8 results about "Situation model" patented technology

The invention discloses a computing power resource intelligent transaction optimization method and system, and relates to the technical field of cloud computing. Comprising the following steps: acquiring multi-source heterogeneous computing power resource data, performing normalization processing and vectorization modeling, and generating a standardized resource feature vector; historical and real-time data are collected to construct a demand side service portrait and a supply side dynamic resource map, and a space-time perception supply and demand situation model is formed; a multi-objective optimization model comprehensively considering resource utilization rate, carbon emission intensity, policy preferential income and transaction cost is established based on the model, and a non-dominated solution set is generated by adopting a Pareto optimization algorithm; and constructing an intelligent matching decision engine based on a reinforcement learning framework, carrying out real-time sensing, dynamic adjustment and execution on the transaction strategy scheme, and outputting a final executable transaction scheme. The technical problems of low computing power transaction efficiency and low resource utilization rate caused by non-uniform computing power resource description, supply and demand situation perception lag, single optimization target and stiffness of a matching mechanism are solved.

The application relates to the technical field of Internet of Things device power consumption management, and particularly discloses a water level monitoring device power consumption self-regulation method and system adopting context situation awareness. First, a multi-level context situation awareness layer and model are constructed by combining local historical hydrological data with low-power access to multi-source external information; then, multi-dimensional operation data of the device are collected, a coupling relationship between the multi-dimensional operation data and the situation model is analyzed, power consumption value is evaluated to determine a regulation level; next, device modules are abstracted into energy consumption nodes, a power consumption topology is constructed, and a power consumption reduction scheme group is generated; subsequently, a digital twin is built, a scheme resilience index is simulated and evaluated, and the optimal scheme is selected; finally, the optimal scheme is deployed, the environment and the strategy effect are continuously monitored, and when a triggering condition is met, backtracking iteration is performed, so that precise and adaptive regulation is realized.

The invention relates to the technical field of automobile artificial intelligence, and provides a vehicle-mounted interaction system and service prediction method based on cross-scene behavior learning, and the system comprises a data layer which collects behavior data of a user in a vehicle, constructs a four-dimensional behavior modeling engine, and compares the collected behavior data with behavior data stored in a cloud knowledge base; the learning layer runs a federal learning framework in a vehicle-mounted edge computing unit, generates a situation model of the current comprehensive state of the user and sends the situation model to the interaction layer; the interaction layer is used for establishing a service execution grading mechanism based on credibility, generating a prediction result, sending the prediction result to the execution layer, and determining a service execution mode according to prediction accuracy; and the execution layer is used for establishing a prediction service matrix and executing a corresponding service action according to the prediction result. According to the method, single-dimensional association is broken through; the dynamic situation is fused, so that the position prediction is more accurate; and a progressive trust mechanism is adopted.

The invention discloses a context control method based on context awareness, an intelligent agent and a storage medium. The situation control method comprises the following steps: acquiring multi-modal data of a current environment; analyzing and reasoning the multi-modal data by utilizing a situation data fusion engine and a situation model to generate a current situation vocabulary, and performing semantic fusion on the current situation vocabulary to generate a current situation state; a target situation state is determined according to the current situation state and an intention utility function, and the intention utility function is obtained according to the user intention and the user utility; matching the situation conversion rules according to the current situation state and the intention utility function; and under the condition that the situation conversion rule is successfully matched, exporting the target situation state into a state conversion function by utilizing an instruction processing module so as to finish the situation conversion of the current environment according to the state conversion function.

The invention relates to the technical field of Internet of Things equipment power consumption management, and particularly discloses a water level monitoring equipment power consumption autonomous regulation and control method and system adopting context awareness. Firstly, multi-source external information is accessed through low power consumption, local historical hydrological data are combined, and a multi-level context sensing layer and a model are constructed; collecting multi-dimensional operation data of the equipment, analyzing a coupling relationship between the multi-dimensional operation data and the situation model, and evaluating a power consumption value to determine a regulation and control level; abstracting a device module as an energy consumption node, constructing a power consumption topology and generating a power consumption reduction scheme group; then building a digital twinborn body, and selecting the optimal toughness index of the simulation evaluation scheme; and finally, deploying an optimal scheme, continuously monitoring an environment and a strategy effect, and performing backtracking iteration when a triggering condition is met, thereby realizing accurate and adaptive regulation and control.

The invention discloses a multi-screen terminal intelligent collaboration method and device based on situational cognition, and the method comprises the steps: carrying out the knowledge-based expression of a historical use scene, and obtaining a historical scene knowledge base; obtaining new task information; processing the historical scene knowledge base and the new task information to obtain a multi-screen display strategy of the new task; processing the multi-screen display strategy by utilizing a collaborative strategy execution and feedback method to obtain an optimized situation model; obtaining user interaction information; the user interaction information comprises a voice instruction, gesture interaction and keyboard and mouse operation; processing the user interaction information to obtain user intention information; and processing the user intention information and the optimization situation model to obtain a multi-screen terminal intelligent collaborative display result. According to the invention, the problems of information islands, resource allocation rigidness and low interaction efficiency in a multi-task, multi-user and multi-device scene can be solved, and situation awareness and space intelligence capabilities in a cooperation process are improved.

The invention relates to the technical field of data security and privacy protection, and discloses a data asset security transaction and privacy protection management system. The system comprises an information extraction module for weaving meta-information, a content entity and an interaction flow into a data asset holographic portrait through a semantic association engine; the sensitive situation sensing module is used for carrying out hierarchical risk identification and deduction on the holographic image to generate a dynamic risk situation model; the strategy deduction module is used for matching the risk features with a strategy knowledge graph to generate a candidate strategy set; the strategy fusion module is used for performing simulation and conflict detection on the candidate strategies and fusing to generate a conflict-free composite security strategy instruction stream; and the strategy efficiency module is used for evaluating the strategy effect and driving the knowledge graph to iteratively update. According to the method, deep semantic association cognition and dynamic modeling of the data assets are realized, a coordinated and conflict-free composite security policy can be automatically generated, and the accuracy of risk perception and the overall collaborative efficiency of policy protection are improved.

A real-time data analysis and context-aware anchor broadcasting method, device and medium, through the integration of multiple levels of technologies such as real-time game data acquisition, character behavior feature analysis, action event prediction, tactical intention inference, deep context model emotion calculation and natural language generation, not only can identify single character behavior, but also can understand the cooperative tactical relationship of multiple characters, and further combine the deep context model to generate time-continuous emotion indicators, so that the voice broadcast and expression rendering of the virtual e-sports anchor can be dynamically adjusted according to the game situation, improving the realism and immediacy of the broadcast, thereby achieving the technical effects of improving the ability to capture key tactical events, optimizing the continuity of virtual anchor emotion performance, and improving the immediacy of the broadcast.