254 related articles for article (PubMed ID: 16526477)
1. Tuning the structure and parameters of a neural network by using hybrid Taguchi-genetic algorithm.
Tsai JT; Chou JH; Liu TK
IEEE Trans Neural Netw; 2006 Jan; 17(1):69-80. PubMed ID: 16526477
[TBL] [Abstract][Full Text] [Related]
2. Tuning of the structure and parameters of a neural network using an improved genetic algorithm.
Leung FF; Lam HK; Ling SH; Tam PS
IEEE Trans Neural Netw; 2003; 14(1):79-88. PubMed ID: 18237992
[TBL] [Abstract][Full Text] [Related]
3. Noninvasive evaluation of mental stress using by a refined rough set technique based on biomedical signals.
Liu TK; Chen YP; Hou ZY; Wang CC; Chou JH
Artif Intell Med; 2014 Jun; 61(2):97-103. PubMed ID: 24877617
[TBL] [Abstract][Full Text] [Related]
4. Hierarchical genetic algorithm for near optimal feedforward neural network design.
Yen G; Lu H
Int J Neural Syst; 2002 Feb; 12(1):31-43. PubMed ID: 11852443
[TBL] [Abstract][Full Text] [Related]
5. Identification of High-Order Single-Nucleotide Polymorphism Barcodes in Breast Cancer Using a Hybrid Taguchi-Genetic Algorithm: Case-Control Study.
Chuang LY; Yang CS; Yang HS; Yang CH
JMIR Med Inform; 2020 Jun; 8(6):e16886. PubMed ID: 32554381
[TBL] [Abstract][Full Text] [Related]
6. An alternative approach for neural network evolution with a genetic algorithm: crossover by combinatorial optimization.
García-Pedrajas N; Ortiz-Boyer D; Hervás-Martínez C
Neural Netw; 2006 May; 19(4):514-28. PubMed ID: 16343847
[TBL] [Abstract][Full Text] [Related]
7. An improved genetic algorithm based fuzzy-tuned neural network.
Ling SH; Leung FH; Lam HK
Int J Neural Syst; 2005 Dec; 15(6):457-74. PubMed ID: 16385635
[TBL] [Abstract][Full Text] [Related]
8. The superior fault tolerance of artificial neural network training with a fault/noise injection-based genetic algorithm.
Su F; Yuan P; Wang Y; Zhang C
Protein Cell; 2016 Oct; 7(10):735-748. PubMed ID: 27502185
[TBL] [Abstract][Full Text] [Related]
9. Biological engineering applications of feedforward neural networks designed and parameterized by genetic algorithms.
Ferentinos KP
Neural Netw; 2005 Sep; 18(7):934-50. PubMed ID: 15963690
[TBL] [Abstract][Full Text] [Related]
10. Hybrid multiobjective evolutionary design for artificial neural networks.
Goh CK; Teoh EJ; Tan KC
IEEE Trans Neural Netw; 2008 Sep; 19(9):1531-48. PubMed ID: 18779086
[TBL] [Abstract][Full Text] [Related]
11. A One-Layer Recurrent Neural Network for Pseudoconvex Optimization Problems With Equality and Inequality Constraints.
Qin S; Yang X; Xue X; Song J
IEEE Trans Cybern; 2017 Oct; 47(10):3063-3074. PubMed ID: 27244757
[TBL] [Abstract][Full Text] [Related]
12. Constructive approximation to multivariate function by decay RBF neural network.
Hou M; Han X
IEEE Trans Neural Netw; 2010 Sep; 21(9):1517-23. PubMed ID: 20693108
[TBL] [Abstract][Full Text] [Related]
13. Backpropagation algorithm adaptation parameters using learning automata.
Beigy H; Meybodi MR
Int J Neural Syst; 2001 Jun; 11(3):219-28. PubMed ID: 11574959
[TBL] [Abstract][Full Text] [Related]
14. An improvement of extreme learning machine for compact single-hidden-layer feedforward neural networks.
Huynh HT; Won Y; Kim JJ
Int J Neural Syst; 2008 Oct; 18(5):433-41. PubMed ID: 18991365
[TBL] [Abstract][Full Text] [Related]
15. A local training and pruning approach for neural networks.
Chang SJ; Leung CS; Wong KW; Sum J
Int J Neural Syst; 2000 Dec; 10(6):425-38. PubMed ID: 11307857
[TBL] [Abstract][Full Text] [Related]
16. Recurrent neural network for non-smooth convex optimization problems with application to the identification of genetic regulatory networks.
Cheng L; Hou ZG; Lin Y; Tan M; Zhang WC; Wu FX
IEEE Trans Neural Netw; 2011 May; 22(5):714-26. PubMed ID: 21427022
[TBL] [Abstract][Full Text] [Related]
17. Optimal and robust design of brain-state-in-a-box neural associative memories.
Park Y
Neural Netw; 2010 Mar; 23(2):210-8. PubMed ID: 19914797
[TBL] [Abstract][Full Text] [Related]
18. A hybrid forward algorithm for RBF neural network construction.
Peng JX; Li K; Huang DS
IEEE Trans Neural Netw; 2006 Nov; 17(6):1439-51. PubMed ID: 17131659
[TBL] [Abstract][Full Text] [Related]
19. Multiobjective hybrid optimization and training of recurrent neural networks.
Delgado M; Cuéllar MP; Pegalajar MC
IEEE Trans Syst Man Cybern B Cybern; 2008 Apr; 38(2):381-403. PubMed ID: 18348922
[TBL] [Abstract][Full Text] [Related]
20. An H(∞) control approach to robust learning of feedforward neural networks.
Jing X
Neural Netw; 2011 Sep; 24(7):759-66. PubMed ID: 21458228
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
