Computer Intelligent Course Scheduling System Based on Deep Learning

Abstract

In recent years, with the continuous development of computer technology, the successful application and penetration of computer technology in all aspects of society has made people more and more aware that the problem of school class scheduling can be solved by computer technology. The purpose of this paper is to study the design of computer intelligent course scheduling system based on deep learning. First of all, regarding the general problems existing in the current intelligent course scheduling, starting from the needs of users, and on the basis of many research results in the field of intelligent course scheduling at home and abroad, a BP neural network is proposed to provide decision-making for genetic algorithms to achieve system self-adaptation method of scheduling. Secondly, carry out detailed system design, database design, scheduling, and realize the software development of all functions of the intelligent course scheduling system. Finally, the practical problems of course arrangement are tested, the quality and efficiency of course arrangement results are analyzed and evaluated, and the practicability and practicability of the system are discussed. The experimental results show that the running time and the average teacher utilization rate of the improved genetic algorithm system both reach 95%, which is higher than the GA and AGA algorithms.