PSO Papers

Features

  • Improving Classifier Fusion Using Particle Swarm Optimization
    Kalyan Veeramachaneni, Lisa Osadciw, Kai Goebel, and Weizong Yan
    IEEE Fusion Conference, Italy, July, 2006, (20% acceptance rate)
    http://web.syr.edu/~laosadci/fusion2006_final.pdf
      

  • A PSO-aided neuro-fuzzy classifier employing linguistic hedge concepts 
    Amitava Chatterjee and Patrick Siarry
    Expert Systems with Applications 
     
    The present paper proposes the development of an adaptive neuro-fuzzy classifier which employs two relatively less explored and comparatively new problem solving domains in fuzzy systems. The relatively less explored field is the domain of the fuzzy linguistic hedges which has been employed here to define the flexible shapes of the fuzzy membership functions (MFs). To achieve finer and finer adaptation, and hence control, over the fuzzy MFs, each MF is composed of several piecewise MF sections and the shape of each such MF section is varied by applying a fuzzy linguistic operator on it. The system employs a Takagi-Sugeno based neuro-fuzzy system where the rulenext term consequences are described by zero order elements. This proposed linguistic hedge based neuro-fuzzy classifier (LHBNFC) employs a relatively new field in the area of combinatorial metaheuristics, called particle previous termswarmnext term optimization (PSO), for its efficient learning. PSO has been employed in this scheme to simultaneously tune the shape of the fuzzy MFs as well as the previous termrulenext term consequences for the entire fuzzy previous termrulenext term base. The performance of the proposed system is demonstrated by implementing it for two classical benchmark data sets: (i) the iris data and (ii) the thyroid data. Performance comparison vis-à-vis other available algorithms shows the effectiveness of our proposed algorithm.
     

  • PERCEPTIVE PARTICLE SWARM OPTIMISATION: AN INVESTIGATION
    Boonserm Kaewkamnerdpong and Peter J. Bentley
    http://www.cs.ucl.ac.uk/staff/B.Kaewkamnerdpong/bkpb-sis05.pdf
     
  • Tree swarm optimization: an approach to PSO-based tree discovery
    Veenhuis, C.   Koppen, M.   Kruger, J.   Nickolay, B.
    Evolutionary Computation, 2005. The 2005 IEEE Congress on Publication Date: 2-
     
    In recent years a swarm-based optimization methodology called particle swarm optimization (PSO) has developed. PSO is highly explorative and primarily used in function optimization. This paper proposes a swarm-based learning algorithm based on PSO which is able to discover trees in tree spaces. Particles are flying through a tree space forming flocks around peaks of a fitness function. Because it inherits the explorative property of PSO, it needs only few evaluations to find suitable trees.
     
  • Supervised Classification in High Dimensional Space: Geometrical, Statistical, and Asymptotical Properties of Multivariable Data
    L. O. Jimenez, and D. A. Landgrebe
    IEEE Transactions on Systems, Man and Cybernetics, Vol 28, No. 1, February 1998, pp. 39-54.
     
  • Classification of Hyperdimensional Data Based On Feature and Decision Fusion Approaches Using Projection Pursuit, Majority Voting, and Neural Networks
    L. O. Jimenez
    IEEE Transactions on Geoscience and Remote Sensing, accepted.
     
  • Hyperspectral Data Analysis and Feature Reduction Via Projection Pursuit
    L. O. Jimenez and D. A. Landgrebe
    IEEE Transactions on Geoscience and Remote Sensing, submitted and accepted.
     
  • Link where I got the remote sensing data used for the experiments
    http://ece.uprm.edu/~jimenez/
     

Conferences

  • Particle Swarm Optimization
    Kennedy, J., Eberhart, R., 1995,
    Proc. IEEE Int’l. Conf. on Neural Networks (Perth, Australia), IEEE Service Center, Piscataway, NJ, IV: 1942-1948
     
  • FPGA Implementation of Particle Swarm Optimization for Inversion of Large Neural Networks
    Paul D. Reynolds, Russell W. Duren, Matthew L. Trumbo & Robert J. Marks II
    Proceedings 2005 IEEE Swarm Intelligence Symposium. SIS 2005. June 8-10, Pasadena, pp. 389 - 392 http://web.ecs.baylor.edu/faculty/marks/REPRINTS/2005-FPGAImplementationOfParticleSwarm.pdf 
      

IEEE Transactions on Evolutionary Computation

  • The particle swarm - Explosion, stability, and convergence in a multi-dimensional complex space
    M. Clerc and J.Kennedy
    IEEE Trans. Evol. Comput., vol. 6, pp. 58–73, Feb. 2002.
     

