Allocation and application of computer software system based on system architecture

2021 ◽  
pp. 1-8
Author(s):  
Xiaolian Di
Keyword(s):  
Fourier Transform ◽  
Decision Tree ◽  
Software Development ◽  
Parallel Algorithm ◽  
Discrete Fourier Transform ◽  
Computer Software ◽  
Software System ◽  
Decision Tree Algorithm ◽  
Tree Algorithm ◽  
Computer Software System

 With the improvement of software system complexity and frequent updating of user requirements, the requirements of the information software development industry for information construction are constantly improved, and the quality and management requirements of software products researched and developed are also constantly improved. Project managers in the information software development industry gradually realize the importance and necessity of software system deployment. It requires scientific, timely, effective and clear work. Software system deployment system for task division and task monitoring. Based on the research results at home and abroad, this paper studies the deployment of computer software system based on event-driven architecture by using a discrete Fourier transform algorithm, decision tree algorithm and parallel algorithm. By comparing and optimizing the advantages and disadvantages of discrete Fourier transform algorithm, decision tree algorithm and parallel algorithm. This paper studies the unified management, scheduling and allocation of computer software resources. The results show that after using the research model, the data error is controlled within 5%, and the overall data accuracy is improved by 15% compared with the previous methods, which have certain practical value.

scholarly journals Classification of diabetes disease using decision tree algorithm (C4.5)

2021 ◽  
Vol 1869 (1) ◽  
pp. 012082
Author(s):  
B A C Permana ◽  
R Ahmad ◽  
H Bahtiar ◽  
A Sudianto ◽  
I Gunawan
Keyword(s):  
Decision Tree ◽  
Decision Tree Algorithm ◽  
Tree Algorithm

An Analysis of Factors Influencing Foreign Language Self-Efficacy Based on C5.0 Decision Tree Algorithm in Data Mining

2014 ◽  
Vol 538 ◽  
pp. 460-464
Author(s):  
Xue Li
Keyword(s):  
Data Mining ◽  
Decision Tree ◽  
Foreign Language ◽  
Language Learning ◽  
Learning Strategies ◽  
Self Efficacy ◽  
Foreign Language Learning ◽  
Decision Tree Algorithm ◽  
Tree Algorithm ◽  
C5.0 Decision Tree

Based on inter-correlation and permeability among disciplines, the author makes an attempt to apply the information science to cognitive linguistics to provide a new perspective for the study of foreign languages. The correlation between self-efficacy and such four factors as anxiety, learning strategies, motivation and learners’ past achievement is analyzed by means of data mining and the extent to which the above factors affect self-efficacy in language learning is explored in this paper. The paper employs the decision tree algorithm in SPSS Clementine. C5.0 decision tree algorithm is adopted to analyze data in the study. The results are elicited from the researches carried out in this paper. The increased anxiety is bound to weaken learners’ motivation over time. It is obvious that learners have low self-efficacy. It is very important to employ strategies in foreign language learning. Ignorance of using learning strategies may result in unplanned learning with unsatisfactory achievements in spite of more efforts involved. Self-efficacy in foreign language learning may be weakened accordingly. Learners’ past achievement is a reference dimension in measuring self-efficacy with weaker influence.

Research on Asset Recognition Algorithm of Information Security Product Based on Decision Tree Algorithm

2013 ◽  
Vol 397-400 ◽  
pp. 2296-2300 ◽  
Author(s):  
Fei Shuai ◽  
Jun Quan Li
Keyword(s):  
Computational Complexity ◽  
Information Security ◽  
Decision Tree ◽  
Recognition Algorithm ◽  
Space Complexity ◽  
Complex Relationship ◽  
Decision Tree Algorithm ◽  
Tree Algorithm ◽  
C4.5 Algorithm ◽  
C4.5 Decision Tree

In current, there are complex relationship between the assets of information security product. According to this characteristic, we propose a new asset recognition algorithm (ART) on the improvement of the C4.5 decision tree algorithm, and analyze the computational complexity and space complexity of the proposed algorithm. Finally, we demonstrate that our algorithm is more precise than C4.5 algorithm in asset recognition by an application example whose result verifies the availability of our algorithm.Keywordsdecision tree, information security product, asset recognition, C4.5

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