...
首页> 外文期刊>Journal of Economics and Sustainable Development >Fraud Detection in Telecommunications Industry: Bridging the Gap with Random Rough Subspace Based Neural Network Ensemble Method
【24h】

Fraud Detection in Telecommunications Industry: Bridging the Gap with Random Rough Subspace Based Neural Network Ensemble Method

机译:电信行业的欺诈检测:基于随机粗糙子空间的神经网络集成方法弥合差距

获取原文
           

摘要

Fraud has been very common in the society and it affects private enterprises as well as public entities. Telecommunication companies worldwide suffer from customers who use the provided services without paying. There are also different types of telecommunication fraud such as subscription fraud, clip on fraud, call forwarding, cloning fraud, roaming fraud and calling card fraud. Thus, detection and prevention of these frauds are the main targets of the telecommunication industry. This paper addresses the various techniques of detecting fraud, giving the limitations of each technique and proposes random rough subspace-based neural network ensemble method for effective fraud detection. Keywords: Fraud, Fraud detection, Random rough subspace, Neural network, Telecommunications
机译:欺诈在社会中非常普遍,它影响到私营企业和公共实体。全世界的电信公司都遭受了客户使用提供的服务而无需付费的痛苦。还有其他类型的电信欺诈,例如订阅欺诈,剪辑欺诈,呼叫转移,克隆欺诈,漫游欺诈和电话卡欺诈。因此,检测和防止这些欺诈是电信行业的主要目标。本文介绍了各种检测欺诈的技术,并给出了每种技术的局限性,并提出了基于随机粗子空间的神经网络集成方法,以进行有效的欺诈检测。关键字:欺诈,欺诈检测,随机粗糙子空间,神经网络,电信

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号