An improved swarm optimized functional link artificial neural network (ISO-FLANN) for classification

Journal of Systems and Software

Volumn 85, Issue 6, 2012, Pages 1333-1345

  Dehuri, Satchidananda ^a   Roy, Rahul ^b   Cho, Sung Bae ^c   Ghosh, Ashish ^b  

^a FAKIR MOHAN UNIVERSITY   (India)

^b INDIAN STATISTICAL INSTITUTE   (India)

^c Yonsei University   (South Korea)

Author keywords

Classification; Data mining; FSN; Functional link artificial neural networks; Improved particle swarm optimization; Multi layer perception; Particle swarm optimization; SVM

Indexed keywords

FSN; FUNCTIONAL LINK ARTIFICIAL NEURAL NETWORKS; IMPROVED PARTICLE SWARM OPTIMIZATION; MULTI-LAYER PERCEPTION; PARTICLE SWARM; SVM;

CLASSIFICATION (OF INFORMATION); DATA MINING; LEARNING ALGORITHMS; NEURAL NETWORKS; PROBLEM SOLVING; RADIAL BASIS FUNCTION NETWORKS; REACTIVE POWER; SUPPORT VECTOR MACHINES;

NETWORK LAYERS;

EID: 84859519948     PISSN: 01641212     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jss.2012.01.025     Document Type: Article

References (51)

