System and method for predicting demanded quantities of teachers in different subjects based on neural network

• Main Authors: ZHUANG ZHIYUAN, ZHUANG XIAO, KAN JILI
• Format: Patent
• Language: Chinese; English
• Published: 07.05.2024
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES; PHYSICS; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR

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