IEEE Transactions on Power Systems

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IEEE Transactions on Magnetics

Kernels

Journals

  • Particle swarm based data mining algorithms for classiffication tasks.
    Sousa T, Silva A, Neves A (2004)
    Parallel Computing, 30:767-783.
     

  • Particle swarm based data mining algorithms for classiffication tasks
    Sousa T, Silva A, Neves A (2004)
    Parallel Computing, 30:767-783.
     

Misc.

  • Swarm Intelligence: Foundations, Perspectives and Applications
    http://www.softcomputing.net/swarm-chapter.pdf
     

  • Particle swarm optimization for image clustering (2005)
    Omran M, Engelbrecht P A and Salman A
    International Journal of Pattern Recognition and Artifficial Intelligence, 19(3):297-321.
     

  • Fuzzy discrete particle swarm optimization for solving traveling salesman problem.
    Pang W, Wang K P, Zhou C G, at el. (2004)
    Proceedings of the 4th International Conference on Computer and Information Technology, IEEE CS Press.
     

  • Fuzzy adaptive particle swarm optimization.
    Shi Y H and Eberhart R C (2001)
    Proceedings of IEEE International Conference on Evolutionary Computation, 101-106.
     

  • Popularity: A book [Kennedy and Eberhart, 2001]
     

  • Recent special issue
    IEEE Transaction on Evolutionary Computation [Vol. 8, June 2004]
    http://ieeexplore.ieee.org/xpl/tocresult.jsp?isYear=2004&isnumber=28981&Submit32=Go+To+Issue
     

Papers

  • References from chapter at
    http://www.softcomputing.net/swarm-chapter.pdf
     

  • Particle swarm optimization for image clustering (2005)
    Omran M, Engelbrecht P A and Salman A
    International Journal of Pattern Recognition and Artifficial Intelligence, 19(3):297-321.
     

  • Fuzzy discrete particle swarm optimization for solving traveling salesman problem.
    Pang W, Wang K P, Zhou C G, at el. (2004)
    Proceedings of the 4th International Conference on Computer and Information Technology, IEEE CS Press.
     

  • Fuzzy adaptive particle swarm optimization.
    Shi Y H and Eberhart R C (2001)
    Proceedings of IEEE International Conference on Evolutionary Computation, 101-106.
     

  • Hybrid Particle Swarm Optimiser with Breeding and Subpopulations
    Morten Løvbjerg and Thomas Kiel Rasmussen and Thiemo Krink
    http://www.evalife.dk/publications/ML_GECCO2001_PSO_with_breeding.pdf
     

  • Multi-exemplars Particle Swarm Optimization Algorithm
    J. J. Liang, A. K. Qin, P. N. Suganthan and S. Baskar
    11th Int. Conf. on Neural Information Processing (ICONIP2004), Calcutta, India, Vol. 3316, pp. 230-235, Nov., 2004.
    http://www.ntu.edu.sg/home/epnsugan/index_files/papers/iconip04-CLPSO.pdf 
     

  • Particle Swarm Optimization based predictive control of Proton Exchange Membrane Fuel Cell (PEMFC)
    REN Yuan, CAO Guang-yi, ZHU Xin-jian
    http://www.zju.edu.cn/jzus/2006/A0603/A060328.pdf
     

  • PSO Bibliography - Theoretical Studies
    http://tracer.uc3m.es/tws/pso/full_bibliography.html
     

  • Binary PSO
    PDF: http://clerc.maurice.free.fr/pso/binary_pso/Binary_PSO.pdf 
    Code: http://clerc.maurice.free.fr/pso/binary_pso/binary_pso_c.zip
     

  • Comparing PSO Structures to Learn the Game Checkers from Zero Knowledge
    Franken, N. Engelbrecht, AP. 2003.
    IEEE Congress on Evolutionary Computation, Canberra, Australia, 2003, 234-241, IEEE
    http://cirg.cs.up.ac.za/publications/CEC2003a.zip
     

