17results about How to "Realize association" patented technology

The embodiment of the invention provides a fault positioning method and device based on association rules, equipment and a program product. Relates to the field of energy storage system fault diagnosis. The method comprises the following steps: acquiring a state code, a fault code and an operation parameter of the energy storage thermal management equipment; based on the state code, the fault code and the operation parameter, generating a fault rule base by adopting an association rule mining algorithm; unsupervised clustering analysis is carried out on the operation parameters, and abnormal data deviating from the standard are screened out; fusing the abnormal data with the fault rule base to generate a fault map; and based on the fault map, a fault positioning report of the energy storage thermal management equipment is output, the fault positioning report at least comprises a fault propagation path and a maintenance scheme, and the fault propagation path is a path of a causal relationship between the fault code and the abnormal mode. The method is used for achieving the effect of improving the fault positioning efficiency and accuracy.

The present application relates to the technical field of environmental monitoring and pollution tracing, and discloses a basin-scale perfluorinated compound tracing method and system based on artificial intelligence, which integrates multi-source data in a basin to construct a unified spatial and temporal granularity basin multi-source data cube, identifies perfluorinated compound structures through a virtual spectrum diagram enhanced deep learning model, simulates pollutant spatial and temporal concentration distribution by combining a graph neural network of a physical mechanism, and then inversely propagates and matches source characteristic fingerprints to invert potential emission source contribution, outputs a pollution source contribution heat map and a priority control enterprise list, solves the core problems of difficulty in joint analysis of multi-source data, difficulty in identification of unknown compounds and difficulty in quantitative determination of multi-source superposition contribution in basin-scale perfluorinated compound tracing, and provides support for precise pollution control.

Embodiments of the present application provide a kind of based on graph's alarm event determination method, device, electronic equipment and storage medium, method includes: the security log is converted into the target graph information corresponding to the security log;Based on the target graph information and the graph rule configuration information obtained in advance, generate first graph query statement;The graph rule configuration information at least includes: the rule for generating the first graph query statement;The graph information matching operation is carried out between the first graph query statement and the graph information in graph database;The graph database is used to store at least one kind of graph information;According to the graph information matched to the first graph query statement, generate alarm event.The embodiments of the present application realize the association of security log before and after and the association between multi-source security log by graph database, can effectively reduce false alarm rate;In addition, based on the high efficient query ability of the association relationship of graph database itself, the low time and low resource consumption of the association analysis of multiple security logs can be realized.

The invention provides an object pose estimation method. The object pose estimation method comprises the steps of obtaining object structure features of a target object, hand pose features of a robot hand and contact area features of the hand in contact with the target object; fusing the object structure feature and the contact area feature to obtain a first fusion feature; fusing the hand posture feature with the contact area feature to obtain a second fused feature; fusing the first fusion feature and the second fusion feature to obtain a global fusion feature; and performing pose estimation based on the global fusion features to obtain a target pose of the target object. According to the embodiment of the invention, the accuracy of object pose estimation can be improved.

The invention provides an optical cable design intelligent drawing system and method based on fusion of multi-source acquisition data. Through combination of the large model processing layer and the core function layer, automatic analysis, association and compliance detection of the multi-source collection data are realized, the work of manually completing verification and compliance detection of the multi-source collection data in the prior art is replaced, and the manual workload is greatly reduced, so that the multi-source collection data verification and compliance detection can be realized in a complex scene, and the multi-source collection data verification and compliance detection efficiency is improved. Automatic processing can be completed based on the combination of the large model processing layer and the core function layer of the system, and the technical effect of improving the completion efficiency and precision is generated due to the reduction of the manual workload.

The invention relates to the technical field of situation awareness, and discloses a power grid communication network security situation awareness method, which comprises the following steps of: performing time sequence normalization processing on multi-source heterogeneous security logs and traffic data of a power grid network to obtain a multi-source security data set; performing power protocol association analysis on the multi-source security data set to obtain a security event sequence; constructing a power grid attack knowledge graph; performing association matching on the security event sequence and the power grid attack knowledge graph, and performing adaptive sensitivity weight evaluation on the operation state information of the power grid network to obtain a threat judgment result and confidence; carrying out situation analysis and quantification on the asset importance and the real-time load level of the power grid network to obtain a comprehensive security situation index; mapping the comprehensive security situation index to a preset early warning strategy response library to obtain an early warning signal and a protection strategy; according to the invention, the efficiency of power grid communication network security situation awareness can be improved.

