Research on the identification of network traffic anomalies in the access layer of power IoT based on extreme learning machine-Reference-Cited by-同舟云学术

Research on the identification of network traffic anomalies in the access layer of power IoT based on extreme learning machine

Published:2022-08 Issue: Volume: Page:
ISSN:
Container-title:2022 International Conference on Artificial Intelligence, Information Processing and Cloud Computing (AIIPCC)
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Author:

Zhong Baoqiang¹,Tan Yikai¹,Wang Wei²,Cui Weihong¹,Cai Zehan¹,Wei Lai¹,He Qian²

Affiliation:

1. China Southern Power Grid Peak shaving and Frequency Modulation Power Generation Co., Ltd,Guangzhou,Guangdong,China

2. Information Communication Branch of China Southern Power Grid Peak shaving and Frequency Modulation Power Generation Co., Ltd,Guangzhou,Guangdong,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10070113/10069879/10070281.pdf?arnumber=10070281

Reference14 articles.

1. Reduce Training Error of Extreme Learning Machine by Selecting Appropriate Hidden Layer Output Matrix

2. Prediction Model of Magnetorheological (MR) Fluid Damper Hysteresis Loop using Extreme Learning Machine Algorithm

3. A Timeliness-Enhanced Traffic Identification Method in Airborne Network

4. Progressive researches on IoT security: An exhaustive analysis from the perspective of protocols, vulnerabilities, and preemptive architectonics

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