Research on Automated Research and Judgment System for Intelligent Work Order Based on GCNN Recommendation Model
To improve the computational speed of data information,an intelligent work order automated research and judgment system based on graph convolutional neural network(GCNN)recommendation model is designed.Automated monitoring and intelligent processing techniques are used to analyze the situation related to work order data types.Creatively using the combination of artificial intelligence and GCNN recommendation model,the work order automation research and judgment system realizes the automatic classification and identification of work orders to realize work order creation,intelligent allocation,and internal work order flow,etc.5G communication technology is applied to the system to strengthen the response to work order information feedback and improve the data information processing capability.The test results show that the work order completion rate of the system is more than 90%,and the interference rate is under 2%.The research provides a feasible program for automated research and judgment of intelligent work order types.
Power monitoring automationGraph convolutional neural network(GCNN)Work order automationArtificial intelligenceResearch and judgment system5G communication
万方数据
维普