Embodiments of the present application disclose a method and device for constructing a literature knowledge base, electronic equipment and a storage medium, and relate to the field of knowledge graphs. The method comprises: determining at least one piece of literature; obtaining multi-modal data and metadata of each piece of literature; the multi-modal data comprises image data and text data; obtaining an image feature vector and a text feature vector of the at least one piece of literature based on the multi-modal data of the at least one piece of literature; constructing a literature knowledge graph based on the metadata, the image feature vector and the text feature vector of the at least one piece of literature; and constructing the literature knowledge base based on the literature knowledge graph. The embodiments of the present application associate the multi-modal data of different literature by constructing a literature knowledge graph, and quickly locate the multi-modal data associated therewith through a literature identifier, thereby achieving efficient literature management and retrieval.

The invention provides a farmland ecological meteorological monitoring method and device, and the method comprises the steps: constructing a rainfall risk time sequence model based on historical daily scale air temperature and rainfall data; the current spring effective accumulated temperature is obtained and compared with the historical same period, and a climate anomaly factor is obtained; on the basis of the abnormal factors and the current observation sequence, the most probable hidden state at the current moment is determined through the forward probability, rolling prediction is conducted through the corrected transfer matrix from the current moment to the prediction moment, and the rainfall risk probability from the current moment to the prediction moment is obtained; comparing the rainfall risk probability with the soil moisture bearing capacity of the farmland to be monitored, and obtaining the risk probability actually borne by the farmland ecosystem as a first risk probability; based on real-time soil conditions and land parcel characteristics, estimating the probability of ecological risks caused by farming adjustment behaviors; a risk driving value is obtained based on the first risk probability, an ecological cost value is obtained based on the ecological risk probability, and when the risk driving value is larger than the ecological cost value, a final farming decision is generated, and the farming decision behavior is dynamically adjusted based on the current real-time climate through deep processing and association of the farmland ecological meteorological data.

This application provides a method and system for intelligent identification of minerals in weak information areas based on transfer learning, relating to the field of transfer learning technology. First, a source domain mineral sample set and a set of mineral samples to be identified in weak information areas are obtained. Then, geological correlation elements between the two are extracted and a cross-domain feature mapping is constructed. The original features of the minerals in the weak information areas are subjected to transfer adaptation processing to generate intermediate features of the minerals in the weak information areas that are adapted to the feature dimensions of the source domain. Next, sparse feature dimensions in the intermediate features are identified, and the corresponding feature distribution patterns of the source domain are used to complete the features, generating completed features. The completed features are input into a pre-trained transfer learning identification model for cross-domain identification, generating preliminary identification results. Finally, source domain samples with similar geological correlation elements are selected to determine the transfer deviation, correct the preliminary identification results, and generate the final identification results, effectively improving the accuracy and reliability of mineral identification in weak information areas.

The invention relates to the technical field of data processing, in particular to a survey data real-time synchronous storage method for indoor and outdoor work integration. According to the method, on a mobile terminal side, a change record containing a new space coordinate, a change operation type and a unique identifier is generated when field personnel perform graph editing, whether the new space coordinate is self-intersected and consistent with the change operation type is checked in real time, and the change record is uploaded only when the two items of checking are passed; invalid or logic conflict geometric data are prevented from entering the server, and the data quality problem caused by lack of editing real-time verification is solved.

The invention discloses a VLA-based low-speed park automatic driving method, and relates to the technical field of automatic driving, and the method comprises the steps: collecting a plurality of park environment data, generating a panoramic park environment perception tensor, executing semantic element recognition and dynamic subject motion trend pre-judgment, and generating a park environment semantic analysis topology with a dynamic motion trend; performing advance obstacle avoidance path planning and stationary path optimization on the park environment semantic analysis topology with the dynamic motion trend and the preset driving path, and generating a park automatic driving control instruction set with dynamic safety redundancy; and executing the instruction set and collecting vehicle driving state feedback data to generate a multi-mode-path planning collaborative optimization parameter tensor, and continuously adjusting automatic driving execution logic. Therefore, automatic driving can continuously adapt to scene changes in long-term operation, and the operation stability and robustness are improved.

