scholarly journals A Novel RNN-GBRBM Based Feature Decoder for Anomaly Detection Technology in Industrial Control Network

2017 ◽  
Vol E100.D (8) ◽  
pp. 1780-1789 ◽  
Author(s):  
Hua ZHANG ◽  
Shixiang ZHU ◽  
Xiao MA ◽  
Jun ZHAO ◽  
Zeng SHOU
Author(s):  
Yanli Feng ◽  
Gongliang Sun ◽  
Zhiyao Liu ◽  
Chenrui Wu ◽  
Xiaoyang Zhu ◽  
...  

2014 ◽  
Vol 644-650 ◽  
pp. 828-831
Author(s):  
Wen Lai Liu

In the operation process of large industrial control network, with conventional fuzzy PID control algorithm for industrial control networks energy-saving control, excessive industrial networks will aggravate machine wear of the single network, thereby reduce the effect of energy-saving for industrial network. This paper presents an approach for industrial network energy-saving control based on non-uniform data production rate. According to the relationship between the network load and loss, the loss model of industrial control network can be established. Adaptive linear genetic method is utilized to control industrial control network energy-saving load, so as to achieve energy-saving control of industrial control network. Experimental results show that the algorithm can effectively improve the energy-saving efficiency of industrial control network, and achieve satisfactory results.


2021 ◽  
Vol 132 ◽  
pp. 103509
Author(s):  
Truong Thu Huong ◽  
Ta Phuong Bac ◽  
Dao Minh Long ◽  
Tran Duc Luong ◽  
Nguyen Minh Dan ◽  
...  

2018 ◽  
Vol 51 (7-8) ◽  
pp. 360-367
Author(s):  
Geng Liang ◽  
Wen Li

Traditionally, routers and other network devices encompass both data and control functions in most large enterprise networks, making it difficult to adjust the network infrastructure and operation to large-scale addition of end systems, virtual machines, and virtual networks in industrial comprehensive automation. A network organizing technique that has come to recent prominence is the Software-Defined Network (SDN). A novel SDN based industrial control network (SDNICN) was proposed in this paper. Intelligent network components are included in a SDNICN. Switches in SDNICN provided fundamental network interconnection for the whole industrial control network. Network controller is used for data transmission, forwarding and routing control between different layers. Service Management Center (SMC) is essentially responsible for managing various services used in industrial process control. SDNICN can not only greatly improve the flexibility and performance of industrial control network but also meet the intelligence and informatization of the future industry.


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