A review on particle swarm optimization algorithms and their applications to data clustering

Artificial Intelligence Review

Volumn 35, Issue 3, 2011, Pages 211-222

  Rana, Sandeep ^a   Jasola, Sanjay ^a   Kumar, Rajesh ^b  

^a GAUTAM BUDDHA UNIVERSITY   (India)

^b MALAVIYA NATIONAL INSTITUTE OF TECHNOLOGY   (India)

Author keywords

Data clustering; Data mining; K mean clustering; Particle swarm optimization

Indexed keywords

CLASSICAL ALGORITHMS; CONVERGENCE RATES; DATA CLUSTERING; K-MEAN CLUSTERING; LITERATURE SURVEY; LOCAL OPTIMA; PARTICLE SWARM OPTIMIZATION ALGORITHM; SEARCH ALGORITHMS; SOCIAL BEHAVIOR;

CLUSTER ANALYSIS; CONVERGENCE OF NUMERICAL METHODS; DATA MINING; PARTICLE SWARM OPTIMIZATION (PSO);

CLUSTERING ALGORITHMS;

EID: 79955946974     PISSN: 02692821     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10462-010-9191-9     Document Type: Review

References (90)

1. Aguirre AH, Munoz Zavala AE, Diharce EV, Botello Rionda S (2007) COPSO: constraints optimization via PSO algorithm. Communication technics, (CC/CIMAT), pp 1-30
2. Ahalt SC, Krishnamurty AK, Chen P, Melton DE (1990) Competitive algorithms for vector quantization. Neural Netw 3:277-291
3. Ahmadi A, Karray F, Kamel MS (2007) Multiple cooperating swarms for data clustering. In: Proceedings of the IEEE swarm intelligence symposium. pp 206-212 (Pubitemid 47431841)
4. Ahmadi A, Karray Fi, Kamel MS (2009) Flocking based approach for data clustering. Springer, Berlin
5. Ahmadyfard A, Modares H (2008) Combining PSO and k-means to enhance data clustering. In: International symposium on telecommunications. pp 688-691
6. Alam S, Dobbie G, Riddle P (2008) An evolutionary particle swarm optimization algorithm for data clustering. In: Proceedings of the IEEE SIS. pp 1-6
7. Alatas B, Akin E (2008) Rough particle swarm optimization and its applications in data mining. In: Proceedings of the soft computing. Berlin, pp 1205-1208
8. Alpaydin E (2004) Introduction to machin learning. The MIT Press, Cambridge, pp 133-150
9. Alviar JB, Pena J, Hincapie R (2007) Subpopulation best rotation: a modification on PSO. Revista Facultad de Ingenieria No 40, pp 118-122
10. Boeringer D-W, Werner DH (2004) Particle swarm optimization versus genetic algorithm for phased array synthesis. IEEE Trans Antennas Propag 52(3):771-779
11. Brits R, Engelbrecht AP, Van den Bergh F (2005) Niche particle swarm optimization. Technical report, Department of Computer Science, University of Pretoria
12. Chang J-F, Chu SC, Roddick JF, Pan JS (2005) A parallel particle swarm optimization algorithm with communication strategies. J Inf Sci Eng 21(4):809-818 (Pubitemid 40972090)
13. Chen CY, Ye F (2004) Particle swarm optimization algorithm and its application to clustering analysis. In: Proceedings of the 2004 IEEE international conference on networking, sensing and control. Taipei, Taiwan, pp 789-794
14. Cui X, Potok TE, Palathingal P (2005) Document clustering using particle swarm optimization. In: Proceedings in SIS. pp 185-191
15. Das S, Abraham A, Konar A (2008) Automatic kernel clustering with a multi-elitist particle swarm optimization algorithm. Pattern Recognit Lett 29:688-699
16. Dehuri S, Ghosh A, Mall R (2006) Particle with age data clustering. In: Proceedings of IEEE 9th international conference on information technology. pp 221-224
17. Dezhen F, Zaimei Z, Fang Z, Jianheng J (2008) Application study of data mining on customer relationship management in E-commerce. In: 9th international conference on computer-aided instrial design and conceptual design. pp 2706-2710
18. Duran O, Rodriquez N, ConsalterL-A (2008) A PSO-based clustering algorithm for manufacturing cell design. In: IEEE 1st international workshop on knowledge discovery and data mining. pp 72-75
19. Esmin AAA, Pereira DL, de Araujo F (2008) Study of different approach to clustering data by using the particle swarm optimization algorithm. In: IEEE world congress on computational intelligence. pp 1817-1822
