Design and Application of Web-based Education Management System using Split and Kernel based Residual Network

A web based education management system is established to develop education system by enhancing quality of education and teaching model. However, the existing resource allocation model and teaching in web-based education system has limitations such as ineffective teaching due to inappropriate resource allocation affect the education system. To overcome this problem, a Split and Kernel based Residual Network (SK-ResNet) is proposed to improve quality of education by allocating resources effectively and enhance teaching model in the web based education system. The split technique in ResNet model, divide the tasks and distributed across multiple servers or devices. By splitting and kernel optimizing the tasks, the load on any single system allows the model for faster content processing and delivery. At first, the data are acquired and fed into functional structure of education system, and finally analyzed and integrated into cloud computing based on SK-ResNet model. The experimental results of the proposed method achieved accuracy of 87.29% which is greater when compared to existing method such as Deep Neural Network (DNN) and Hybrid Deep Learning (HDL) model.