3results about How to "Accurate and Efficient Prediction" patented technology

This invention provides a training and prediction method, system, device, and storage medium for a pressure prediction model, belonging to the field of urban intelligent water supply network technology. The training method for a multi-monitoring-point network pressure prediction model includes: acquiring historical pressure data of the monitored urban water supply network; constructing a pressure prediction model, which includes a temporal convolutional network model and a long short-term memory network model; jointly training the convolutional network model and the long short-term memory network model based on historical pressure data to obtain a trained pressure prediction model; and using this trained pressure model to predict the pressure data of each monitoring point on the monitored urban water supply network based on the historical pressure data. This invention provides a training method for a pressure prediction model that, based on the correlation and periodicity of multiple monitoring points on an urban water supply network, efficiently and accurately predicts the pressure data of each monitoring point on the network.

This invention discloses an intelligent analysis method and system for the bottom support status of caissons based on correlation features, relating to the field of caisson construction monitoring technology. The method includes: acquiring strain time-series data of the target monitoring location at the bottom of the caisson during the drainage sinking stage; preprocessing the strain time-series data and classifying and labeling the support status, constructing labeled sample data, where the support status includes both voided and non-voided states; performing various correlation analyses on the labeled sample data to mine multiple correlation information between the sample data and the support status; constructing a classification prediction model for each correlation information, and training the classification prediction model using each correlation information; deploying the trained classification prediction models to the non-drainage sinking stage, and comprehensively judging the bottom support status of the caisson during the non-drainage sinking stage based on the prediction results of each classification prediction model. This invention can achieve accurate and efficient identification of the bottom support status of caissons during the non-drainage sinking stage.

The application discloses a 6G wireless communication prediction channel modeling method based on large language model fine tuning, relates to the technical field of channel prediction, and comprises the following steps: processing channel measurement data, matching corresponding text data, dividing a training set and a test set, and constructing a channel prediction data set; designing a channel encoder and a dual-domain fusion module to extract channel features, and designing a text-driven encoder to extract text features; fine tuning a large language model by using the extracted channel and text features, enhancing multi-modal perception and transfer learning capability; designing a fine tuning module, fine tuning the output of the large language model, and projecting to predicted future channel state information; designing an angle consistency loss function, training a prediction algorithm based on large language model fine tuning in combination with prediction loss, and obtaining a trained network architecture; and iteratively predicting the space-time domain channel state by using the trained network, and outputting a channel prediction result. The system has high-precision prediction performance, and has outstanding practical value and popularization prospect.