scholarly journals Network Public Opinion Prediction and Control Based on Edge Computing and Artificial Intelligence New Paradigm

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Ying Zhu
Keyword(s):  
Time Series ◽  
Public Opinion ◽  
Chaotic Time Series ◽  
Edge Computing ◽  
Factor Graph ◽  
New Paradigm ◽  
Placement Problem ◽  
Index Method ◽  
Service Placement ◽  
Network Public Opinion

In this paper, an adaptive edge service placement mechanism based on online learning and a predictive edge service migration method based on factor graph model are proposed to solve the edge computing service placement problem from the edge computing dimension. First, the time series of the development of online chaotic public opinion is a platform for vectorized collection of keyword index trends using the theory of chaotic phase space reconstruction. Secondly, it is necessary to use the main index method to judge whether the time series has the chaotic characteristics of the network public opinion data. The simulation results show that network public opinion is the development characteristic of chaotic time series. Finally, the prediction model is improved by using complex network topology. Through the simulation experiment of network public opinion and chaotic time series, the results show that the improved model has the advantages of accuracy, rapidity, and self-adaptability and can be applied to other fields.

scholarly journals Emotional characteristics and time series analysis of Internet public opinion participants based on emotional feature words

2020 ◽  
Vol 17 (1) ◽  
pp. 172988142090421 ◽  
Author(s):  
Fengzhen Jia ◽  
Chun-Chun Chen
Keyword(s):  
Time Series ◽  
Public Opinion ◽  
Rapid Development ◽  
Practical Application ◽  
Analysis Model ◽  
Evolution Analysis ◽  
Proposed Model ◽  
Tendency Analysis ◽  
Emotional Lexicon ◽  
Network Public Opinion

In recent years, with the rapid development and wide application of the Internet, it has become the main place for the generation and dissemination of public opinion. To grasp the information of network public opinion in a timely and comprehensive way can not only effectively prevent sudden network malignant events but also provide a reference for the scientific and democratic decision-making of government departments. Therefore, in view of the practical application needs, this article studies the emotional characteristics and the evolution of public opinion over time based on the emotional feature words of network public opinion participants. Firstly, the positive and negative emotional lexicon of HowNet emotional dictionary is used, and the commonly used emotional lexicon and expression symbols are added to the lexicon. At the same time, the polarity annotation method of Chinese emotional lexicon ontology is used to construct the emotional lexicon of this article. Secondly, considering other emotional polarity characteristics in the dictionary, an emotional tendency analysis model is proposed. In this article, emotional analysis is applied to the evolution analysis of network public opinion, and the change of network public opinion characteristics with time series is obtained. The simulation results show that the emotional dictionary constructed in this article and the proposed model of emotional orientation analysis can effectively analyze the emotional characteristics of network public opinion participants and apply emotional analysis to the evolution analysis of network public opinion, which can get the change of emotional characteristics of public opinion participants with time series.

scholarly journals An Overview of Service Placement Problem in Fog and Edge Computing

2020 ◽  
Vol 53 (3) ◽  
pp. 1-35 ◽  
Author(s):  
Farah Aït Salaht ◽  
Frédéric Desprez ◽  
Adrien Lebre
Keyword(s):  
Edge Computing ◽  
Placement Problem ◽  
Service Placement

Dynamic Service Placement and Load Distribution in Edge Computing

2020 ◽  
Author(s):  
Adyson Magalhaes Maia ◽  
Yacine Ghamri-Doudane ◽  
Dario Vieira ◽  
Miguel Franklin de Castro
Keyword(s):  
Load Distribution ◽  
Edge Computing ◽  
Service Placement

The Lyapunov Exponent Variance of an Electronic Manufacturing Enterprise’s Daily Qualified Rate Time Series by Improved Small Data Sets Approach

2012 ◽  
Vol 197 ◽  
pp. 271-277
Author(s):  
Zhu Ping Gong
Keyword(s):  
Time Series ◽  
Lyapunov Exponent ◽  
Chaotic Time Series ◽  
Quality System ◽  
Quality Level ◽  
Largest Lyapunov Exponent ◽  
Small Data ◽  
Data Set ◽  
Electronic Manufacturing ◽  
Small Data Set

Small data set approach is used for the estimation of Largest Lyapunov Exponent (LLE). Primarily, the mean period drawback of Small data set was corrected. On this base, the LLEs of daily qualified rate time series of HZ, an electronic manufacturing enterprise, were estimated and all positive LLEs were taken which indicate that this time series is a chaotic time series and the corresponding produce process is a chaotic process. The variance of the LLEs revealed the struggle between the divergence nature of quality system and quality control effort. LLEs showed sharp increase in getting worse quality level coincide with the company shutdown. HZ’s daily qualified rate, a chaotic time series, shows us the predictable nature of quality system in a short-run.

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