An Efficient Self-Organizing Map Learning Algorithm with Winning Frequency of Neurons for Clustering Application

被引：0

作者：

Chaudhary, Vikas ^{[1
]}

Ahlawat, Anil K. ^{[2
]}

Bhatia, R. S. ^{[1
]}

机构：

[1] Natl Inst Technol NIT, Kurukshetra, Haryana, India

[2] Krishna Inst Engn & Technol, Dept Comp Applicat, Ghaziabad, Uttar Pradesh, India

来源：

PROCEEDINGS OF THE 2013 3RD IEEE INTERNATIONAL ADVANCE COMPUTING CONFERENCE (IACC) | 2013年

关键词：

Self-organizing map (SOM); winning frequency; modified SOM;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

u The Self-organizing map (SOM) has been extensively applied to data clustering, image analysis, dimension reduction, and so forth. The conventional SOM does not calculate the winning frequency of each neuron. In this study, we propose a modified SOM which calculate the winning frequency of each neuron. We investigate the behavior of modified SOM in detail. The learning performance is evaluated using the three measurements. We apply modified SOM to various input data set and confirm that modified SOM obtain a more effective map reflecting the distribution state of the input data.

引用

页码：672 / 676

页数：5

共 50 条

[31] The Self-Organizing Map applying the "Survival of the Fittest Type" Learning Algorithm
Shibata, Junko
Okuhara, Koji
Shiode, Shogo
Ishii, Hiroaki
ISDA 2008: EIGHTH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS DESIGN AND APPLICATIONS, VOL 3, PROCEEDINGS, 2008, : 95 - +
[32] Generalized Net Model of Optimization of the Self-Organizing Map Learning Algorithm
Petkov, Todor
Sotirov, Sotir
Popov, Stanislav
UNCERTAINTY AND IMPRECISION IN DECISION MAKING AND DECISION SUPPORT: CROSS-FERTILIZATION, NEW MODELS, AND APPLICATIONS, 2018, 559 : 316 - 324
[33] Application of the self-organizing feature map algorithm in facial image morphing
Su, MC
Liu, IC
NEURAL PROCESSING LETTERS, 2001, 14 (01) : 35 - 47
[34] Application of the Self-Organizing Feature Map Algorithm in Facial Image Morphing
Mu-Chun Su
I-Chen Liu
Neural Processing Letters, 2001, 14 : 35 - 47
[35] Application of Self-organizing Feature Map Neural Network Based on Data Clustering
Hu, Xiang
Yang, Yun
Zhang, Lihong
Xiang, Tao
Hong, Chengqiu
Zheng, Xiaotong
PROCEEDINGS OF THE 10TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION (WCICA 2012), 2012, : 797 - 802
[36] SELF-ORGANIZING MAP NETWORK AS AN INTERACTIVE CLUSTERING TOOL - AN APPLICATION TO GROUP TECHNOLOGY
KIANG, MY
KULKARNI, UR
TAM, KY
DECISION SUPPORT SYSTEMS, 1995, 15 (04) : 351 - 374
[37] Self-organizing map algorithm and distortion measure
Rynkiewicz, Joseph
NEURAL NETWORKS, 2006, 19 (6-7) : 830 - 837
[38] ENHANCING SELF-ORGANIZING MAP CAPABILITIES WITH GRAPH CLUSTERING: AN APPLICATION TO FINANCIAL MARKETS
Resta, Marina
INTELLIGENT SYSTEMS IN ACCOUNTING FINANCE & MANAGEMENT, 2016, 23 (1-2): : 21 - 46
[39] Investigation of self-organizing map for genetic algorithm
Kita, Eisuke
Kan, Shen
Fei, Zhai
ADVANCES IN ENGINEERING SOFTWARE, 2010, 41 (02) : 148 - 153
[40] Self-organizing map clustering analysis for molecular data
Wang, Lin
Jiang, Minghu
Lu, Yinghua
Noe, Frank
Smith, Jeremy C.
ADVANCES IN NEURAL NETWORKS - ISNN 2006, PT 1, 2006, 3971 : 1250 - 1255

← 1 2 3 4 5 →