1. Bäck T.; and Schwefel H.P. An overview of evolutionary algorithms for parameter optimization Evolutionary Computing 1 1993 1 23
2. Bergh F.V.D.; and Engelbrecht A.P. A study of particle swarm optimization particle trajectories Information Sciences 176 8 2006 937 971 (Pubitemid 43190068)
3. Blake, C.L.; Merz, C.J. UCI Repository of Machine Learning Databases. http://www.ics.uci.edu/ mlearn/MLRepository.html.
4. Carvalho M.; and Ludermir T.B. Particle swarm optimization of neural network architectures andweights 7th International Conference on Hybrid Intelligent Systems, 2007 2007 336 339
5. Chang C.G.; Wang D.W.; Liu Y.C.; and Qi B.K. Application of particle swarm optimization based bp neural network on engineering project risk evaluating Third International Conference on Natural Computation, 2007, ICNC 2007, volume 1 2007 750 754
6. Clerc M.; and Kennedy J. The particle swarm - explosion, stability, and convergence in a multidimensional complex space IEEE Transactions on Evolutionary Computation 6 1 2002 58 73 (Pubitemid 34404564)
7. Da Yi, and Xiurun Ge An improved PSO-based ANN with simulated annealing technique Neurocomputing 63 2005 527 533 (Pubitemid 40103877)
8. Decker R.; and Kroll F. Classification in marketing research by means of LEM2-generated rules Decker R. Lenz H.J. Advances in Data Analysis, Studies in Classification, Data Analysis, and Knowledge Organization 2007 Springer Berlin Heidelberg 425 432
9. Dehuri S.; and Cho S.B. Evolutionarily optimized features in functional link neural network for classification Expert System and Applications 37 2010 4379 4391
10. Dehuri S.; and Cho S.B. A hybrid genetic based functional link artificial neural network with a statistical comparison of classifiers over multiple datasets Neural Computing Applications 19 2010 317 328
11. Dehuri S.; Patnaik S.; Ghosh A.; and Mall R. Application of elitist multi-objective genetic algorithm for classification rule generation Applied Soft Computing 8 1 2008 477 487 (Pubitemid 47374580)
12. Demšar J. Statistical comparisons of classifiers over multiple data sets Journal of Maching Learning Research 7 2006 1 30 (Pubitemid 43022939)
13. Eberhart R.C.; and Shi Y. Comparing inertia weights and constriction factors in particle swarm optimization Proceedings of the 2000 Congress on Evolutionary Computation 2000. volume 1 2000 84 88
14. García S.; Fernández A.; Luengo J.; and Herrera F. Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: Experimental analysis of power Information Sciences 180 2010 2044 2064
15. Ge H.W.; Qian F.; Liang Y.C.; Du W.L.; and Wang L. Identification and control of nonlinear systems by a dissimilation particle swarm optimization-based elman neural network Nonlinear Analysis: Real World Applications 9 4 2008 1345 1360 (Pubitemid 351685784)
16. Goldberg David E. Genetic Algorithms in Search, Optimization and Machine Learning 1st edition 1989 Addison-Wesley Longman Publishing Co.; Inc. Boston, MA, USA
17. Guerra F.A.; and Coelho L.D.S. Multi-step ahead nonlinear identification of lorenz's chaotic system using radial basis neural network with learning by clustering and particle swarm optimization. Chaos Solitons & Fractals 35 5 2008 967 979 (Pubitemid 47562758)
18. Hamamoto Y.; Uchimura S.; and Tomita S. A bootstrap technique for nearest neighbor classifier design IEEE Transactions onPattern Analysis and Machine Intelligence 19 1 1997 73 79 (Pubitemid 127762882)
19. Han F.; Ling Q.H.; and Huang D.S. Modified constrained learning algorithms incorporating additional functional constraints into neural networks Information Sciences 178 2008 907 919 (Pubitemid 350050971)
20. Hsu C.W.; and Lin C.J. A comparison of methods for multi-class support vector machines IEEE Transactions on Neural Networks 13 2 2002 415 425
21. Jiang M.; Luo Y.P.; and Yang S.Y. Stochastic convergence analysis and parameter selection of the standard particle swarm optimization algorithm Information Processing Letters 102 1 2007 8 16 (Pubitemid 46186357)
22. John Paul T.; Yusiong, Prospero C.; and Naval Jr Training neural networks using multiobjective particle swarm optimization ICNC (1) 2006 879 888 (Pubitemid 44617976)
23. Kang M.; and Brown D.P. A modern learning adaptive functional neural network applied to handwritten digit recognition Information Sciences 178 2008 3802 3812
24. Kennedy J.; and Eberhart R. Swarm Intelligence Morgan Kaufmann 3rd edition 2001 Academic Press New Delhi, India
25. Kennedy J.; and Eberhart R.C. Particle swarm optimization Proceedings of the IEEE International Conference on Neural Networks Perth, Australia 1995 1942 1948
26. King R.D.; Feng C.; and Sutherland A. Statlog: Comparison of classification algorithms on large real-world problems Applied Artificial Intelligence 9 3 1995 289 333
27. Liu H.B.; Tang Y.Y.; Meng J.; and Ji Y. Neural networks learning using vbest model particle swarm optimisation Proceedings of 2004 International Conference on Machine Learning and Cybernetics 2004, volume 5 2004 3157 3159
28. B. Liu, L. Wang, Y.-H. Jin, F. Tang, and D.-X. Huang Improved particle swarm optimization combined with chaos Chaos, Solitons & Fractals 0960-0779 25 5 2005 1261 1271 (Pubitemid 40643077)
29. Luengo J.; García S.; and Herrera F. A study on the use of statistical tests for experimentation with neural networks: Analysis of parametric test conditions and non-parametric tests Expert System with Applications 36 2009 7798 7808
30. Marinakis Y.; Marinaki M.; Dounias G.; Jantzen J.; and Bjerregaard B. Intelligent and nature inspired optimization methods in medicine: the pap smear cell classification problem Expert Systems 26 5 2009 433 457
31. Mazurowski M.A.; Habas P.A.; Zurada J.M.; Lo J.Y.; Baker J.A.; and Tourassi G.D. Training neural network classifiers for medical decision making: the effects of imbalanced datasets on classification performance Neural Networks 21 2-3 2008 427 436
32. Mishra B.B.; and Dehuri S. Functional link artificial neural network for classification task in data mining Journal of Computer Science 3 2007 948 955
33. Mishra B.B.; Dehuri S.; Panda G.; and Dash P.K. Fuzzy swarm net (FSN) for classification in data mining The CSI Journal of Computer Science and Engineering 5 2&4(b) 2008 1 8
34. Pao Y.H. Adaptive Pattern Recognition and Neural Networks 1989 Addison Wesley
35. Pao Y.H.; Phillips S.M.; and Sobajic D.J. neural-net computing and intelligent control systems International Journal of Control Systems 56 2 1992 263 289
36. Park H.S.; and Cho S.B. An efficient attribute ordering optimization in Bayesian networks for prognostic modeling of the metabolic syndrome ICIC (3)'06 2006 381 391
37. Pereira M.; Costa V.S.; Camacho R.; Fonseca N.A.; Sim oes C.; and Brito R.M. Comparative study of classification algorithms using molecular descriptors in toxicological databases Proceedings of the 4th Brazilian Symposium on Bioinformatics: Advances in Bioinformatics and Computational Biology, BSB '09 Berlin, Heidelberg, Springer-Verlag 2009 121 132
38. Quinlan J.R. C4. 5: programs for machine learning 1993 Morgan Kaufmann Publishers Inc. San Francisco, CA, USA
39. Rudolph G. Local convergence rates of simple evolutionary algorithms with cauchy mutations IEEE Transactions on Evolutionary Computation 1 4 1997 249 258 (Pubitemid 127771033)
40. Schwefel H.P. Numerical Optimization of Computer Models 1981 John Wiley & Sons, Inc. New York, NY, USA
41. Shi Y.; and Eberhart R.C. Empirical study of particle swarm optimization Proceedings of the 1999 Congress on Evolutionary Computation, 1999. CEC 99, volume 3 1999 6 9
42. Trelea I.C. The particle swarm optimization algorithm: convergence analysis and parameter selection Information Processing Letters 85 6 2003 317 325
43. Wu J.; Jin L.; and Liu M. Modeling meteorological prediction using particle swarm optimization and neural network ensemble Wang J. Yi Z. Zurada J. Lu B.L. Yin H. Advances in Neural Networks - ISNN 2006, volume 3973 of Lecture Notes in Computer Science 2006 Springer Berlin/Heidelberg 1202 1209 (Pubitemid 44045845)
44. Yager R.R. An extension of the naive Bayesian classifier Information Sciences 176 5 2006 577 588 (Pubitemid 41668600)
45. Yang J.M.; and Kao C.Y. A robust evolutionary algorithm for training neural networks Neural Computing & Applications 10 2001 214 230
46. Yu J.; Xi L.; and Wang S. An improved particle swarm optimization for evolving feedforward artificial neural networks Neural Processing Letters 26 2007 217 231 (Pubitemid 350005976)
47. Yung Y.; and Shaw M.J. Introduction to fuzzy decision tree Fuzzy Set and Systems 69 1 1995 125 139
48. Zhang G.P. Neural networks for classification: a survey. IEEE Transactions on Systems Man and Cybernetics Part C: Applications and Reviews 30 4 2000 451 462
49. Zhang J.; Lok T.; and Lyu M. A hybrid particle swarm optimization-back- propagation algorithm for feedforward neural network training Applied Mathematics and Computation 185 2 2007 1026 1037 (Pubitemid 46335819)
50. Zhao L.; and Yang Y. Pso-based single multiplicative neuron model for time series prediction Expert System Application 36 2009 2805 2812
51. Schutte J.F.; and Groenwold A.A. A study of global optimization using particle swarms Journal of Global Optimization 31 2005 93 108 (Pubitemid 40608861)