3results about How to "Mitigation resources" patented technology

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.

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.

The application discloses a layered scheduling optimization method and platform for multi-resource dynamic balancing of engineering projects, and belongs to the technical field of engineering project scheduling optimization. The method comprises the following steps: an engineering project data model containing an activity directed acyclic graph, multi-type resource requirements and milestone constraints is established; a resource coupling coefficient is calculated, and a feasible time window in the form of a multi-section closed interval union is generated for each activity; a resource pool quota is allocated among projects according to a resource urgency index at a strategic layer; adaptive rolling rescheduling is started according to four types of trigger conditions at an operation layer; and a cross-layer bidirectional closed loop is formed through step-by-step feedback. The platform comprises the following modules: a multi-source data acquisition module, a biological meteorological window management module, a resource demand prediction module, a three-layer scheduling engine module and the like. The application can simultaneously realize single-resource balancing and cross-resource collaboration, so that the scheduling result has biological meteorological sensitivity, and can quickly respond when a disturbance arrives, thereby relieving on-site work, improving resource pool utilization and reducing the deviation of the construction period.