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020 _a9783031145711
_9978-3-031-14571-1
024 7 _a10.1007/978-3-031-14571-1
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
072 7 _aUYQ
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082 0 4 _a006.3
_223
100 1 _aMohammadazadeh, Ardashir.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_979982
245 1 0 _aNeural Networks and Learning Algorithms in MATLAB
_h[electronic resource] /
_cby Ardashir Mohammadazadeh, Mohammad Hosein Sabzalian, Oscar Castillo, Rathinasamy Sakthivel, Fayez F. M. El-Sousy, Saleh Mobayen.
250 _a1st ed. 2022.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2022.
300 _aIX, 117 p. 105 illus., 87 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSynthesis Lectures on Intelligent Technologies,
_x2731-6920
505 0 _aChapter 1. Introduction -- Chapter 2. Multilayer Perceptron (MLP) Neural Networks -- Chapter 3- Neural Networks Training Based on Recursive Least Squares (RLS) -- Chapter 4. Neural Networks Training Based on Second-Order Optimization Technique -- Chapter 5. Neural Networks Training Based on Genetic Algorithm -- Chapter 6. Neural Network Training Based on Particle Swarm Optimization (PSO) -- Chapter 7- Neural Network Training Based on UKF -- Chapter 8. Designing Neural-Fuzzy PID Controller through Multiobjective Optimization.
520 _aThis book explains the basic concepts, theory and applications of neural networks in a simple unified approach with clear examples and simulations in the MATLAB programming language. The scripts herein are coded for general purposes to be easily extended to a variety of problems in different areas of application. They are vectorized and optimized to run faster and be applicable to high-dimensional engineering problems. This book will serve as a main reference for graduate and undergraduate courses in neural networks and applications. This book will also serve as a main basis for researchers dealing with complex problems that require neural networks for finding good solutions in areas, such as time series prediction, intelligent control and identification. In addition, the problem of designing neural network by using metaheuristics, such as the genetic algorithms and particle swarm optimization, with one objective and with multiple objectives, is presented.
650 0 _aComputational intelligence.
_97716
650 0 _aArtificial intelligence.
_93407
650 1 4 _aComputational Intelligence.
_97716
650 2 4 _aArtificial Intelligence.
_93407
700 1 _aSabzalian, Mohammad Hosein.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_979983
700 1 _aCastillo, Oscar.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_979984
700 1 _aSakthivel, Rathinasamy.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_979985
700 1 _aEl-Sousy, Fayez F. M.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_979986
700 1 _aMobayen, Saleh.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_979987
710 2 _aSpringerLink (Online service)
_979988
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031145704
776 0 8 _iPrinted edition:
_z9783031145728
776 0 8 _iPrinted edition:
_z9783031145735
830 0 _aSynthesis Lectures on Intelligent Technologies,
_x2731-6920
_979989
856 4 0 _uhttps://doi.org/10.1007/978-3-031-14571-1
912 _aZDB-2-SXSC
942 _cEBK
999 _c84882
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