人工智能大数据信用风险区集中化检测系统设计  

Design of artificial intelligence centralized detection system for big data credit risk area

作　　者：孙占锋 包空军 SUN Zhanfeng;BAO Kongjun(Zhengzhou University of Light Industry,Zhengzhou 450001,China)

机构地区：[1]郑州轻工业大学,河南郑州450001

出　　处：《现代电子技术》2021年第15期39-43,共5页Modern Electronics Technique

摘　　要：针对大数据环境抗入侵效果较差,应用系统信用风险较高的问题,提出了人工智能大数据信用风险区集中化检测系统设计。使用IEEE 1394型号数字采集卡,将信号以数字形式无损地采集到系统主机上,设置2路脉冲信号、72路开关信号,避免数字系统噪声现象发生。选择HART⁃HT2012型号数字传感器,可捕捉大数据中的信用风险信息。采用双线系统屏的RS 485接口,最多可实现32个节点联接,简化信号连接线。在人工智能技术支持下,设计系统软件部分,划分大数据信用风险区域,并通过规则库匹配确定大数据数据信用风险,将适应度函数作为数据读取前处理步骤,设计高低信用风险数据匹配规则,根据集中化检测流程完成系统设计。实验结果表明,该系统检测结果精准,具有快速检测性能。In view of the poor anti⁃intrusion effect of the big data environment and high credit risk of the application systems,the design of artificial intelligence centralized detection system for big data credit risk area is proposed.With the digital acquisition card IEEE 1394,the signals are collected and sent to the main computer of the system in digital form without damage.2⁃way pulse signals and 72⁃way switch signals are set to avoid the occurrence of the noise of the digital system.The digital sensor HART⁃HT2012 is selected to capture the credit risk information of big data.The interface RS 485 with the transmission mode of two⁃wire system screen is adopted to realize the connection of 32 nodes at maximum,which simplifies the signal connecting line.With the support of artificial intelligence technology,the system software is designed,the credit risk area of big data is divided,and the credit risk of big data is determined by rule base matching.The fitness function is taken as the pre⁃processing step of data reading to design the matching rules of high and low credit risk data.The system design is achieved according to the centralized detection process.The experimental results show that the system has accurate detection results and fast detection performance.

关 键 词：集中化检测 大数据信用风险 风险区域检测 人工智能 数据匹配 系统设计 

分 类 号：TN99-34[电子电信—信号与信息处理] TP311.13[电子电信—信息与通信工程]