20. Felix TSC, Kumar V, Mishra N (2007) A CMPSO algorithm based approach to solve the multi-plant supply chain problem. Swarm Intelligence, Focus on Ant and Particle Swarm Optimization, pp 447-474
21. Gheitanchi S Ali, FH, Stipidis E (2008) Trained particle swarm optimization for ad-hoc collaborative computing networks. In: Swarm intell, algorithms and applications symposium, ASIB, UK, Vol 11, pp 7-12
22. Guoyin W, Jun H, Qinghua Z, Xiangquan L, Jiaqing Z (2008) Granular computing based data mining in the view of rough set and fuzzy set. In: International conference on Granular computing. Proceedings in IEEE GRC. pp 67-67
23. He Y, Pan W, Lin J (2006) Cluster analysis using multivariate normal mixture models to detect differential gene expression with microarray data. Comput Stat Data Anal 51:641-658 (Pubitemid 44635901)
24. Ho S-Y, Lin H-S, Liauh WH, Ho S-J (2008) OPSO orthogonal particle swarm optimization and its application to task assignment problems. IEEE Trans Syst Man Cyber Part A 38(2):288-298 (Pubitemid 351425583)
25. Hongwen Y, Rui Ma (2006) Design a nevel neural network clustering algorithm based on PSO and application. In: Proceedings of the IEEE world congress intelligent control and automation (WCICA), vol 2. pp 6015-6018 (Pubitemid 46540635)
26. Jain AK, Murty MN, Flynn PJ (1999) Data clustering: a reviw. ACM Comput Surv 31(3):264-323
27. Jang WS, Kang HI, Lee BH, Kim KI, Shin DI, Kim SC (2007) Optimized fuzzy clustering by predator prey particle swarm optimization. In: IEEE/CEC. pp 3232-3238
28. Janson S, Middendorf M (2004) A hierarchical particle swarm optimizer for dynamic optimization problems. In: Proceedings of the application of evolutionary computing, vol 3005. pp 513-524
29. Jarbouia B, Cheikha M, Siarryb P, Rebaic A (2007) Combinatorial particle swarm optimization (CPSO) for partitioned clustering problem. J Appl Math Comput 192(2):337-345
30. Jie J, Zeng J, Han C (2006) Self-organization particle swarm optimization based on infirmation feedback. In: Advances in natural Computing (Part-I-II: second international conference, ICNC, Xi'an, China), pp 913-922 (Pubitemid 44641546)
31. Jinxin d, Minyong Q (2009) A new algorithm for clustering based on particle swarm optimization and k-means. In: IEEE international conference on artificial intelligence and computational intelligence, vol 4. pp 264-268
32. Johnson Ryan K, Sachin Ferat (2009) Particle swarm optimization methods for data clustering. In: IEEE fifth international conference soft computing, computing with words and perceptions in system analysis, decision and control. pp 1-6
33. Junliang L, Xinping X (2008) Multi-swarm and multi-best particle swarm optimization algorithm. In: IEEE world congress on intelligent control and automation. pp 6281-6286
34. Junyan C, Huiying Z (2007) Research on application of clustering algorithm based on PSO for the web usage pattern. In: Proceedings of the IEEE international conference on wireless communications, networking and mobile computing. pp 3705-3708
35. Kao IW, Tsai CY, Wang YC (2007a) An effective particle swarm optimization method for data clustering. In: IEEE international conference on industrial engineering and engineering management. pp 548-552 (Pubitemid 351371057)
36. Kao Y-T, Zahara E, Kao I-W (2007b) A hybridized approach to data clustering. Expert Syst Appl 34: 1754-1762 (Pubitemid 350298200)
37. Kennedy J, Eberhart RC (1995) Particle swarm optimization. In: IEEE internal conference on neural networks, Perth Australia, vol 4. pp 1942-1948
38. Kennedy J (1997) Minds and cultures: particle swarm implications. Socially intelligent agents papers AAAI fall symposium technical report FS-97-02. AAAI Press, Menlo Park, CA, pp 67-72
39. Kennedy J, Eberhart RC (1997) A discrete binary version of the particle swarm algorithm. In: IEEE conference on systems, man, and cyber, vol 5. pp 4104-4108
40. Kennedy J, Eberhart RC, Shi Y (2002) Swarm intelligence. Morgan Kaufmann, Los Altos
41. Khan S, Ahmad A (2004) Cluster centre initialization algorithm for k-means clustering. Pattern Recognit lett 25:1293-1302 (Pubitemid 41161769)
