Investigating the Behaviour of Radial Basis Function Networks in Regression and Classification of Geospatial Data

被引：0
|
作者：
Guidali, Andrea [1 ]
Binaghi, Elisabetta [1 ]
Guglielmin, Mauro [2 ]
Pascale, Marco [1 ]
机构：
[1] Univ Insubria, Dept Comp Sci & Commun, Via Mazzini 5, I-21100 Varese, Italy
[2] Univ Insubria, Dept Structural & Funct Biol, I-21100 Varese, Italy
来源：
INTELLIGENT DATA ENGINEERING AND AUTOMATED LEARNING - IDEAL 2010 | 2010年 / 6283卷
关键词：
Radial Basis Function Networks; Regression; Classification; Fuzzy sets; Geospatial data;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This work investigates learning and generalisation capabilities of Radial Basis Function Networks used to solve function regression and classification tasks in the environmental context. In particular RBFN is applied to solve the problem of snow cover thickness estimation in which critical aspects such as minimal training condition, weak pattern description and inconsistency among data arise. The RBFN shows good performances and high flexibility in coping with regression, hard and soft classifications which are complementary tasks in the analysis of complex environmental phenomena.
引用
收藏
页码：110 / +
页数：2
相关论文
共 50 条
  • [41] On the Comparison of Fuzzy Kernel Regression Estimator and Fuzzy Radial Basis Function Networks
    Pehlivan, Nimet Yapici
    Apaydin, Aysen
    GAZI UNIVERSITY JOURNAL OF SCIENCE, 2008, 21 (03): : 87 - 95
  • [42] Radial basis function networks, regression weights, and the expectation-maximization algorithm
    Langari, R
    Wang, L
    Yen, J
    IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS, 1997, 27 (05): : 613 - 623
  • [43] Regression Estimation by Radial Basis Function Networks With Self-Constructing Clustering
    Tu, Ching-Sheng
    Wu, Deng-Yi
    Lee, Shie-Jue
    Wu, Chih-Hung
    2018 5TH INTERNATIONAL CONFERENCE ON SYSTEMS AND INFORMATICS (ICSAI), 2018, : 327 - 332
  • [44] A Partial Least Squares Regression Method for Growing Radial Basis Function Networks
    Yin, Jianchuan
    Bi, Gexin
    Dong, Fang
    2008 CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-11, 2008, : 2562 - 2565
  • [45] Uncertainty propagation through radial basis function networks. Part I: Regression networks
    Chetwynd, D.
    Worden, K.
    Manson, G.
    Pierce, S. G.
    Structural Dynamics - EURODYN 2005, Vols 1-3, 2005, : 923 - 928
  • [46] Fuzzy regression with radial basis function network
    Cheng, CB
    Lee, ES
    FUZZY SETS AND SYSTEMS, 2001, 119 (02) : 291 - 301
  • [47] Fundamentals of artificial metaplasticity in radial basis function networks for breast cancer classification
    Vives-Boix, Victor
    Ruiz-Fernandez, Daniel
    NEURAL COMPUTING & APPLICATIONS, 2021, 33 (19): : 12869 - 12880
  • [48] Texture image classification using modular radial basis function neural networks
    Chang, Chuan-Yu
    Wang, Hung-Jen
    Fu, Shih-Yu
    JOURNAL OF ELECTRONIC IMAGING, 2010, 19 (01)
  • [49] Generalized sparse radial basis function networks for multi-classification problems
    Dai, Yunwei
    Wu, Qingbiao
    Zhang, Yuao
    APPLIED SOFT COMPUTING, 2024, 154
  • [50] Fundamentals of artificial metaplasticity in radial basis function networks for breast cancer classification
    Víctor Vives-Boix
    Daniel Ruiz-Fernández
    Neural Computing and Applications, 2021, 33 : 12869 - 12880
12345