  • Evaluation of the Particle Swarm Algorithm for Biomechanical Optimization
    Jaco F. Schutte, Byung-Il Koh2, Jeffrey A. Reinbolt, Benjamin J. Fregly1,3, Raphael T. Haftka1, and Alan D. George
      
  • Parallel Global Optimization with the Particle Swarm Algorithm
    J.F. Schutte1, J.A. Reinbolt2, B.J. Fregly1,2, R.T. Haftka1, A.D. George
     

  • PSOt, A Particle Swarm Optimization Toolbox for Matlab (2003)
    Birge, B.,
    IEEE Swarm Intelligence Symposium Proceedings, April 24-26
     
  • Computational Intelligence
    Eberhart, R., Simpson, P., Dobbins, R., 1996,
    PC Tools, Academic Press, Inc., pp. 212-223.
     
  • A Genetic Algorithm for Function Optimization: A Matlab Implementation
    Houck, C., Joines, J., and Kay M.
    ACM Transactions on Mathematical Software
     
  • Kennedy, J., Eberhart, R., Shi, Y., 2001, Swarm Intelligence
    Academic Press, Inc.
     
  • Particle swarm optimization
    J. Kennedy and R. Eberhart
    Proc. IEEE Int. Conf. Neural Networks, 1995, pp. 1942–1948.
     
  • The particle swarm: Social adaptation of knowledge
    J. Kennedy
    Proc. IEEE Int. Conf. Evolutionary Computation, 1997, pp. 303–308.
     
  • Behavior of particles
    Lecture Notes in Computer Science, vol. 1447, Proc. 7th Int. Conf.
    Evolutionary Programming—Evolutionary Programming VII, Mar. 1998, pp. 581–589.
     
  • A discrete binary version of the particle swarm algorithm
    J. Kennedy and R. Eberhart
    Proc. IEEE Int. Conf. Systems, Man, Cybernetics, Computational Cybernetics, Simulation, vol. 5, 1997, pp. 4104–4108.
     
  • Stereotyping: Improving particle swarm performance with cluster analysis
    J. Kennedy
    Proc. IEEE Int. Conf. Evolutionary Computation, vol. 2, 2000, pp. 303–308.
     
  • Matching algorithms to problems: An experimental test of the particle swarm and some genetic algorithms on the multi-modal problem generator
    J. Kennedy and W. M. Spears
    Proc. IEEE World Congr. Computational Intelligence, May 1998, pp. 78–83.
     
  • Using selection to improve particle swarm optimization
    P. J. Angeline
    Proc. IEEE Int. Conf. Computational Intelligence, 1998, pp. 84–89.
     
  • Evolutionary optimization verses particle swarm optimization: Philosophy and the performance difference
    P. J. Angeline
    Lecture Notes in Computer Science, vol. 1447, Proc. 7th Int. Conf. Evolutionary Programming - Evolutionary Programming VII, Mar. 1998, pp. 600–610.
     
  • The swarm and the queen: Toward a deterministic and adaptive particle swarm optimization
    M. Clerc
    Proc. IEEE Int. Congr. Evolutionary Computation, vol. 3, 1999, p. 1957.
     
  • Particle swarm optimization: Developments, applications and resources
    R. C. Eberhart and Y. Shi
    Proc. IEEE Int. Conf. Evolutionary Computation, vol. 1, 2001, pp. 81–86.
     
  • Comparing inertia weights and constriction factors in particle swarm optimization
    Y. Shi and R. C. Eberhart
    Proc. IEEE
     
  • Comparison between genetic algorithms and particle swarm optimization
    Y. Shi and R. C. Eberhart
    Lecture Notes in Computer Science - Evolutionary Programming VII, vol. 1447, Proc. 7th Int. Conf. Evolutionary Programming, Mar. 1998, pp. 611–616.
     
  • Parameter selection in particle swarm optimization
    Y. Shi and R. C. Eberhart
    Lecture Notes in Computer Science—Evolutionary Programming VII, vol. 1447, Proc. 7th Int. Conf. Evolutionary Programming, Mar. 1998, pp. 591–600.
     
  • A modified particle swarm optimizer
    Y. Shi and R. C. Eberhart
    Proc. IEEE Int. Conf. Evolutionary Computation, 1998, pp. 69–73.
     
