birkhäuser, 1997.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
23

Cios, Krzysztof J. A comparison of neural networks and fuzzy logic methods for process modeling. [Washington, DC]: National Aeronautics and Space Administration, 1996.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
24

Approximation methods for efficient learning of Bayesian networks. Amsterdam: IOS Press, 2008.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
25

Hsieh, William Wei. Machine learning methods in the environmental sciences: Neural networks and kernels. Cambridge, UK: Cambridge University Press, 2009.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
26

Machine learning methods in the environmental sciences: Neural networks and kernels. Cambridge, UK: Cambridge University Press, 2009.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
27

Horst, Bunke, and Kandel Abraham, eds. Hybrid methods in pattern recognition. River Edge, N.J: World Scientific, 2002.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
28

J, Taylor Brian, ed. Methods and procedures for the verification and validation of artificial neural networks. New York, NY: Springer Science + Business Media, 2006.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
29

1963-, Segovia Javier, Szczepaniak Piotr S. 1953, and Niedzwiedzinski Marian 1947-, eds. E-commerce and intelligent methods. Heidelberg: Physica-Verlag, 2002.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
30

Docampo, D. Intelligent Methods in Signal Processing and Communications. Boston, MA: Birkhäuser Boston, 1997.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
31

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.

Full text
Abstract:
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.
APA, Harvard, Vancouver, ISO, and other styles
32

Center, Ames Research, ed. Simulation tests of the optimization method of Hopfield and Tank using neural networks. Moffett Field, California: National Aeronautics and Space Administration, Ames Research Center, 1989.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
33

Amezcua, Jonathan. New Classification Method Based on Modular Neural Networks with the LVQ Algorithm and Type-2 Fuzzy Logic. Springer, 2018.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
34

Ohira, Toru. A master equation approach to stochastic neurodynamics. 1993.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
35

David, Brown. Artificial Intelligence for Business: Understand Neural Networks and Machine Learning for Robotics. A Step-By-Step Method to Develop AI and ML Projects for Business. Independently published, 2019.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
36

D, Livingstone, ed. Artificial neural networks: Methods and applications. Totowa, NJ: Humana Press, 2008.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
37

Artificial Neural Networks Methods And Applications. Humana Press, 2011.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
38

Artificial Neural Networks: Methods and Applications (Methods in Molecular Biology). Humana Press, 2008.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
39

Fox, Raymond. The Use of Self. Oxford University Press, 2011. http://dx.doi.org/10.1093/oso/9780190616144.001.0001.

Full text
Abstract:
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.
APA, Harvard, Vancouver, ISO, and other styles
40

Tirozzi, Brunello, Silvia Puca, and Stefano Pittalis. Neural Networks and Sea Time Series. Springer, 2008.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
41

Neural Network Methods in Natural Language Processing. Morgan & Claypool Publishers, 2017.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
42

Goldberg, Yoav, and Graeme Hirst. Neural Network Methods in Natural Language Processing. Morgan & Claypool Publishers, 2017.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
43

Goldberg, Yoav, and Graeme Hirst. Neural Network Methods in Natural Language Processing. Morgan & Claypool Publishers, 2017.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
44

Neural Network Methods for Natural Language Processing. Springer International Publishing AG, 2017.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
45

Segev, Idan, and Christof Koch. Methods in Neuronal Modeling: From Ions to Networks. MIT Press, 1998.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
46

Poulton, M. M. Computational Neural Networks for Geophysical Data Processing. Elsevier Science & Technology Books, 2001.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
47

1956-, Koch Christof, and Segev Idan, eds. Methods in neuronal modeling: From ions to networks. 2nd ed. Cambridge, Mass: MIT Press, 1998.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
48

Boudreau, Joseph F., and Eric S. Swanson. Classical spin systems. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198708636.003.0020.

Full text
Abstract:
The thermodynamic properties of spin systems are evaluated with Monte Carlo methods. A review of classical thermodynamics is followed by a discussion of critical exponents. The Monte Carlo method is then applied to the two-dimensional Ising model with the goal of determining the phase diagram for magnetization. Boundary conditions, the reweighting method, autocorrelation, and critical slowing down are all explored. Cluster algorithms for overcoming critical slowing down are developed next and shown to dramatically reduce autocorrelation. A variety of spin systems that illustrate first, second, and infinite order (topological) phase transitions are explored. Finally, applications to random systems called spin glasses and to neural networks are briefly reviewed.
APA, Harvard, Vancouver, ISO, and other styles
49

Kasabov, Nikola K., Petia Koprinkova-Hristova, and Valeri Mladenov. Artificial Neural Networks: Methods and Applications in Bio-/Neuroinformatics. Springer, 2014.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
50

Kasabov, Nikola K., Petia Koprinkova-Hristova, and Valeri Mladenov. Artificial Neural Networks: Methods and Applications in Bio-/Neuroinformatics. Springer, 2016.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the bibliographies on the topic 'Neural Networks method' for other source types:
Journal articles Dissertations / Theses
We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!

To the bibliography