Balanced scheduling method of ideological and political teaching resources based on cluster analysis algorithm

In order to overcome the problems of poor scheduling accuracy, low recall rate and long scheduling time in the traditional scheduling method of ideological and political resources, the paper proposes a balanced scheduling method of resources based on clustering analysis algorithm.First, the load time series of the teaching resource server is determined and pre-processed.Secondly, cluster analysis is used to classify the data.Finally, according to the classification results, the balanced scheduling function of resources is constructed, and the particle swarm optimisation algorithm is used to solve the scheduling function to obtain the final scheduling strategy.The results show that the scheduling accuracy of the proposed method is 99.12%, the recall rate is up to 95%, the scheduling time is controlled within 7 s, and the resource balance scheduling effect is good.

Authors

Publication Details

Journal
International Journal of Reasoning-based Intelligent Systems
Published
2025-01-01
DOI
https://doi.org/10.1504/ijris.2025.145056
Citations
1
Primary Topic
Ideological and Political Education
Type
article
Field-Weighted Citation Impact
8.93
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Balanced scheduling method of ideological and political teaching resources based on cluster analysis algorithm

Wenbin Liu
1 citations
International Journal of Reasoning-based Intelligent Systems
Ideological and Political Education
8.93
article

Balanced scheduling method of ideological and political teaching resources based on cluster analysis algorithm

Wenbin Liu
article en
1 citations

Abstract

In order to overcome the problems of poor scheduling accuracy, low recall rate and long scheduling time in the traditional scheduling method of ideological and political resources, the paper proposes a balanced scheduling method of resources based on clustering analysis algorithm.First, the load time series of the teaching resource server is determined and pre-processed.Secondly, cluster analysis is used to classify the data.Finally, according to the classification results, the balanced scheduling function of resources is constructed, and the particle swarm optimisation algorithm is used to solve the scheduling function to obtain the final scheduling strategy.The results show that the scheduling accuracy of the proposed method is 99.12%, the recall rate is up to 95%, the scheduling time is controlled within 7 s, and the resource balance scheduling effect is good.

International Journal of Reasoning-based Intelligent SystemsVol. 17(1)
Openalex Percentile: Top 5%
Ideological and Political Education
8.93
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Balanced scheduling method of ideological and political teaching resources based on cluster analysis algorithm — Wenbin Liu · International Journal of Reasoning-based Intelligent Systems (2025) | TGRS Research Map | TGRS