  • Fuzzy adaptive particle swarm optimization
    Y. Shi and R. C. Eberhart
    Proc. IEEE Int. Congr. Evolutionary Computation, vol. 1, 2001, pp. 101–106.
     
  • Empirical study of particle swarm optimization
    Y. Shi and R. C. Eberhart
    Proc. IEEE Int. Congr. Evolutionary Computation, vol. 3, 1999, pp. 101–106.
     
  • Hybrid particle swarm optimizer with breeding and subpopulation
    M. Lovbjerg, T. K. Rasmussen, and T. Krink
    Proc. 3rd Genetic Evolutionary Computation Conf. (GECCO-2001), San Francisco, CA, July 2001, pp. 469–476.
     
  • Particle swarm optimizer with neighborhood operator
    P. N. Suganthan
    Proc. IEEE Int. Congr. Evolutionary Computation, vol. 3, 1999, pp. 1958–1962.
     
  • Effect of swarm size on cooperative particle swarm optimizers
    F. van den Bergh and A. P. Engelbrecht
    Proc. Genetic Evolutionary Computation Conf. (GECCO-2001), San Francisco, CA, July 2001, pp. 892–899.
     
  • Improvised music with swarms
    T. M. Blackwell and P. bentley
    in Proc. IEEE Congr. Evolutionary Computation 2002, vol. 2, Honolulu, HI, May 2002, pp. 1462–1467.
     
  • Extending particle swarm optimizers with self-organized critically
    M. Lovbjerg and T. Krink
    Proc. IEEE Int. Congr. Evolutionary Computation, vol. 2, Honolulu, HI, May 2002, pp. 1588–1593.
     
  • Division of labor in particle swarm optimization
    J. S. Vesterstrom, J. Riget, and T. Krink
    Proc. IEEE Int. Congr. Evolutionary Computation 2002, vol. 2, Honolulu, HI, May 2002, pp. 1570–1575.
     
  • Particle swarm optimization with spatial particle extension
    T. Krink, J. S. Vesterstrom, and J. Riget
    Proc. IEEE Congr. Evolutionary Computation 2002, vol. 2, Honolulu, HI, May 2002, pp. 1474–1479.
     
  • A dissipative particle swarm optimization
    X. F. Xie, W. J. Zhang, and Z.-L.Zhi-Lian Yang
    Proc. IEEE Congr. Evolutionary Computation 2002, vol. 2, Honolulu, HI, May 2002, pp. 1456–1461.
     
  • Tracking changing extrema with particle swarm optimizer
    A. Carlisle and G. Dozier
    Auburn Univ., Auburn, AL, Tech. Rep. CSSE01-08, 2001.
     
  • Particle swarm optimization method in multiobjective problems
    K. E. Parsopoulos and M. N. Vrahatis
    Proc. ACMSymp. Applied Computing 2002 (SAC 2002), 2002, pp. 603–607.
     
  • Particle swarm optimization for minimax problems
    E. C. Laskari, K. E. Parsopoulos, and M. N. Vrahatis
    Proc. IEEE Int. Congr. Evolutionary Computation, vol. 2, Honolulu, HI, May 2002, pp. 1576–1581.
     
  • Particle swarm optimization for integer programming
    E. C. Laskari, K. E. Parsopoulos, and M. N. Vrahatis
    in Proc. IEEE Int. Congr. Evolutionary Computation, vol. 2, Honolulu, HI, May 2002, pp. 1582–1587
     
  • Genetic Algorithms in Search, Optimization, and Machine Learning
    D. E. Goldberg
    Reading, MA: Addison-Wesley, 1989.
     
  • Tracking and optimizing dynamic systems with particle swarms
    R. C. Eberhart and Y. Shi
    Proc. IEEE Congr. Evolutionary Computation 2001, Seoul, Korea, 2001, pp. 94–97.
     
  • Particle swarm optimization for reactive power and voltage control in electric power systems
    Y. Fukuyama and H. A. Yoshida
    Proc. IEEE Congr. Evolutionary Computation 2001 (CEC 2001), vol. 1, May 2001, pp. 87–93.
     
  • A discrete binary version of the particle swarm algorithm
    J. Kennedy and R. C Eberhart
    Proc. World Multiconf. Systemics, Cybernetics, Informatics, Orlando, FL, 1997, pp. 4104–4109.
     
