Artificial intelligence in electrostatic risk management

被引：2

作者：

Gulyas, Attila ^{[1
]}

Kiss, Istvan ^{[1
]}

Berta, Istvan ^{[1
]}

机构：

[1] Budapest Univ Technol & Econ, Dept Power Engn, H-1111 Budapest, Hungary

来源：

JOURNAL OF ELECTROSTATICS | 2013年 / 71卷 / 03期

关键词：

Risk management; Hazard management; SCOUT system; Artificial intelligence; Support vector machines; NEURAL-NETWORKS; SYSTEM;

D O I：

10.1016/j.elstat.2012.12.010

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In the last two decades protection against electrostatic hazards became a very important topic. The increase in the range of possible faults fast automated systems and complex fault analysis is required. The tools of artificial intelligence and expert systems have been applied successfully on this field and this paper aims to take a step further. While giving some insight to the currently used tools, another Al method, the 'support vector machines' are introduced in this paper. Besides a brief review on SVMs they are introduced to the SCOUT system, a novel approach to electrostatic hazard management. (C) 2012 Elsevier B.V. All rights reserved.

引用

页码：387 / 391

页数：5

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