Specifications

of a 1.5 MW DFIG was designed by applying above fuzzy optimization method, and a series of
simulations were conducted in the Matlab/Simulink platform. The simulation results show that
the current of the rotor, oscillation of the bus voltage and the electromagnetic torque oscilation
can be reduced by the crowbar resistance optimization, meanwhile, the operation reliability of
DFIG sets can be effectively improved. © 2012 Chin. Soc. for Elec. Eng.
Number of references: 20
Main heading: Rotors (windings)
Controlled terms: Electric fault currents - Fuzzy sets - Membership functions -
Optimization - Site selection
Uncontrolled terms: Bus voltage - Constraint boundaries - Doubly fed induction
generators - Doubly fed induction-generator - Electromagnetic torques - Fuzzy
objective function - Fuzzy optimization - Fuzzy optimization theory - Low-voltage -
Low-voltage ride-through - MATLAB /simulink - Operation reliability - Power grids -
Ride-through - Rotor current - Short-circuit fault - System security
Classification code: 402 Buildings and Towers - 403 Urban and Regional Planning and
Development - 704.1 Electric Components - 706.2 Electric Power Lines and Equipment -
921 Mathematics - 921.5 Optimization Techniques
Database: Compendex
Compilation and indexing terms, © 2013 Elsevier Inc.
3.
Accession number: 20130315910818
Title: An application of machine learning on the network security model
Authors: Wang, Hai-Chen1 ; Zhao, Xiang-Mo1 ; Wang, Hai-Sheng2/;;;
Author affiliation:
1 School of Information Engineering, Chang'an University, Nan Er Huan Zhong Duan, Xi'an
710064, China
2 Department of Computer Science and Technology, Xi'an University of Technology, No. 5,
South Jinhua Road, Xi'an 710048, China
Corresponding author: Wang, H.-C. ([e-mail])
Source title: ICIC Express Letters
Abbreviated source title: ICIC Express Lett.
Volume: 7
Issue: 2
Issue date: 2013
Publication year: 2013
Pages: 291-296
Language: English
ISSN: 1881803X
Document type: Journal article (JA)
Publisher: ICIC Express Letters Office, Tokai University, Kumamoto Campus, 9-1-1,
Toroku, Kumamoto, 862-8652, Japan
Abstract: Rough set classifier or SVM (Support Vector Machine) classifier is a typical
machine learning model. Through inductive reasoning Rough set classifier is going to learn the
general rule. The two classifiers are used to classify nodes into trust nodes, strange nodes and