Design and Application of WEB based Blended Teaching System using Optimized ResNet50

The Blended teaching system is a learning method that mixes the online classes with traditional offline classroom methods. Web-based blended teaching system influences web technologies for create a blended learning environment. The web-based blended teaching system is effective in training centers, higher studies institutions and it helps to study the students in their own place and reduces the need for infrastructure and materials. The blended teaching system is affecting the staffs in institution because of rules and policies of institutions. The paper proposed an optimized ResNet50 with effective hyperparameter optimizations of Random Opposition Learning Strategy and Greedy Selection based Flamingo Search Algorithm namely ResNet50-RGFSA. The proposed ResNet50-RGFSA used to predict the student’s academic performance via web-based blending teaching system. ResNet50 utilized to determine the academic performance of student and RGFSA is used to identify optimum hyperparameters. The ResNet50-RGFSA is used for effective prediction of academic performance in a WEB based blended learning. The experimental results show that comparison between the Root Mean Squared Error (RMSE), Mean Squared Error (MSE), Mean Absolute Error (MAE) and R<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> of 0.196, 0.178, 0.145 and 0.165 for ResNet50-RGFSA compared with existing model like FSA.