  • Particle swarm optimization: Surfing the waves
    E. Ozcanand and C. K. Mohan
    Proc. IEEE Congr. Evolutionary Computation 1999, vol. 3, Washington, DC, 1999, pp. 1944–1999.
     
  • A particle swarm optimization for reactive power and voltage control considering voltage stability
    H. Yoshida, K. Kawata, Y. Fukuyama, and Y. Nakanishi
    Proc. Int. Conf. Intelligent System Application to Power System, Rio de Janeiro, Brazil, 1999, pp. 117–121.
     
  • NC end milling optimization using evolutionary computation
    V. Tandon, H. E. Mounayri, and H. Kishawy
    Int. J. Mach. Tools Manuf., vol. 42, no. 5, pp. 595–605, 2002.
     
  • Use of intelligent-particle swarm optimization in electromagnetics
    G. Ciuprina, D. Ioan, and I. Munteanu
    IEEE Trans. Magn., vol. 38, pp. 1037–1040, Mar. 2002.
    http://ieeexplore.ieee.org/iel5/20/21500/00996266.pdf
     
  • Particle swarm optimization with Gaussian mutation
    N. Higashi and H. Iba
    Proceedings of the IEEE Swarm Intelligence Symposium 2003 (SIS 2003), Indianapolis, IN, 2003, pp. 72–79.
     
  • Optimization of valve timing events of internal combustion engines with particle swarm optimization
    A. Ratnaweera, H. C. Watson, and S. K. Halgamuge
    Proc. 2003 Congr. Evolutionary Computation (CEC 2003), vol. 4, Canberra, Australia, Dec. 2003, pp. 2411–2418.
     
  • A Multiparent Version of the Parent-Centric Normal Crossover for Multimodal Optimization
    P. J. Ballester and W. Graham Richard
    Proc. CEC 2006. (pdf available form Dr Pedro Ballester Aristin [pedro.ballester@chem.ox.ac.uk])
     
  • Recent approaches to global optimization problems through Particle Swarm Optimization (2002)
    K. E. PARSOPOULOS and M. N. VRAHATIS
    Natural Computing 1: 235-306, 2002
    http://www.math.upatras.gr/~kostasp/papers/NatComp.pdf
     
    with MATLAB code 
     
  • Multidisciplinary Optimization of a Transport Aircraft Wing using Particle Swarm Optimization (2002)
    Gerhard Venter and Jaroslaw Sobieszczanski
    http://www.vrand.com/pub/vs_mdo_2002.pdf 
     
  • Computing Periodic Orbits of Nonlinear Mappings Through Particle Swarm Optimization (2002)
    Parsopoulos, K.E., Vrahatis, M.N.
    Proceedings of the 4th GRACM Congress on Computational Mechanics, Patras, Greece, June 27-29, 2002
    http://www.math.upatras.gr/~kostasp/papers/gracm.pdf 
     
  • Particle Swarm Optimization (PSO): A Novel Paradigm for Antenna Designs
    Yahya Rahmat-Samii, Dennis Gies, and Jacob Robinson
    http://www.ee.ucla.edu/~dgies/files/gies_ursi_2003.pdf 
    http://www.ee.ucla.edu/~dgies/files/gies_aps_2003.pdf 
    http://www.ee.ucla.edu/~dgies/files/gies_motl_2003.pdf 
     
  • Design of Linear Phase FIR Filters using Particle Swarm Optimization
    J.M.P. Langlois
    http://www.ece.queensu.ca/symposium/papers/3D_3.pdf 
     

  • Human Tremor Analysis using Particle Swarm Optimization (1999)
    R. Eberhart and X. Hu.
    PSO is used to train artificial neural network to classify tremor patients from normal subjects
    http://icdweb.cc.purdue.edu/~hux/cgi-bin/download.cgi?CEC1999Human.pdf
      

  • Data Clustering using Particle Swarm Optimization
    DW van der Merwe and AP Engelbrecht
    http://cirg.cs.up.ac.za/publications/CEC2003d.pdf 
     

  • Particle swarm optimization-based approach for optical finite impulse response filter design
    Ying Zhou, Guangjie Zeng, and Feihong Yu
    http://lcd.creol.ucf.edu/people/yzhou/publications/JAO.pdf 
     

  • A Multiparent Version of the Parent-Centric Normal Crossover for Multimodal Optimization
    P. J. Ballester and W. Graham Richard
    Proc. CEC 2006
     

  • A particle-swarm-optimized fuzzy-neural network for voice-controlled robot systems
    Chatterjee, A.; Pulasinghe, K.; Watanabe, K.; Izumi, K.
    IEEE Transactions on Industrial Electronics, Vol. 52, No. 6, Dec. 2005 Page(s):1478 - 1489
    http://ieeexplore.ieee.org/iel5/41/33004/01546363.pdf
     

Misc.

