Multi-species PSO and fuzzy systems of Takagi-Sugeno-Kang type

Information Sciences

Volumn 267, Issue , 2014, Pages 240-251

  Di Martino, Ferdinando ^a   Loia, Vincenzo ^b   Sessa, Salvatore ^a  

^a UNIVERSITY OF NAPLES FEDERICO II   (Italy)

^b UNIVERSITY OF SALERNO   (Italy)

Author keywords

CVRMSE; GIS; HCMSPSO; NRMSE; Spatial analysis; Tagaki Sugeno Kang fuzzy system

Indexed keywords

ALGORITHMS; GEOGRAPHIC INFORMATION SYSTEMS; HIERARCHICAL SYSTEMS; MAPS; MEAN SQUARE ERROR; PARTICLE SWARM OPTIMIZATION (PSO);

COEFFICIENT OF VARIATION; CVRMSE; HCMSPSO; NRMSE; ROOT MEAN SQUARE ERRORS; ROOT-MEANS-SQUARE ERRORS; SPATIAL ANALYSIS; TAKAGI-SUGENO-KANG TYPES;

FUZZY SYSTEMS;

EID: 84896401307     PISSN: 00200255     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ins.2014.01.017     Document Type: Article

References (35)

1. O. Al-Jarrah, and H. Abu-Qdais Municipal solid waste landfill siting using intelligent system Waste Manage. 26 3 2006 299 306 (Pubitemid 43011378)
2. P. Bajpai, and S.N. Singh Fuzzy adaptive particle swarm optimization for bidding strategy in uniform price spot market IEEE Trans. Power Syst. 22 4 2007 2152 2160 (Pubitemid 350142017)
3. D.-b. Chen, F. Zou, and Y.-t. Wang A multi-objective endocrine PSO algorithm and application Appl. Soft Comput. 11 8 2011 4508 4520
4. X. Chen, and Y. Li A modified PSO structure resulting in high exploration ability with convergence guaranteed IEEE Trans. Syst. Man Cyber. 37 5 2007 1271 1289 (Pubitemid 47534592)
5. F. Di Martino, V. Loia, and S. Sessa A fuzzy-based tool for modelization and analysis of the vulnerability of aquifers: a case study Int. J. Approx. Reason. 38 1 2005 99 111
6. F. Di Martino, V. Loia, S. Sessa, and M. Giordano An evaluation of the reliability of a GIS based on fuzzy logic, in a concrete case study F.E. Petry, V.B. Robinson, M.A. Cobb, Fuzzy Modeling with Spatial Information for Geographic Problems 2005 Springer Heidelberg 185 208
7. F. Di Martino, V. Loia, and S. Sessa Fuzzy systems based on multi-species PSO method in spatial analysis Adv. Fuzzy Syst. 2012 8 10.1155/2012/808361 ID 808361
8. A.E. Gunes, and J.P. Kovel Using GIS in emergency management operations J. Urban Plann. Dev. 126 3 2000 136 149
9. C.-F. Juang, and C.-M. Hsiao Hierarchical cluster-based multispecies particle-swarm optimization for fuzzy system optimization IEEE Trans. Fuzzy Syst. 18 1 2010 14 26
10. C.F. Juang A hybrid of genetic algorithm and particle swarm optimization for recurrent network design IEEE Trans. Syst. Man Cyber. 34 2 2004 997 1006
11. J. Kennedy, R. Eberhart, Particle swarm optimization, in: Proceedings IEEE Internat. Conf. Neural Networks, 1995, pp. 1942-1948.
12. J. Kennedy, R. Eberhart, and Y. Shi Swarm Intelligence 2001 Morgan Kaufmann San Mateo (CA)
13. P. Kumar, V. Singh, and D. Reddy Advanced traveler information system for Hyderabad City IEEE Trans. Intell. Transport. Syst. 6 1 2005 26 37 (Pubitemid 40384784)
14. D. Kukolj Design of adaptive Takagi-Sugeno-Kang fuzzy models Appl. Soft Comput. 2 2002 89 103 (Pubitemid 40421591)
15. P.C. Nayak, and S.K. Jain Modelling runoff and sediment rate using a neuro-fuzzy technique Proc. ICE-Water Manage. 164 4 2011 201 209