42. Kiranyaz S, Ince T, Yildirim A, Gabbouj M (2009) Multi-dimensional particle swarm optimization for dynamic clustering. In: IEEE EUROCON. pp 1398-1405
43. Krink T, Vesterstrom JS, Riget J (2002) Particle swarm optimization with spatial particle extension. Proc Cong Evol Comput (CEC'02) 2:1474-1479
44. Krishna K, Murty M (1999) Genetic k-means algorithm. In: IEEE transactions on systems, man, and cybernetics, vol 29. pp 433-439
45. Lam HT, Nikolaevna PN, Quan NTM (2007) The heuristic particle swarm optimization. In: Proceedings of the annual conference on gentic and evolutionary computation in ant colony optimization, swarm Intell, and artificial immune systems GECCO'07. pp 174-174
46. Lee M, Lee Y, Meang B, Choi O (2009) A clustering algorithem using particle swarm optimization for DNA chip data analysis. In: Proceedings in ACM ICUMS-09. Suwon, S. Korea, pp 664-668
47. Li HQ, Li L (2007) A novel hybrid particle swarm optimization algorithm combined with harmony search for high dimensional optimization problems. In: Proceedings of the IEEE/IPC. pp 94-97
48. Li T, Lai X, Wu M (2006a) An improved two-swarm based particle swarm optimization algorithm. Proc IEEE/WCICA 1:3129-3133
49. Li W, Yushu L, Xinxin Z, Yuanqing X (2006b) Particle swarm optimization for fuzzy c-means clustering. In: Proceedings of the 6th world congress on intelligent control and automation, vol 2. pp 6055-6058
50. Lu H, Chen W (2008) Self-adaptive velocity particle swarm optimization for solving constrained optimization problems. J Glob Optim 41(3):427-445
51. Lu Y, Wang S, Li S, Zhou C (2009) Particle swarm optimizer for variable weighting in clustering high-dimensional data. Springer, Berlin
52. Maulik U, Bandyopadhyay S (2002) Genetic algorithm based data clustering techniques. Pattern Recogn 33:1455-1465
53. McLachlan GJ, Krishnan T (1997) The EM algorithm and extensions. Wiley, New York
54. Meissner M, Schmuker M, Schneider G (2006) Optimized paricle swarm optimization (OPSO) and its application to artificial neural network training. BMC Bioinform 7:1-11
55. Mitra S, Acharya T (2004) Data mining. Wiley, New York
56. Niasar NS, Yazdani S, Mohajeri M (2008) K-NichePSO clustering. In: IEEE international conference on machine learning and cybernetics, vol 5. pp 2668-2672
57. Niu Y, Shen L (2006) An adaptive multi-objective particle swarm optimization for color image fusion. Lecture notes in computer science, LNCS. pp 473-480 (Pubitemid 44812373)
58. Omran, M, Salman AA, Engelbrecht AP (2006) Dynamic clustering using particle swarm optimization with application in image segmentation. Pattern Anal Appl 8:332-344 (Pubitemid 43190442)
59. Ozcan E, Yilmaz M (2006) Particle swarm for multimodel optimization. In: Lecture notes in computer science, Proceedings of the 8th international conference on adaptive and natural computing algorithms, part I. pp 366-375
60. Ozcift A, Kaya M, Gulten A, Karabulut M (2009) Swarm optimized organizing map (SWOM): a swarm intelligence based optimization of self-organizing map. Published in an Expert Systems with Applications 36, an International Journal, vol 36. pp 10640-10648
61. Pampara G, Franken N, Engelbrecht AP (2005) Combining particle swarm optimization with angle modulation to solve binary problems. IEEE Cong Evol Comput 1:89-96 (Pubitemid 41495842)
62. Panov P, Dzeroski S, Soldatova L (2008) OntoDM: an ontology of data mining. In: IEEE international conference on data mining. pp 752-760
63. Paterlini S, Krink T (2006) Differential evolution and particle swarm optimization in partitional clustering. Comput Stat Data Anal 50:1220-1247 (Pubitemid 41562038)
64. Peram T, Veeramachaneni K, Mohan CK (2003) Fitness-distance-ratio based particle swarm optimization. In: Proceedings of the IEEE/SIS. pp 174-181
65. Pyle D (1999) Data preparation for data mining. Morgan Kaufmann, Los Altos
66. Qiang L, Qing-He X, Xue-Na Q (2009) A discrete particle swarm optimization algorithm with fully communicated high dimensional data. Springer, Berlin
