The invention discloses an intelligent
distribution system based on
deep learning and
dynamic resource scheduling, and relates to the technical field of
resource scheduling. Comprising the steps of 1, creating an intelligent
distribution system, 2, integrating an NLP engine through a user request analysis module, carrying out intention recognition and semantic analysis on a user request, extracting a service type and related parameters, carrying out triple positioning by fusing GPS /
base station / Wi-Fi, and obtaining user position information, and 3, constructing a
service personnel digital portrait
library through a
dynamic resource management module, 4, calculating the
geographic proximity of candidate
service personnel and the user position through an intelligent matching module by adopting a Manhattan distance formula, training an LSTM neural network based on historical service data by utilizing a
service quality prediction model, and obtaining the current position and the
moving speed of the
service personnel through the LSTM neural network; and step 5, obtaining user service
evaluation data through a feedback module, triggering a
service quality prediction model to perform retraining, and outputting a
service quality prediction value in the
confidence interval, generating a real-time comprehensive priority according to the
geographic proximity, the service quality prediction value and the service emergency degree, and recommending services according to the comprehensive priority, and step 5, obtaining user service
evaluation data through the feedback module, and triggering the service quality prediction model to perform retraining. And updating the service personnel digital portrait
library by adopting an
incremental learning strategy.