Thesis

  • An Analysis of Particle Swarm Optimizers
    Frans van den Bergh. 2001.
     

  • Training Support Vector Machines with Particle Swarms
    Ulrich Paquet. 2003.
     

  • Niching Particle Swarm Optimizers
    Riaan Brits. 2003.
     

Tutorials

Fuzzy

  • Design of PSO-based Fuzzy Classification Systems
    Chia-Chong Chen
    Tamkang Journal of Science and Engineering, Vol. 9, No 1, pp. 63 70 (2006)
    http://www2.tku.edu.tw/~tkjse/9-1/9-1-7.pdf
     

  • A Framework for Identification of Fuzzy Models Through Particle Swarm Optimization Algorithm
    Khosla, A., Kumar, S., Aggarwal, K.K.
    Proc. 2005 Annual IEEE INDICON Conference, Chennai, India, pp. 388-391, 2005.
     

  • Fuzzy PSO: A Generalization of Particle Swarm Optimization
    Abdelbar, A.M., Abdelshahid, S., Wunsch II, D.C.
    IEEE 2005 International Joint Conference on Neural Networks, Montreal, Canada, pp. 1086-1091, 2005.
     

IEEE Conferences

  • Particle swarm optimization (PSO) applied to fuzzy modeling in a thermal-vacuum system
    Marinke, R.; Araujo, E.; Coelho, Ld.S.; Matiko, I.;
    Hybrid Intelligent Systems, 2005. Fifth International Conference on 6-9 Nov. 2005 Page(s):6 pp.
     
  • Particle evolutionary swarm optimization algorithm (PESO)
    Zavala, A.E.M.; Aguirre, A.H.; Diharce, E.R.V.
    Sixth Mexican International Conference on Computer Science (ENC 2005), September 26-30, 2005 pp. 282 - 289
     

  • Investigation of particle swarm optimization for dynamic reconfiguration of field-programmable analog circuits
    Tawdross, P.; Konig, A.
    Hybrid Intelligent Systems, 2005. Fifth International Conference on 6-9 Nov. 2005 Page(s):6 pp.
     

  • Fuzzy adaptive turbulent particle swarm optimization
    Hongbo Liu; Abraham, A.
    Fifth International Conference on Hybrid Intelligent Systems, November 6-9, 2005
     

  • Using PSO algorithm to evolve an optimum input subset for a SVM in time series forecasting
    Chunkai Zhang; Hong Hu
    2005 IEEE International Conference on Systems, Man and Cybernetics, Volume 4, 10-12 Oct. 2005 Page(s):3793 - 3796 Vol. 4
     

  • PSO based bit rate optimization for MPEG-1/2 video coding
    Arachchi, H.K.; Fernando, W.A.C.
    Image Processing, 2005. ICIP 2005. IEEE International Conference on Volume 2, 11-14 Sept. 2005 Page(s):II - 329-32
     

  • A Modified Adaptive Particle Swarm Optimization Algorithm
    Wang Lei; Kang Qi; Xiao Hui; Wu Qidi
    IEEE International Conference on Industrial Technology (ICIT2005), December 14-17, 2005, pp. 209 - 214
     

  • A Particle Swarm Optimization-Based Approach for Pricing VAR Providers in the Electricity Market with the Consideration of Voltage Security
    El-Araby, E.E.; Yorino, N.;
    2005 International Conference on Future Power Systems, November 16-18, 2005, pp. 1-6
     

  • A ridgelet kernel approach for regression using particle swarm optimization algorithm
    Shuyuan Yang; Min Wang; Licheng Jiao
    Proceedings of the 2005 IEEE International Joint Conference on Neural Networks (IJCNN '05), Volume 5, 31 July-4 Aug. 2005, pp. 2837-2842 vol. 5
     

