179 related articles for article (PubMed ID: 16761810)
1. Evolutionary neural networks for anomaly detection based on the behavior of a program.
Han SJ; Cho SB
IEEE Trans Syst Man Cybern B Cybern; 2006 Jun; 36(3):559-70. PubMed ID: 16761810
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. Intrusion detection using rough set classification.
Zhang LH; Zhang GH; Zhang J; Bai YC
J Zhejiang Univ Sci; 2004 Sep; 5(9):1076-86. PubMed ID: 15323002
[TBL] [Abstract][Full Text] [Related]
4. Adaptive evolutionary artificial neural networks for pattern classification.
Oong TH; Isa NA
IEEE Trans Neural Netw; 2011 Nov; 22(11):1823-36. PubMed ID: 21968733
[TBL] [Abstract][Full Text] [Related]
5. An empirical comparison of combinations of evolutionary algorithms and neural networks for classification problems.
CantĂș-Paz E; Kamath C
IEEE Trans Syst Man Cybern B Cybern; 2005 Oct; 35(5):915-27. PubMed ID: 16240768
[TBL] [Abstract][Full Text] [Related]
6. 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]
7. An automatically tuning intrusion detection system.
Yu Z; Tsai JJ; Weigert T
IEEE Trans Syst Man Cybern B Cybern; 2007 Apr; 37(2):373-84. PubMed ID: 17416165
[TBL] [Abstract][Full Text] [Related]
8. Min-max hyperellipsoidal clustering for anomaly detection in network security.
Sarasamma ST; Zhu QA
IEEE Trans Syst Man Cybern B Cybern; 2006 Aug; 36(4):887-901. PubMed ID: 16903372
[TBL] [Abstract][Full Text] [Related]
9. Guiding hidden layer representations for improved rule extraction from neural networks.
Huynh TQ; Reggia JA
IEEE Trans Neural Netw; 2011 Feb; 22(2):264-75. PubMed ID: 21138801
[TBL] [Abstract][Full Text] [Related]
10. Fast learning method for convolutional neural networks using extreme learning machine and its application to lane detection.
Kim J; Kim J; Jang GJ; Lee M
Neural Netw; 2017 Mar; 87():109-121. PubMed ID: 28110106
[TBL] [Abstract][Full Text] [Related]
11. A machine learning evaluation of an artificial immune system.
Glickman M; Balthrop J; Forrest S
Evol Comput; 2005; 13(2):179-212. PubMed ID: 15969900
[TBL] [Abstract][Full Text] [Related]
12. Hierarchical Kohonenen net for anomaly detection in network security.
Sarasamma ST; Zhu QA; Huff J
IEEE Trans Syst Man Cybern B Cybern; 2005 Apr; 35(2):302-12. PubMed ID: 15828658
[TBL] [Abstract][Full Text] [Related]
13. A novel geometric approach to binary classification based on scaled convex hulls.
Liu Z; Liu JG; Pan C; Wang G
IEEE Trans Neural Netw; 2009 Jul; 20(7):1215-20. PubMed ID: 19482572
[TBL] [Abstract][Full Text] [Related]
14. Error minimized extreme learning machine with growth of hidden nodes and incremental learning.
Feng G; Huang GB; Lin Q; Gay R
IEEE Trans Neural Netw; 2009 Aug; 20(8):1352-7. PubMed ID: 19596632
[TBL] [Abstract][Full Text] [Related]
15. Logistic regression by means of evolutionary radial basis function neural networks.
Gutierrez PA; Hervas-Martinez C; Martinez-Estudillo FJ
IEEE Trans Neural Netw; 2011 Feb; 22(2):246-63. PubMed ID: 21138802
[TBL] [Abstract][Full Text] [Related]
16. Simultaneous perturbation learning rule for recurrent neural networks and its FPGA implementation.
Maeda Y; Wakamura M
IEEE Trans Neural Netw; 2005 Nov; 16(6):1664-72. PubMed ID: 16342505
[TBL] [Abstract][Full Text] [Related]
17. Blood cell identification using a simple neural network.
Khashman A
Int J Neural Syst; 2008 Oct; 18(5):453-8. PubMed ID: 18991367
[TBL] [Abstract][Full Text] [Related]
18. AdaBoost-based algorithm for network intrusion detection.
Hu W; Hu W; Maybank S
IEEE Trans Syst Man Cybern B Cybern; 2008 Apr; 38(2):577-83. PubMed ID: 18348941
[TBL] [Abstract][Full Text] [Related]
19. A novel multiple instance learning method based on extreme learning machine.
Wang J; Cai L; Peng J; Jia Y
Comput Intell Neurosci; 2015; 2015():405890. PubMed ID: 25705220
[TBL] [Abstract][Full Text] [Related]
20. Dynamic extreme learning machine and its approximation capability.
Zhang R; Lan Y; Huang GB; Xu ZB; Soh YC
IEEE Trans Cybern; 2013 Dec; 43(6):2054-65. PubMed ID: 23757515
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]