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A Multi-Entity Business Collaborative Optimization Operation Method Based on Distributed Control (Source, Grid, Load, and Storage)

ActiveCN122092389AImprove utilization efficiencyavoid state
This invention discloses a multi-entity business collaborative optimization operation method based on distributed control, belonging to the field of collaborative optimization technology. The method includes: each distributed business control center determines an acceptable adjustment direction based on a collaborative feasible interval and determines the collaborative pressure level based on a conflict interval; when the pressure threshold is not exceeded, the current operational intention is directionally corrected; when the pressure threshold is exceeded, the operational intention is triggered to revert and switch to a pre-declared secondary business feasible interval, generating corrected operational intention information; when the corrected operational intentions of each distributed business control center reach a preset consistency condition, a stable distributed collaborative operation state is determined. This invention, by determining an acceptable adjustment direction based on a collaborative feasible interval, achieves fine coordination between individual interests and global goals among multiple entities, alleviating the resource inefficiency and interest conflicts caused by insufficient consideration of business-level constraints in traditional methods.
Owner:STATE GRID (TIANJIN) INTEGRATED ENERGY SERVICE CO LTD

A user mining method and device, electronic equipment, program product, and storage medium

PendingCN122288739Aachieve adaptivefast convergenceEngineeringElectronic equipment
This application provides a user mining method and apparatus, electronic device, program product, and storage medium. The method includes: acquiring user data through public API interfaces of multiple social networking platforms and storing the acquired user data in an intelligent computing performance-enhanced file storage service deployed on a cloud computing platform; using a data processing cluster on the cloud computing platform to read the user data from the intelligent computing performance-enhanced file storage service, reconstructing features based on the user data, and storing the reconstructed feature data back to the intelligent computing performance-enhanced file storage service; constructing and training a reinforcement learning model on the cloud computing platform based on the reconstructed feature data; storing historical experience data of the agent in the intelligent computing performance-enhanced file storage service during the training process; deploying the trained reinforcement learning model to a production environment and using the reinforcement learning model to perform user mining based on real-time acquired user data.
Owner:CHINA MOBILE (SUZHOU) SOFTWARE TECH CO LTD +1