  • Lotto-type competitive learning with particle swarm features
    Luk, A.; Lien, S.
    Proceedings. 2005 IEEE International Joint Conference on Neural Networks (IJCNN '05), Volume 3, 31 July-4 Aug. 2005, pp. 1517 - 1522 vol. 3
     

  • Optimizing class-related thresholds with particle swarm optimization
    Oliveira, L.S.; Britto, A.S., Jr.; Sabourin, R.;
    Neural Networks, 2005. IJCNN '05. Proceedings. 2005 IEEE International Joint Conference on Volume 3, 31 July-4 Aug. 2005 Page(s):1511 - 1516 vol. 3
     

  • Nonlinear mappings based on particle swarm optimization
    Figueroa, C.J.; Estevez, P.A.; Hernandez, R.E.
    Proceedings of the 2005 IEEE International Joint Conference on Neural Networks (IJCNN '05), Volume 3, 31 July-4 Aug. 2005 Page(s):1487 - 1492 vol. A
     

  • Framework for Identification of Fuzzy Models through Particle Swarm Optimization Algorithm
    Khosla, A.; Kumar, S.; Aggarwal, K.K.
    INDICON, 2005 Annual IEEE Proceedings of IEEE India Annual Conference (INDICON 2005), pp. 184-187, 11-13 December, 2005, IIT Chennai
     

  • Optimal control parameters for a UPFC in a multimachine using PSO
    Venayagamoorthy, G.K.
    Intelligent Systems Application to Power Systems, 2005. Proceedings of the 13th International Conference on 6-10 Nov. 2005 Page(s):6 pp
     

  • PSO-based evolutionary optimization for black-box modeling of arbitrary shaped on-chip RF inductors
    Bhattacharya, R.; Joshi, A.; Bhattacharya, T.K.;
    Silicon Monolithic Integrated Circuits in RF Systems, 2006. Digest of Papers. 2006 Topical Meeting on 18-20 Jan. 2006 Page(s):4 pp.
     

  • A Novel Binary Particle Swarm Optimization Method Using Artificial Immune System
    Afshinmanesh, F.; Marandi, A.; Rahimi-Kian, A.
    The 2005 International Conference on Computer as a Tool  (EUROCON 2005) Volume 1, 21-24 Nov. 2005 Page(s):217 - 220
     

  • A perturbation particle swarm optimization for the synthesis of the radiation pattern of antenna array
    Zhihao Yuan; Ronghong Jin; Junping Geng; Yu Fan; Jia Lao; Jiaqiang Li; Xianyi Rui; Zhijiang Fang; Jing Sun
    Microwave Conference Proceedings, 2005. APMC 2005. Asia-Pacific Conference Proceedings Volume 3, 4-7 Dec. 2005 Page(s):4 pp.
     

  • Synthesis of antenna array using particle swarm optimization
    Chen, T.B.; Chen, Y.B.; Jiao, Y.C.; Zhang, E.S.; Microwave Conference Proceedings, 2005. APMC 2005. Asia-Pacific Conference Proceedings Volume 3, 4-7 Dec. 2005 Page(s):4 pp.
     

  • Floorplanning based on particle swarm optimization
    Tsung-Ying Sun; Sheng-Ta Hsieh; Hsiang-Min Wang; Cheng-Wei Lin;
    Emerging VLSI Technologies and Architectures, 2006. IEEE Computer Society Annual Symposium on Volume 00, 2-3 March 2006 Page(s):5 pp
     

  • An adaptive diversity strategy for particle swarm optimization
    Fang Wang; Naiqin Feng; Yuhui Qiu;
    Natural Language Processing and Knowledge Engineering, 2005. IEEE NLP-KE '05. Proceedings of 2005 IEEE International Conference on 30 Oct.-1 Nov. 2005 Page(s):760 - 764
     

  • PSO-based learning rate adjustment for blind source separation
    Chun-Ling Lin; Sheng-Ta Hsieh; tsung-Ying Sun; Chan-Cheng Liu;
    Proceedings of 2005 International Symposium on Intelligent Signal Processing and Communication Systems, (ISPACS 2005) 13-16 Dec. 2005, pp. 181-184
     

Interesting conferences on the topic

2006 - SPMC / SoCEE / UoP