This invention discloses a method and apparatus for data association. The method includes: collecting the large box codes of the large boxes to be collected to form a first data queue; after the large boxes to be collected are loaded onto the pallet, collecting the large box codes of the large boxes to be collected on the top of the pallet to form a second data queue, wherein the second data queue corresponds one-to-one with the large box codes of the large boxes to be collected on the top of the pallet; obtaining pallet-associated large box data based on the first data queue and the second data queue; associating the pallet-associated large box data with virtual pallet codes to generate box-pallet association data, thereby realizing data association, which can improve the accuracy and reliability of data association, and also improve the efficiency of data association.

The invention discloses a behavior recognition method and device based on a video text model and a storage medium, and belongs to the technical field of artificial intelligence. The method comprises the following steps: acquiring video data to be identified, and performing frame extraction on the video data to obtain multiple video frames; inputting the multiple video frames into a preset video text model to obtain a behavior recognition result of the target object in the video data; wherein the video text model comprises an intra-frame attention module, a cross-frame attention module and a video text feature fusion module. According to the method, the time sequence relation between the video frames can be captured, the information between different frames can be integrated, semantic information is provided for behavior recognition, a video text model can comprehensively judge the behavior action of the target object from the two aspects of vision and semantics, and therefore the accuracy of behavior action recognition in the open set video is improved.

The application discloses a static and dynamic combined fuzzy gesture recognition method and device and medium. The method comprises the following steps: extracting gesture feature points of a gesture image to be recognized of a user at a current time, and taking the gesture feature points as first feature points; normalizing a first position difference function of the first feature points to generate a spatial domain feature matrix; obtaining a plurality of historical gesture images of the user within a preset historical time length; extracting gesture feature points of each historical gesture image, determining gesture feature points at the same position in adjacent historical gesture images, and taking the gesture feature points at the same position as second feature points; normalizing a second position difference function of the second feature points to generate a space-time sequence feature matrix; inputting the spatial domain feature matrix and the space-time sequence feature matrix into a pre-constructed deep convolutional neural network model respectively, and outputting a gesture posture and a gesture action category of the user at the current time, thereby improving the gesture recognition accuracy.

This invention relates to the field of data processing technology, specifically to a method for real-time synchronization and database entry of survey data for integrated field and office work. On the mobile terminal side, this invention generates a change record containing new spatial coordinates, change operation type, and a unique identifier when field personnel are editing graphics. It also instantly verifies whether the new spatial coordinates are self-intersecting and consistent with the change operation type. The change record is only uploaded after both verifications pass. This avoids invalid or logically conflicting geometric data from entering the server, solving data quality problems caused by the lack of real-time verification during editing.

This application provides a method for identifying psychological states based on the fusion of multimodal biometrics and scale data, belonging to the field of psychological state recognition technology. The method collects physiological data from target subjects when answering psychological scales and extracts the physiological features corresponding to each question; calculates initial scale scores based on the answer data and determines the initial correlations between questions; constructs a heterogeneous graph model with questions as nodes, physiological features and semantic features as node features, and the initial correlations as connecting edges; inputs this model into a graph attention network, dynamically adjusts the attention coefficients through the fusion values ​​of physiological and semantic features, and iteratively aggregates neighbor node information to obtain higher-order node representations; after graph pooling the higher-order node representations to output a graph representation, it fuses it with the initial scale scores across modalities, and determines the psychological state based on the fusion result. This application integrates physiological responses and scale semantic information to achieve accurate psychological state recognition.

This invention discloses a three-dimensional spatial multi-omics reconstruction method based on histological images, comprising: acquiring continuous sections of biological tissue; selecting a portion of the sections, performing spatial single-omics sequencing on each section to obtain corresponding spatial single-omics measured data, and acquiring its morphological image, wherein the molecular information of each spatial single-omics measured data is different; acquiring only morphological images for the remaining sections; mapping the morphological images of all sections to a three-dimensional coordinate system; extracting the morphological features of single cells in each section; training a spatial multi-omics prediction model using all spatial single-omics measured data and their corresponding morphological images; inputting all morphological features into the trained model, performing encoding fusion, association calculation with a learnable prototype set, and decoding to output corresponding multi-omics prediction data; thereby generating three-dimensional spatial multi-omics expression data. This invention overcomes the cost and throughput bottlenecks of slice-by-slice sequencing, achieving high-resolution three-dimensional multi-omics reconstruction of large-volume tissues.