3results about How to "Training accurately" patented technology

The invention discloses a dynamic modeling analysis system for combustion atmosphere data of a biomass oxygen-enriched combustion boiler, and relates to the technical field of dynamic modeling analysis. The system comprises a working condition self-adaptive feature extraction module, a time sequence maintaining model training module, an online self-adaptive correction module and an incremental model updating module. Through a working condition adaptive feature extraction module, a time sequence maintenance model training module, an online adaptive correction module and an incremental model updating module, adaptive feature vectors are generated through feature extraction, a basic model is obtained through training, and online correction and incremental updating are performed by combining feature vector verification threshold judgment. And finally, iterative upgrading is completed through an incremental learning fine tuning model, the reliability of dynamic modeling analysis of the combustion atmosphere data of the biomass oxygen-enriched combustion boiler is improved, and the problem that in the prior art, the reliability of dynamic modeling analysis of the combustion atmosphere data of the biomass oxygen-enriched combustion boiler is low is solved.

The application discloses a model training method, an address positioning method, an electronic device, a storage medium and a computer program product, relates to the technical field of large models and image positioning, and the method comprises the following steps: acquiring a training data set, wherein the training data set comprises a training scene image and a visual question and answer data set of corresponding address information of the training scene image; performing cross-view alignment training on an initial multi-modal address positioning model by using the training data set, to generate an intermediate multi-modal address positioning model; and performing address positioning training on the intermediate multi-modal address positioning model by using the training data set, to generate a target multi-modal address positioning model, wherein the target multi-modal address positioning model is used for performing address positioning analysis on a target scene image to be processed and an address question, to obtain an address answer. The application solves the technical problems of the image address positioning scheme provided in the related art, such as coarse positioning granularity, poor positioning accuracy and poor flexibility of question and answer interaction.

A product quality prediction system based on federated learning includes a server and clients set up on multiple production lines. The server sends an initial product quality prediction model and fused model parameters to the clients. The fused model parameters are obtained by fusing the model parameters sent by each client. The clients include: multiple sensors for collecting product manufacturing process data; a training set construction module for acquiring sensor data and performing feature extraction to construct a local training set; a model training module for training the acquired product quality prediction model using a forward propagation federated training method based on the local training set; encrypting and sending the model parameters during training to the server and updating the local product quality prediction model according to the fused parameters; stopping training when training requirements are met to obtain a trained product quality prediction model; and a product quality prediction module for performing quality prediction based on the trained product quality prediction model.