Multisource heterogeneous data fusion-based mobile learning system course scheduling algorithm

Abstract

The invention discloses a multisource heterogeneous data fusion-based mobile learning system course scheduling algorithm. The algorithm is very simple and does not cause the phenomena such as repeatedteaching and class missing; the sciences, the arts, the arts in art and the sciences in art have different to-be-learnt subjects, so that the subjects are divided, class distribution of teacher can be carried out more conveniently, teacher distribution is carried out after subject distribution, the operation is convenient and mistakes are not easy to cause; classes with different properties needdifferent to-be-learnt subjects, and different class properties are numbered, so that a class schedule generation module does not compile subjects of the sciences such as physics, chemistry and the like into the arts classes, and the distinguishing is facilitated; and a cell subject replacement module is used for screening repeated courses in a day so as to ensure that the courses are not repeated, and adding secondary courses after primary courses so as to avoid the condition that no primary courses exist in the day.

Description

technical field [0001] The invention relates to the field of multi-source heterogeneous algorithms, in particular to a shift system scheduling algorithm based on multi-source heterogeneous data fusion. Background technique [0002] With the merger and expansion of colleges and universities, course scheduling has become a heavy task in the teaching management of colleges and universities. In order to reduce the workload of arranging courses, intelligent course arranging systems are widely used in colleges and universities. Course scheduling in colleges and universities has the characteristics of multi-stage and hierarchical arrangement. The Office of Academic Affairs first uses smart arrangements to handle most of the courses, and then the college arranges or adjusts the remaining courses. Therefore, the effectiveness of the intelligent course scheduling system is directly related to the efficiency and quality of the entire course scheduling process. [0003] In the field ...

AI Technical Summary

Problems solved by technology

The most worrying problem in the traditional manual scheduling is the conflict of teacher resources or site resources, and the work is cumbersome and the workload is huge, especially in large-scale middle schools. There are more problems when scheduling classes

The existing methods to solve the course scheduling problem are mainly the backtracking method and the genetic algorithm, among which the backtracking algorithm is the most basic algorithm among all search algorithms, and it adopts the idea of ​​returning if it fails to get through as its control structure, which is quite Because the root-first traversal method is used to construct the solution tree, it can be used to find solutions or all solutions and the optimal solution; the backtracking algorithm consumes less space, and when it is used together with the branch and bound method, the Answering questions with deeper levels in the tree has a better effect, but it is used in questions where the successor node may be the same as the predecessor node, resulting in a loop

[0004] In the existing technology, there is a lack of a course scheduling system specially suitable for professional testing and training education, and it relies more on manual management, and there are often situations such as wrong scheduling and missing scheduling, which not only cannot conveniently and flexibly meet the needs of students Carry out correct and automatic class scheduling according to the actual situation, and it is impossible to summarize the class information of statisticians and teachers in real time

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