Integration and Optimization of Multimedia Technology in Art and Painting Education under Big Data

With the continuous changes in art and painting teaching problems, the commonly used methods can no longer solve the problem very well. At this time, we use multimedia technology to study them in the context of big data. The experiments show that: (1) Multimedia technology can be well integrated into the teaching of art and painting; the rapport rate between them reached 92%. The problem that the system would sometimes become unstable was solved through the optimization algorithm, and finally, the overall score of the model was obtained through the evaluation algorithm to be floating between 88–94 points. (2) According to the data of the figures and tables, it can be concluded that due to the integration of multimedia technology into the teaching of art and painting, my country is paying more and more attention to it anyway, and the amount invested is also increasing, which has changed from the original 2.5 billion to 4 billion yuan. In the future, the training of art and painting teaching talents will be 123 million yuan in 2020–222 million yuan in 2024, and the proportion of my country’s art and painting transactions will basically account for 50%. Finally, the teaching of art and painting in our country will become better and better.

Authors

Institutions

Publication Details

Journal
Journal of Circuits Systems and Computers
Published
2025-10-04
DOI
https://doi.org/10.1142/s0218126626500027
Primary Topic
Digital Media and Visual Art
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Integration and Optimization of Multimedia Technology in Art and Painting Education under Big Data

Yuli He, Shiqi Zhou
Journal of Circuits Systems and Computers
Digital Media and Visual Art
article

Integration and Optimization of Multimedia Technology in Art and Painting Education under Big Data

Yuli He, Shiqi Zhou
article en

Abstract

With the continuous changes in art and painting teaching problems, the commonly used methods can no longer solve the problem very well. At this time, we use multimedia technology to study them in the context of big data. The experiments show that: (1) Multimedia technology can be well integrated into the teaching of art and painting; the rapport rate between them reached 92%. The problem that the system would sometimes become unstable was solved through the optimization algorithm, and finally, the overall score of the model was obtained through the evaluation algorithm to be floating between 88–94 points. (2) According to the data of the figures and tables, it can be concluded that due to the integration of multimedia technology into the teaching of art and painting, my country is paying more and more attention to it anyway, and the amount invested is also increasing, which has changed from the original 2.5 billion to 4 billion yuan. In the future, the training of art and painting teaching talents will be 123 million yuan in 2020–222 million yuan in 2024, and the proportion of my country’s art and painting transactions will basically account for 50%. Finally, the teaching of art and painting in our country will become better and better.

Journal of Circuits Systems and ComputersVol. 35(08)
Fujian Jiangxia University (CN), Education Department of Fujian Province (CN), Fuzhou University (CN)
Openalex Percentile: Top 52%
Digital Media and Visual Art
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.

Integration and Optimization of Multimedia Technology in Art and Painting Education under Big Data — Yuli He, Shiqi Zhou · Journal of Circuits Systems and Computers (2025) | TGRS Research Map | TGRS