Data Scheduling Algorithm of Mobile Education Streaming Media Based on Improved Random Forest

• Published in: 2024 Asia-Pacific Conference on Software Engineering, Social Network Analysis and Intelligent Computing (SSAIC) pp. 78 - 82
• Main Author: Wu, Xiaoming
• Format: Conference Proceeding
• Language: English
• Published: IEEE 10.01.2024
• Subjects: Accuracy; Economics; Education; Improved random forest algorithm; Mobile education; Prediction algorithms; Scheduling algorithms; Software algorithms; Streaming media; Streaming media data scheduling
• DOI: 10.1109/SSAIC61213.2024.00021

With the rapid development of the Internet, the traditional media market has been integrated with the computer network, resulting in many new applications such as online video on demand, distance education, network television and so on. Streaming media is a technology that can play audio, video and other multimedia files on the Internet in real time without downloading and waiting. This paper builds a streaming media data scheduling model based on the improved random forest algorithm. First, it analyzes some indicators that affect the data flow, and then analyzes the accuracy of the improved random algorithm and its traditional algorithm under different decision tree numbers according to the improved forest algorithm. The gmean value of an improved random forest algorithm proposed in this paper is significantly higher than that of the traditional algorithm, and the fvalue is close to 0.92. It shows that the prediction accuracy of default and non-default samples is improved by this algorithm. It can improve the economic benefit and promote the establishment of an economical, smooth and efficient streaming media communication transmission system.