Home| Contact Us| New Journals| Browse Journals| Journal Prices| For Authors|

Print ISSN:
Online ISSN:


  About PCA
  DLINE Portal Home
Home
Aims & Scope
Editorial Board
Current Issue
Next Issue
Previous Issue
Sample Issue
Upcoming Conferences
Self-archiving policy
Alert Services
Be a Reviewer
Publisher
Paper Submission
Subscription
Contact us
 
  How To Order
  Order Online
Price Information
Request for Complimentary
Print Copy
 
  For Authors
  Guidelines for Contributors
Online Submission
Call for Papers
Author Rights
 
 
RELATED JOURNALS
Journal of Digital Information Management (JDIM)
Journal of Multimedia Processing and Technologies (JMPT)
International Journal of Web Application (IJWA)

 

 
Progress in Computing Applications(PCA)
 

Optimization of Resource Allocation Based on Sports Information Industry Management
Xu Suzhou
Guangxi Vocational and Technical College of Transportation Nanning, Guangxi, 530000 China
Abstract: The sports information industry is one of the rapidly developing industries in recent years, and it faces many challenges and problems in its development process. Among them, the rational allocation of resources is one of the important issues in managing the sports information industry. How to reasonably allocate resources and improve the management level and efficiency of the sector is an urgent problem to be solved in the current sports information industry. This article studies optimizing resource allocation based on sports information industry management. Through research on the management of the sports information industry, a resource-based optimization method for resource allocation has been proposed, aiming to improve the management level and efficiency of the sports information industry.
Keywords: Data Mining Algorithm, Sports Information Industry,Optimization Design Optimization of Resource Allocation Based on Sports Information Industry Management
DOI:https://doi.org/10.6025/pca/2023/12/2/27-34
Full_Text   PDF 1.18 MB   Download:   52  times
References:

[1] Liu, M., Qu, M., Zhao, B. (2016). Research and Citation Analysis of Data Mining Technology Based on Bayes Algorithm. Mobile Networks and Applications, 22(3), 1-9.
[2] Wang, G. J., Jin, S. G. (2015). Design and Development of Intelligent Logistics System Based on Data Mining and Association Rules Technology. Advanced Materials Research, 1078, 392-396.
[3] Zeng, Y., Zhang, Z.,and Kusiak, A. (2015). Predictive modeling and optimization of a multi-zone HVAC system with data mining and firefly algorithms. Energy, 86, 393-402.
[4] Hailong, S., and Fangsong, L. (2017). Research on algorithm of vehicle track data mining based on cloud computing. Agro Food Industry Hi Tech, 28(1), 1439-1443.
[5] Jha, R., Pettersson, F., Dulikravich, G. S., et al. (2015). Evolutionary Design of Nickel-Based Superalloys Using Data-Driven Genetic Algorithms and Related Strategies. Materials & Manufacturing Processes, 30(4), 488-510.
[6] Zheng, G. J., Zhang, J. W., Hu, P., et al. (2015). Optimization of hot forming process using data mining techniques and finite element method. International Journal of Automotive Technology, 16(2), 329-337.
[7] Habib u R. M., Liew, C. S., Wah, T. Y., et al. (2015). Mining personal data using smartphones and wearable devices: a survey. Sensors, 15(2), 4430.
[8] Kim, J. C., Jin, S. A., Park, Y. H., et al. (2015). Information Visualization for the Manufacturing Process Optimization Based on Design of Experiment and Data Analysis. 4(9), 393-402.
[9] Li, Y., Thomas, M. A., and Osei-Bryson, K. M. (2016). Ontology-based data mining model management for self-service knowledge discovery. Information Systems Frontiers, 19, 1-19.
[10] Liu, L., Lv, J., Ma, Z., et al. (2015). Toward the Association Rules of Meteorological Data Mining Based on Cloud Computing. Future Generation Computer Systems, 334, 1051-1059.


Home | Aim & Scope | Editorial Board | Author Guidelines | Publisher | Subscription | Previous Issue | Contact Us |Upcoming Conferences|Sample Issues|Library Recommendation Form|

 

Copyright © 2011 dline.info