DATA INFORMATION SECURITY OF COMMUNICATION NETWORK BASED ON EDGE COMPUTING TECHNOLOGY AND BP NEURAL NETWORK

2019 ◽  
Vol 78 (20) ◽  
pp. 1837-1845
Author(s):  
Xi. Liu
Keyword(s):  
Neural Network ◽  
Communication Network ◽  
Information Security ◽  
Bp Neural Network ◽  
Edge Computing ◽  
Computing Technology

Smith Predictor Based on Predicting Induced-Delay

2011 ◽  
Vol 201-203 ◽  
pp. 2003-2006
Author(s):  
Shu De Li ◽  
Yi Chen ◽  
Cai Xia Liu
Keyword(s):  
Neural Network ◽  
Communication Network ◽  
Control System ◽  
Bp Neural Network ◽  
Networked Control System ◽  
Smith Predictor ◽  
Networked Control ◽  
Object Model ◽  
Random Delay

Since communication network is introduced into control system, induced-delay appears. Because of the delay, the performance of networked control system becomes bad, even unsteady. Conventional Smith predictor is sensitive to error in object model and needs delay’s value in advance. Regarding random delay, its application is limited. In this paper, we propose a method based on induced-delay predicted by BP neural network, which use two historical delay values to predict the next one. Smith predictor adjusts its parameters according to that value in time. The simulating results indicate that the precision of delay-predicting can be ensured and the performance of networked control system has been improved.

A novel heuristic approach for sustainable social and economic development based on green computing technology and big data

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Xiaoman Wu ◽  
Jun Liu ◽  
Yulian Peng
Keyword(s):  
Neural Network ◽  
Economic Development ◽  
Network Model ◽  
Neural Network Model ◽  
Bp Neural Network ◽  
Green Computing ◽  
Computing Technology ◽  
Content Type ◽  
Social And Economic Development ◽  
Bp Neural Network Model

PurposeWithout damaging and consuming natural resources, green computing technology can meet the needs of society for a long time. This paper discusses how to realize the sustainable development of social economy through the innovation of green computing technology.Design/methodology/approachFor the green computing technology and sustainable social and economic development problems, it builds back propagation (BP) neural network model and analyzes the topological structure of the network model as well as the impact of the training errors allowed by the network on its performance.FindingsBy optimizing the number of input nodes, the number of hidden nodes and the target value, the genetic algorithm (GA) can get the optimal neural network model. The simulation experiment proves that the proposed model is effective.Originality/valueIt can not only reduce the possibility of falling into local optimum, but also optimize the initial weights and thresholds of BP neural network and further improve the stability and test effect of BP neural network model.

scholarly journals Risk Assessment of Power Communication Network Based on LM-BP Neural Network

2019 ◽  
Vol 1187 (2) ◽  
pp. 022063
Author(s):  
Yanan Wang ◽  
Ke Wang ◽  
Ran Zhang ◽  
Qiao Xue ◽  
Xiangzhou Chen ◽  
...  
Keyword(s):  
Neural Network ◽  
Risk Assessment ◽  
Communication Network ◽  
Bp Neural Network
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