Design of an auto-associative neural network by using design of experiments approach

被引：0

作者：

Bratina, Bozidar ^{[1
]}

Muskinja, Nenad ^{[1
]}

Tovornik, Boris ^{[1
]}

机构：

[1] Univ Maribor, Fac Elect Engn & Comp Sci, SLO-2000 Maribor, Slovenia

来源：

KNOWLEDGE - BASED INTELLIGENT INFORMATION AND ENGINEERING SYSTEMS, PT 1, PROCEEDINGS | 2008年 / 5177卷

关键词：

fault detection and isolation; nonlinear principle components; neural networks; design of experiments;

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：

Data driven Computational intelligence methods have become popular in Fault detection and isolation (FDI) due to relatively quick design and not so difficult implementation on real systems. In this paper a research work on a Taguchi DoE approach for training the auto-associative neural network to extract non-linear principal components of a system, is presented. Design of such network was first proposed by Kramer however for achieving robustness to unspecified parameters such as noise level and disturbances, a design of experiments methodology can be used to optimally define network structure and parameters.

引用

页码：25 / 32

页数：8

共 50 条

[1] Design of an auto-associative neural network by using design of experiments approach
Božidar Bratina
Nenad Muškinja
Boris Tovornik
Neural Computing and Applications, 2010, 19 : 207 - 218
[2] Design of an auto-associative neural network by using design of experiments approach
Bratina, Bozidar
Muskinja, Nenad
Tovornik, Boris
NEURAL COMPUTING & APPLICATIONS, 2010, 19 (02): : 207 - 218
[3] Design of an auto-associative neural network for fault detection and isolation by using design of experiments methodology
Bratina, Bozidar
Tovornik, Boris
ECT - 2008: PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON ELECTRICAL AND CONTROL TECHNOLOGIES, 2008, : 57 - 61
[4] Auto-Associative Nanoelectronic Neural Network
Nogueira, C. P. S. M.
Guimaraes, J. G.
7TH INTERNATIONAL CONFERENCE ON LOW DIMENSIONAL STRUCTURES AND DEVICES (LDSD 2011), 2014, 1598 : 229 - 232
[5] An auto-associative neural network for information retrieval
Desjardins, Guy
Proulx, Robert
Godin, Robert
2006 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORK PROCEEDINGS, VOLS 1-10, 2006, : 3492 - 3498
[6] Accurate Arrhythmia Classification using Auto-Associative Neural Network
Chakroborty, Sandipan
2013 35TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 2013, : 4247 - 4250
[7] Study on the application of auto-associative neural network
Wang, PJ
Cox, C
PROCEEDINGS OF THE 2004 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7, 2004, : 3291 - 3295
[8] Auto-associative neural network system for recognition
Zeng, Xian-Hua
Luo, Si-Wei
Wang, Jiao
PROCEEDINGS OF 2007 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7, 2007, : 2885 - 2890
[9] Study on the application of auto-associative neural network
Wang, PJ
Cox, C
2004 7TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS, VOLS 1-3, 2004, : 1570 - 1573
[10] Towards circuit design with auto-associative memories
Deh, Kofi
Prasad, Sheila
Markovic, Vera
TELSIKS 2007: 8TH INTERNATIONAL CONFERENCE ON TELECOMMUNICATIONS IN MODERN SATELLITE, CABLE AND BROADCASTING SERVICES, VOLS 1 AND 2, 2007, : 271 - +

← 1 2 3 4 5 →