16. T. Niknam, and B. Amiri An efficient hybrid approach based on PSO, ACO and k-means for cluster analysis Appl. Soft Comput. 10 1 2010 183 197
17. E.V. Ocalir, O.Y. Ercoskun, and R. Tur An integrated model of GIS and fuzzy logic for location decisions of taxicab stands Expert Syst. Appl. 37 7 2010 4892 4901
18. D. Parrott, and X. Li Locating and tracking multiple dynamic optima by a particle swarm model using speciation IEEE Trans. Evol. Comput. 10 4 2006 440 458 (Pubitemid 44251377)
19. K.E. Parsopoulos, M.N. Vrahatis, Particle swarm optimization method in multi objective problems, in: Proceedings of ACM Symposium on Applied Computing, Madrid, 2002, pp. 603-607. (Pubitemid 35009656)
20. K.E. Parsopoulos, and M.N. Vrahatis Particle Swarm Optimization and Intelligence: Advances and Applications 2010 Information Science Publishing
21. M.E.H. Pedersen, and A.J. Chipperfield Simplifying particle swarm optimization Appl. Soft Comput. 10 2 2010 618 628
22. J. Qin, X. Li, and Y. Yin An algorithmic framework of discrete particle swarm optimization Appl. Soft Comput. 12 3 2012 125 1130
23. A. Ratnaweera, S.K. Halgamuge, and H.C. Watson Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients IEEE Trans. Evol. Comput. 8 3 2004 240 255
24. S.M. Seyedpoora, J. Salajeghehb, E. Salajeghehb, and S. Gholizadehc Optimal design of arch dams subjected to earthquake loading by a combination of simultaneous perturbation stochastic approximation and particle swarm algorithms Appl. Soft Comput. 11 11 2011 39 48
25. Y. Shi, R.C. Eberhart, A modified particle swarm optimizer, in: Proceedings IEEE Internat. Conference Evol. Comput., 1998, pp. 69-73.
26. M. Sugeno, and G.T. Kang Structure identification of fuzzy model Fuzzy Sets Syst. 28 1988 15 33
27. T. Takagi, and M. Sugeno Fuzzy identification of systems and its applications to modeling and control IEEE Trans. Syst. Man Cyber. 15 1985 116 132
28. A.P. Tang, L.L. Xie, and X.X. Tao Application of GIS to build earthquake emergency response system for urban area J. Harbin Inst. Technol. 9 2002 38 42
29. C.H. Tsai, W.C. Wang, C.W. Chen, H.L. Chen, and M.L. Lin The construction of decision model for tourism disaster evacuation based on GIS and fuzzy theory World Acad. Sci. Eng. Technol. 54 2009 81 85
30. M.H. Vahidnia, A.A. Alesheikh, and A. Alimohammadi Hospital site selection using fuzzy ahp and its derivatives J. Environ. Manage. 90 10 2009 3048 3056
31. F. Van Den Bergh, and A.P. Engelbrecht A cooperative approach to particle swarm optimization IEEE Trans. Evol. Comput. 8 3 2004 225 239
32. J. Wei, and Y. Wang Multi-objective fuzzy particle swarm optimization based on elite archiving and its convergence J. Syst. Eng. Electron. 19 5 2008 1035 1040
33. Z. Xinchao A perturbed particle swarm algorithm for numerical optimization Appl. Soft Comput. 10 1 2010 119 124
34. W. Zhang, and Y. Liu Multi-objective reactive power and voltage control based on fuzzy optimization strategy and fuzzy adaptive particle swarm Int. J. Electr. Power Energy Syst. 30 9 2008 525 532
35. D. Zheng, W. Kainz, Fuzzy rule extraction from GIS data with a neural fuzzy system for decision making, ACM GIS '99, Kansas City, 1999, pp. 79-84.