System and method for predicting demanded quantities of teachers in different subjects based on neural network - ZHUANG ZHIYUAN; ZHUANG XIAO; KAN JILI (2024)
The invention discloses a system and a method for predicting teacher demand quantity of different subjects based on a neural network, and belongs to the field of neural networks, and the method comprises the following steps: S1, constructing a matrix of historical single-class plan curriculum quantity and a vector of historical class quantity, calculating historical total plan curriculum quantity, and constructing a matrix of historical total plan curriculum quantity of subjects; s2, constructing a vector of a subject single-person standard course quantity, and constructing a vector of a theoretical teacher demand quantity after data operation and arrangement; s3, constructing a vector of historical actual teacher demand, establishing and training a feedforward neural network model, importing changed information, and predicting teacher demand of each subject; according to the method, the teacher demand is accurately calculated by comprehensively considering factors such as grades, subjects, class scales, cour