Improving Multiple Time Series Forecasting with Data Stream Mining Algorithms

2020 ◽  
Author(s):  
Marcos Alberto Mochinski ◽  
Jean Paul Barddal ◽  
Fabricio Enembreck
Keyword(s):  
Time Series ◽  
Data Stream ◽  
Time Series Forecasting ◽  
Data Stream Mining ◽  
Multiple Time ◽  
Multiple Time Series ◽  
Stream Mining ◽  
Mining Algorithms

Research on the Mining Technology of Multimedia Communication Data Flow Based on Computer Network

2013 ◽  
Vol 380-384 ◽  
pp. 3570-3574
Author(s):  
Yong Hong Cheng ◽  
Li Hua Ouyang ◽  
Xin Yan Liu
Keyword(s):  
Data Stream ◽  
High Speed ◽  
Data Flow ◽  
Computer Network ◽  
Multimedia Communication ◽  
Data Stream Mining ◽  
Stream Mining ◽  
Mining Technology ◽  
Daily Work ◽  
Mining Algorithms

computer network multimedia communication has spread all over daily work and life fields, people also have put forward higher requirements for computer multimedia communication network. Based on current network multimedia communication, there are a large amount of data transmission, high-speed and dynamic characteristics, the mining technology of its communication data flow is carried out related to research. In this paper, the frequent item sets of data stream mining technology is carried out related to research, and the classical HCOUNT algorithm is carried out relevant analysis, according to the relevant analysis, the classical HCOUNT algorithm is improved, in order to alleviate possible error problem in data mining. Finally, the data stream mining algorithms are carried out relevant analysis of actual experimental data. Study on the technical aspects of the data flow mining in computer network multimedia communication, it is an important role in the development of the computer network multimedia communication. Study on the improvement of the current algorithm, it provides reference in the similar field of algorithm research

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