Deep Learning-Guided Simulated Annealing for Designing Vocational High Educational System.

Abstract

With the rapid development of web technology and the improvement of online purchasing products, the traditional classroom instructing model has been unable to bear the requirements of teachers and students. Aiming at the problems of instructing and correspondence, a deep learning-based educational control system supporting B/S structure is designed and implemented. The system adopts the software engineering model for adjustment, uses Java language as the main programming language of the system, uses SQL Server database to store various intelligences, and realizes online teaching and facing problems, data division, teaching direction and testing, and many other cosecants. Due to its structural features and limitations of algorithmic production, traditional fancy emotional literature models perform poorly in the classification of white-eye dimensional data. In order to improve the simulated annealing prediction of full-dimensional data, a modified brain emotion based on simulated annealing algorithm is proposed. By improving the network structure and using the feign annealing algorithm rules, the training process of conceiving scientific standards is proposed, its data fitting capacity and prediction ability are well refined. And the prediction accuracy of the model for high-dimensional data classification problems is improved. Some data adjustments commonly used for instructing performance of our proposed algorithm are excluded from the experiments.