Biomedical Engineering Reference
In-Depth Information
10. Rao RV, Patel V (2013) An improved teaching-learning-based optimization algorithm for
solving unconstrained optimization problems. Sci Iranica D 20(3):710 - 720. doi: 10.1016/j.
scient.2012.12.005
11. Rao RV, Waghmare GG (2014) A comparative study of a teaching - learning-based
optimization algorithm on multi-objective unconstrained and constrained functions. J King
Saud University
346. doi: 10.1016/j.jksuci.2013.12.004
12. Amiri Babak (2012) Application of teaching-learning-based optimization algorithm on cluster
analysis. J Basic Appl Sci Res 2(11):11795
Comput Inf Sci 26: 332
-
11802
13. Suresh K, Kundu D, Ghosh S, Das S, Abraham A (2009) Automatic clustering with multi-
objective differential evolution algorithms.
-
In: Evolutionary computation, 2009,
IEEE
2597
14. Kundu D, Suresh K, Ghosh S, Das S, Abraham A, Badr Y (2009) Automatic clustering using a
synergy of genetic algorithm and multi-objective differential evolution. In: Hybrid arti cial
intelligence systems. Springer, Berlin, pp 177
Congress on CEC
'
09. IEEE, pp 2590
-
186
-
15. Liu Yimin,
zyer Tansel, Alhajj Reda, Barker Ken (2005) Integrating multi-objective genetic
algorithm and validity analysis for locating and ranking alternative clustering. Informatica
29:33 - 40
16. Satapathy SC, Naik A, Parvathi K (2013) A teaching learning based optimization based on
orthogonal design for solving global optimization problems. SpringerPlus 2:130
17. Naik A, Satapathy SC, Parvathi K (2012) Improvement of initial cluster center of c-means
using teaching learning based optimization. Procedia Technol 6:428 - 435. doi: 10.1016/j.
protcy.2012.10.051
18. Murty MR et al (2014) Automatic clustering using teaching learning based optimization. Appl
Math 5:1202
Ö
1211. doi: 10.4236/am.2014.58111
19. Suresh Kaushik, Kundu Debarati, Ghosh Sayan, Das Swagatam, Abraham A, Han SY (2009)
Multi-objective differential evolution for automatic clustering with application to micro-array
data analysis. Sensors 9:3981
-
4004. doi: 10.3390/s90503981
20. Pavan KK, Rao AA, Dattatreya Rao AV, Sridhar GR (2011) Robust seed selection algorithm
for k-means type algorithms. Int J Comput Sci Inf Technol (IJCSIT) 3(5). doi: 10.5121/ijcsit.
2011.3513
21. Deb Kalyanmoy (2000) An ef cient constraint handling method for genetic algorithms.
Comput Methods Appl Mech Eng 186(2):311
-
338
22. Wilkinson L, Friendly M (2009) The history of the cluster heat map. The American Statistician
63(2)
23. Al-Shahrour F, Minguez P, T á rraga J, Medina I, Alloza E, Montaner D, Dopazo J (2007)
FatiGO+: a functional pro ling tool for genomic data. Integration of functional annotation,
regulatory motifs and interaction data with microarray experiments. Nucleic Acids Research
35 (Web Server issue):W91 - W96
24. Dennis G, Sherman BT, Hosack DA, Yang J, Baseler MW, Lane HC, Lempicki RA (2003)
DAVID: database for annotation, visualization, and integrated discovery. Genome Biology 4
(5):P3
-
Search WWH ::




Custom Search