9 results about "Policy information base" patented technology

Embodiments of the present specification disclose an application power consumption control method, related equipment, a storage medium and a program product, to more accurately analyze the attribution of an application in a high power consumption state. The method comprises: receiving stack information of a first thread of a target application, the first thread comprising the top N threads with the highest usage rate of a processor core, the stack information of the first thread being collected and uploaded when the target application is in a high power consumption state, whether the target application is in a high power consumption state being determined based on usage rate information of the target application on the processor core and a temperature of a processor running the target application; determining a factor causing the target application to be in a high power consumption state based on the stack information of the first thread; determining first policy information based on the factor, the first policy information being used to describe a processing operation performed to reduce power consumption of the target application; and sending the first policy information to the processor.

The application provides a policy transfer method and device for reinforcement learning and a storage medium, and belongs to the technical field of machine learning. The method comprises the following steps: obtaining first sample data at multiple simulation time points based on a simulation scene of an autonomous driving scene; determining first policy information and a first prediction model based on multiple groups of the first sample data; in each iteration process, obtaining second sample data at a target time point in the autonomous driving scene based on the first policy information of the current iteration process, updating the first prediction model of the current iteration process based on the second sample data, updating the first policy information based on the updated first prediction model, and performing the next iteration process based on the updated first prediction model and the first policy information. Through the method, the prediction model and the policy information in the simulation scene can be transferred to the autonomous driving scene, so that the action to be performed by the autonomous vehicle can be accurately predicted in the autonomous driving scene, and a better effect can be achieved after the action is performed.

The application discloses a kind of based on public policy information evaluation city group coordination relationship's method, it is related to urban planning data analysis technical field, step S1 obtains the data text of coordinated development policy from network;Step S2 establishes administrative hierarchy category, policy subject topological relationship category and policy theme category, key attribute is coded, forms city group coordinated development policy information base;Step S3 determines the geographical space coordinate of city, and gives city group coordinated development policy information base assignment;New field is established to refer to the coordinate of two cities that there is coordination relationship between each other, forms OD matrix file;Step S4 creates geographical space database, and OD matrix file is imported to geographical space database;Step S5 generates linear model file using XY to Line tool;Step S6 utilizes natural breakpoint grading method and divides into several levels coordination relationship intensity R, forms city group coordination relationship network diagram.

Embodiments of the present application provide a kind of permission management system, method, device, electronic equipment and storage medium, it is related to information security technical field.The system, whenever at least one scene identifier corresponding policy is obtained by server, the specified database is updated using the obtained policy;Client sends the policy acquisition request carrying the scene identifier currently recorded in client and corresponding version number to server regularly;After receiving the policy acquisition request, if the target scene identifier meeting predetermined condition is detected by server, then generate and send the feedback result to client;Client updates local policy information based on the feedback result;When detecting the user operation for any scene identifier represented application scenario, client issues the notification information about permission application based on local policy information.The compliance degree about the permission application of client can be improved by using the scheme provided by the embodiments of the present application.

The invention relates to a multi-modal semantic and dynamic adaptive industrial policy matching method and system, and relates to the field of information processing technologies, and the method comprises the steps: obtaining enterprise entity data and demand policy information; obtaining an enterprise type and an enterprise historical type based on the enterprise entity data; when the enterprise type is consistent with the enterprise historical type, calculating a policy matching degree based on the enterprise entity data and the demand policy information, and defining the policy matching degree as a final matching degree; when the enterprise type is inconsistent with the historical enterprise type, searching change policy information based on the enterprise type; calculating a change matching degree based on the enterprise entity data and the change policy information, and defining the change matching degree as a final matching degree; and analyzing policy suggestions through the final matching degree and outputting the policy suggestions. The method has the effect of improving the accuracy and reliability of the industrial policy matching result.

The embodiment of the invention provides a policy information pushing method and device based on policy timeliness and user types, and relates to the field of information processing and pushing. According to the method, policy information and metadata of the policy information are obtained by receiving a push request of a policy provider, and the policy information comprises a validity period, a target user type, an applicable area and a policy type; determining a user type, a service area and demand degree distribution for different policy categories based on historical interaction data of the user; and pushing matched policy information in combination with metadata, user types, demand degree distribution and service areas. Through dynamic area matching and personalized demand analysis, accurate and timely policy pushing is realized, information reaching efficiency and user experience are improved, and the policy pushing method is suitable for a government or an institution to distribute policy information to a specific user group.

This application provides a method and a related communication apparatus applicable to the communication field. In the method, a network device receives a first notification message sent by a terminal device, where the first notification message indicates that the terminal device has completed training on a target model, and the first notification message includes a model name corresponding to the target model. The network device then determines policy information based on the uplink channel state information of the terminal device; and sends a lightweight indication message to the terminal device.

This invention provides an intelligent push and analysis method and system for new energy and strategic emerging industry policies. The method includes: acquiring industrial policy information related to new energy and strategic emerging industries; performing structured processing on the industrial policy information to generate structured information; wherein the structured information includes domain relevance representation; constructing a user profile based on user attribute information and historical interaction behavior; combining the domain relevance representation and the user profile to determine the user preference index corresponding to each structured information; ranking the structured information based on the user preference index to obtain a ranking result, and pushing at least a portion of the structured information to the user according to the ranking result; determining the professional field indicated by the user profile, and based on the professional field and preset domain knowledge, performing trend inference on the structured information belonging to the professional field in the ranking result to generate decision support information, thereby enabling accurate push and analysis of policy information based on user needs.

The invention discloses an electronic insurance policy testing method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining electronic insurance policy information and reference insurance policy information of a to-be-tested product in response to a selection operation of the to-be-tested product; comparing the electronic insurance policy information with the reference insurance policy information to obtain a first comparison result; when the first comparison result shows that inconsistent information exists in the electronic insurance policy information and the reference insurance policy information, outputting the electronic insurance policy information, the reference insurance policy information and the inconsistent information; and in response to a confirmation operation on the inconsistent information, updating the reference insurance policy information or the electronic insurance policy information based on the inconsistent information. According to the scheme, manual testing is not needed, so that the testing efficiency and the testing accuracy can be effectively improved.