67. Satapathy SC, Katari V, Parimi R, Malireddi S, Srujan KVNK, Mishra BB, Murthy JVR (2007) A new approach of integrating PSO and improved GA for clustering with parallel and transitional technique. In: Proceedings of the IEEE third international conference on natural computation, vol 4. pp 40-50
68. Secrest BR, Lamont GB (2003) Visulizing particle swarm optimization-gaussian particle swarm optimization. In: Proceedings of the swarm intell symposium (IEEE/SIS). pp 198-204
69. Sedighizadeh D, Masehian E (2009) An particle swarm optimization method, taxonomy and applications. In: Proceedings of the international journal of computer theory and engineering, vol 5. pp 486-502
70. Sedlaczek K, Eberhard P (2006) Using augmented lagrangian particle swarm optimization for constrained problems in engineering. J Struct Multidiscip Optim 32(4):277-286 (Pubitemid 44268027)
71. Selim SZ, Alsultan K (1991) A simulated annealing algorithm for the clustering problem. Pattern Recogn 24(10):1003-1008
72. Senthil Arumugam M, Rao MVC, Chandramohan A (2005) Competitive approaches to PSO algorithm via new acceleration co-efficient variant with mutation operators. In: Proceedings of the fifth international conference on computational intelligence and multimedia applications (ICCIMA'05'). pp 225-230 (Pubitemid 44500238)
73. Shanli W (2008) Research on a new effective data mining method based on neural networks. In: International symposium on electronic commerce and security. pp 195-198
74. Shi Y, Eberhart RC (1998) Parameter selection in particle swarm optimization. Evolutionary programming, vol 1441 of Lecture Note in computers science. Springer, Berlin, pp 591-600 (Pubitemid 128118969)
75. Shi Y, Eberhart R (2001) Fuzzy adaptive particle swarm optimization. In: Proceedings of the IEEE/congress on evolutionary computation, vol 1, pp 101-106 (Pubitemid 32806325)
76. Silva A, Neves A, Costa E (2002) Chasing the swarm: a predator pray appoach to function optimization. In: Proceedinge of the MENDEL, international conference on soft computing
77. Steinley D, Brusco MJ (2007) Initialization k-means batch clustering: a critical evaluation of several techniques. J Clasif 24:99-121
78. Subrananyam V, Srinivasan D, Oniganti R (2007) Dual layered PSO algorithm for evolving an artificial neural network controller. In: IEEE/CEC. pp 2350-2357
79. Tsai CY, Chiu CC (2008) Developing a feature weight self-adjustment mechanism for a k-means clustering algorithm. Comput Stat Data Anal 52:4658-4672
80. Van der Merwe DW, Engelhrecht AP (2003) Data clustering using particle swarm optimization. In: Conference of evolutionary computation CEC'03, vol 1. pp 215-220
81. Wang X-H, Li J-J (2004) Hybrid particle swarm optimization with simulated annealing. In: Proceedings of the IEEE international conference on machine learning and cyber, vol 4. pp 2402-2405
82. Wei C, He Z, Zhang Y, Pei W (2002) Swarm directions embedded in fast evolutionary programming. In: Proceeding of the IEEE/CEC. pp 1278-1283
83. Xie XF, Zhang WJ, Yang ZL (2002a) Adaptive particle swarm optimization on individual level. In: International conference signal processing (ICSP). pp 1215-1218
84. Xie XF, Zhang WJ, Yang ZL (2002b) A dissipative particle swarm optimization. In: Congress on evolutionary computation (CEC). pp 1456-1461
85. Xu R, Wunsch D (2005) Survey of clustering algorithm. IEEE Trans Neural Netw 16:645-678
86. Xu L, Krzyzak A, Oja E (1993) Rival penalized competitive learning for clustering analysis, RBF net and curve detection. IEEE Trans Neural Netw 4:636-648
87. Yao X (2008) Cooperatively coevolving particle swarm forlarge scale optimization. In: Conference of EPSRC, artificial intell technologies new and emerging computer paradigms
88. Zalik RK (2008) An efficient k-means clustering algorithm. Pattern Recognit Lett 29:1385-1391
89. Zeng J, Hu J, Jie J (2006) Adaptive particle swarm optimization guided by acceleration information. Proc IEEE/ICCIAS 1:351-355
90. Zhang X, Wang J, Zhang H, Guo J, Li X (2007) Spatial clustering with obstacles constraints using particle swarm optimization. In: Proceedings in conference infoscale Suzhov, China