RBF neural network implementation of fuzzy systems: Application to time series modeling

被引：0

作者：

Marcek, Milan ^{[1
,2
]}

Marcek, Dusan ^{[1
,3
]}

机构：

[1] Silesian Univ, Fac Philosophy & Sci, CZ-74601 Prague, Czech Republic

[2] MEDIS Nitra Ltd, Nitra 94901, Slovakia

[3] Univ Zilina, Fac Management Sci & Informat, Zilina 01026, Slovakia

来源：

ROUGH SETS, FUZZY SETS, DATA MINING AND GRANULAR COMPUTING, PROCEEDINGS | 2007年 / 4482卷

关键词：

probabilistic time-series models; fuzzy system; classic and soft RBF network; cloud models; granular computing;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

At first, we discuss the basic structure of the fuzzy system as a simple yet powerful fuzzy modeling technique. Neural networks and fuzzy logic models are based on very similar underlying mathematics. The similarity between RBF networks and fuzzy models is noted in detail. Then, we propose the extension of RBF neural networks by the cloud model. Time series approximation and prediction by applying RBF neural networks or fuzzy models and comparisons between the various types of RBF networks and statistical models are discussed at length.

引用

页码：500 / +

页数：2

共 50 条

[21] A Novel Grey RBF Neural Network Modeling Method and Its Application
Fan, Chunling
Gao, Feng
Cao, Menglong
Cui, Fengying
[J]. ICNC 2008: FOURTH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, VOL 3, PROCEEDINGS, 2008, : 421 - 425
[22] The application of neural networks to forecast fuzzy time series
Huarng, K
Yu, THK
[J]. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2006, 363 (02) : 481 - 491
[23] The Application of Fuzzy PI and RBF Neural Network Tuning PID in Servo System
Li, Guozhi
Ren, Xiaohong
Ren, Bing
Qiu, Ling
[J]. PROCEEDINGS OF 2013 CHINESE INTELLIGENT AUTOMATION CONFERENCE: INTELLIGENT AUTOMATION, 2013, 254 : 711 - 719
[24] Application of RBF Neural Network in WEDM
Zhang, ShiPing
Ding, YiChao
Wang, Jing
Li, Yuanhui
[J]. AUTOMATION EQUIPMENT AND SYSTEMS, PTS 1-4, 2012, 468-471 : 607 - 612
[25] Application of RBF Neural Network on Bidding
Yang Huiyun
Jiang Ying
Wang Lihai
[J]. PROCEEDINGS OF 2008 INTERNATIONAL CONFERENCE ON CONSTRUCTION & REAL ESTATE MANAGEMENT, VOLS 1 AND 2, 2008, : 47 - 50
[26] A method for predicting nonlinear time series using RBF (Radial Base Function) neural network and its application
Zhang, C.-B.
Deng, Z.-L.
[J]. 2001, Harbin Research Institute (16):
[27] A Modified K-means Algorithm based RBF Neural Network and Its Application in Time Series Modelling
Jiao, Yiping
Shen, Yu
Fei, Shumin
[J]. 14TH INTERNATIONAL SYMPOSIUM ON DISTRIBUTED COMPUTING AND APPLICATIONS FOR BUSINESS, ENGINEERING AND SCIENCE (DCABES 2015), 2015, : 481 - 484
[28] Modeling of Fuzzy Systems Based on the Competitive Neural Network
Barraza, Juan
Melin, Patricia
Valdez, Fevrier
Gonzalez, Claudia I.
Huang, Hong-Zhong
[J]. APPLIED SCIENCES-BASEL, 2023, 13 (24):
[29] Chaotic time series forecasting with PSO-trained RBF neural network
Feng, Bin
Chen, Wei
Sun, Jun
[J]. DCABES 2006 PROCEEDINGS, VOLS 1 AND 2, 2006, : 787 - 790
[30] Safety Evaluation of Microgrid Using Chaotic Time Series and RBF Neural Network
Qin, He
Tang, Wenbo
[J]. 2020 6TH INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING, CONTROL AND ROBOTICS (EECR 2020), 2020, 853

← 1 2 3 4 5 →