Abstract
Present paper reports an upgrade of particle swarm optimization (PSO) algorithm for fuzzy environment by the definition of the particles as fuzzy numbers and reformulating their motion by fuzzy equations. The proposed fuzzified PSO is used to construct a set of fuzzy hyperplanes in the feature space to distinguish different classes. Fuzzy decision hyperplane assign a fuzzy membership to each sample rather than allocating to a specific class. Also the weight vector of fuzzy decision hyperplane is a set of fuzzy numbers. The proposed fuzzy classifier is called fuzzified particle swarm classifier (FPS-classifier) and its performance is evaluated by some artificial and well known benchmarks data sets.
Similar content being viewed by others
References
Askari H, Zahiri S-H (2012) Decision function estimation using intelligent gravitational search algorithm. Int J Mach Learn Cybern 3:163–172
Bahrololoum A, Nezamabadi-pour H, Bahrololoum H, Saeed M (2012) A prototype classifier based on gravitational search algorithm. Appl Soft Comput 12(2):819–825
Bandyopadhyay S, Murthy CA, Pal SK (1999) Theoretical performance of genetic pattern classifier. J Franklin Inst 336(3):387–422
Duda RO, Hart PE, Stork DG (2001) Pattern classification. Wiley, New York
Hao PY (2008) Fuzzy one-class support vector machines. Fuzzy Sets Syst 159(18):2317–2336
He YL, Wang XZ, Huang JZX (2016) Fuzzy nonlinear regression analysis using a random weight network. Inf Sci 364–365(10):222–240
Hrivastri S, Deshmukh R (2014) Data classification particle swarm optimization and gravitational search algorithm. Int J Innovat Res Sci Eng Technol (IJIRSET) 3(2):9734–9741
A-b Ji, Chen S, Hua Q (2014) Fuzzy classifier based on fuzzy support vector machine. J Intell Fuzzy Syst 26(1):421–430
Kaufmann M (2015) Inductive fuzzy classification in marketing analytics. Springer International Publishing
Keller J, Gray M, Givens J (1985) A fuzzy k-nearest neighbor algorithm. IEEE Trans Syst Man Cybern 15:580–585
Keller JM, Hunt DJ (1985) Incorporating fuzzy membership functions into the perceptron algorithm. Pattern Anal Mach Intell IEEE Trans PAMI 7(6):693–699
Kennedy J, Eberhart RC (1995) Particle swarm optimization. In: Paper presented at the proceedings of the IEEE international conference on neural networks
Liu B (1998) Minimax chance constrained programming models for fuzzy decision systems. Inf Sci 112:25–38
Z-g Liu, Pan Q, Dezert J, Mercier G (2014) Credal classification rule for uncertain data based on belief functions. Pattern Recogn 47(7):2532–2541
Ming M, Friedman M, Kandel A (1999) A new fuzzy arithmetic. Fuzzy Sets Syst 108:83–90
Rahgooy T, Yazdi HS, Monsefi R (2009) Fuzzy complex system of linear equations applied to circuit analysis. Int J Comput Electr Eng 1(5):537–538
Salimi J, Ghadiri N, Afrabandpey H (2015) Fuzzy least squares twin support vector machines. CoRR abs/1505.05451:1–16
Shahraki H, Zahiri S-H (2013) Design and simulation of an RF MEMS switch for removing the self: actuation and latching phenomena using PSO method. Iran J Electr Comput Eng 12:56–63
Shahraki H, Zahiri S-H (2015) Classification of trapezoidal fuzzy data based on heuristic classifiers. Kasmera J 43:128–144
Shahraki H, Zahiri S-H (2015) Particle swarm classifier for fuzzy data sets. In: Paper presented at the artificial intelligence and signal processing (AISP)
Simpson PK (1992) Fuzzy min-max neural networks. I. Classification. Neural Netw IEEE Trans 3(5):776–786
Wang XZ (2015) Uncertainty in learning from big data-editorial. J Intell Fuzzy Syst 28(5):2329–2330
Wang XZ, Ashfaq RAR, Fu AM (2015) Fuzziness based sample categorization for classifier performance improvement. J Intell Fuzzy Syst 29(3):1185–1196
Wang XZ, He YL, Dong LC, Zhao HY (2011) Particle swarm optimization for determining fuzzy measures from data. Inf Sci 181(19):4230–4252
Wang XZ, Xing HJ, Li QH, Dong CR, Pedrycz W (2015) A study on relationship between generalization abilities and fuzziness of base classifiers in ensemble learning. IEEE Trans Fuzzy Syst 23(5):1638–1654
Werro N (2015) Fuzzy classification of online customers. Springer International Publishing
Zadeh LA (1965) Fuzzy sets. Inf Control 8(3):338–353
Zahiri S-H (2012) Classification rule discovery using learning automata. Int J Mach Learn Cybernet 3:205–213
Zahiri S-H, Mashhadi HR, Seyedin S-A (2005) Intelligent and robust Genetic algorithm based classifier. Iran J Electr Electron Eng 1(3):1–9
Zahiri S-H, Seyedin S-A (2007) Swarm intelligence based classifiers. J Franklin Inst 344(5):362–376
Zahiri S-H, Seyedin S-A (2009) Using multi-objective Particle Swarm optimization for designing novel classifiers. Swarm Intell Multi-object Probl Data Mining 242:65–92
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Shahraki, H., Zahiri, SH. Fuzzy decision function estimation using fuzzified particle swarm optimization. Int. J. Mach. Learn. & Cyber. 8, 1827–1838 (2017). https://doi.org/10.1007/s13042-016-0561-8
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s13042-016-0561-8