441 results about "Geographic site" patented technology

The invention provides an advertisement recommendation method and system fused with user dynamic behavior modeling. The method comprises the following steps: acquiring a cross-device operation record of a user on multiple terminal devices, and synchronously acquiring a device unique identification code, high-frequency click area data and an operation timestamp; and constructing a space-time relation graph based on combined analysis of the equipment switching time interval and the click behavior, and generating a feature set reflecting the behavior correlation degree. The trajectory similarity is calculated at the edge calculation node through hardware acceleration, and migration correlation parameters are generated. And inputting the space-time relation graph into a behavior analysis model to extract coherent behavior characteristics, and forming a multi-dimensional scene portrait in combination with geographic position change and interface element distribution. And finally, through identifying a user cross-device interest migration mode, dynamically screening advertisement contents matched with the current scene, and realizing accurate pushing strategy optimization based on behavior continuity. According to the technical scheme provided by the invention, the accuracy of cross-terminal advertisement recommendation and the scene response speed are remarkably improved.

The invention relates to a multi-model space-time combination flood peak prediction method fusing physical constraints, which comprises the following steps of: acquiring static space data, dynamic time sequence data and boundary data of a research drainage basin, converting the static space data of the digital elevation model into a grid matrix, and calculating the dynamic time sequence data of the research drainage basin according to the grid matrix and the dynamic time sequence data of the research drainage basin; representing an elevation value of each geographic position, extracting gradient features by using gradient calculation according to the elevation values, and performing normalization processing on the gradient features to obtain normalized gradient features; a CNN-Bi-LSTM-Transform prediction model is constructed, the prediction model comprises a spatio-temporal data alignment module, a CNN convolutional network, a spatio-temporal feature splicing module, a bidirectional long and short term memory network and a Transform module, the prediction model is trained, and a loss function during training adopts a physical constraint loss function composed of mean square error loss and water conservation constraint terms and is used for flood peak prediction.

Techniques for generating a prompt for a language model to determine an action responsive to a user input, are described. In some embodiments, the system receives a user input, determines one or more application programming interfaces (APIs) configured to perform actions that are relevant to the user input and exemplars representing examples of using the APIs with respect to user inputs similar to the current user input. The system further determines device states of devices that are determined to be related to the user input and also determines other contextual information (e.g., weather information, time of day, geographic location, etc.). The system generates a prompt including the user input, the APIs, the exemplars, the device states, and the other contextual information. A language model processes the prompt to determine an action responsive to the user input and the system causes performance of the action.

The invention discloses an air pollutant concentration prediction method and related equipment thereof, and relates to the technical field of data processing. The method comprises the following steps: acquiring current pollutant concentration data, current meteorological data and target site geographic position data corresponding to a target environment monitoring site; taking the current pollutant concentration data, the current meteorological data and the geographic position data of the target station as target input data of the prediction model; wherein an input module of the prediction model is used for performing modal decomposition processing on input data to obtain multiple pieces of modal data; the time feature extraction module is used for extracting time feature data; the spatial feature extraction module is used for extracting spatial feature data; the space-time fusion convolutional network module is used for extracting space-time features; the output module is used for outputting a prediction result; determining a prediction result of the air pollutant concentration corresponding to the target environment monitoring station according to the output result; the method achieves the effects of improving the comprehensiveness and accuracy of a prediction result and expanding application scenes.

The invention provides an intention guide pushing method and system based on geographic position information and multimedia interaction. The method comprises the following steps: constructing an interest model based on a geofence technology and a deep neural network; generating a user activity intention prediction result based on the interest model, obtaining a behavioral rhythm analysis result by using a Bayesian network and a time sequence prediction algorithm based on the user activity intention prediction result, and constructing a user and place relation graph by using a graph theory algorithm based on determining the optimal pushing opportunity of the behavioral rhythm analysis result. Generating a time sensitivity optimization scheme; generating customized content based on a time sensitivity optimization scheme, processing the customized content by adopting an emotion analysis method, a collaborative filtering algorithm, an auto-encoder and a multi-head attention mechanism to obtain final content, adjusting the final content through an instant feedback mechanism, and generating a multimedia push packet; according to the invention, the performance and service quality of the intelligent pushing system are improved, and more accurate and personalized recommendation experience is provided for the user.

The invention discloses an air quality prediction method for mining a space-time attention mechanism based on multiple relationships. The method comprises the following steps: constructing a pollutant concentration change matrix and a meteorological change matrix; acquiring geographical location information data, site feature data and time sequence data of the monitoring sites; determining edges of a space-time diagram according to the pollutant concentration data set and the historical meteorological data set, determining nodes of the space-time diagram according to the geographic position information data, and constructing a space-time diagram structure; determining an adjacent matrix according to the space-time diagram structure, and normalizing the adjacent matrix according to a second normalization formula; training the neural network model to obtain an air quality prediction model; and inputting to-be-detected target data into the air quality prediction model, and outputting target predicted air quality data through the air quality prediction model. According to the invention, the accuracy and timeliness of predicting pollutants in the air can be improved.

The invention relates to the technical field of task matching, and provides a task matching method based on user information and task characteristics, which comprises the following steps: step 1, collecting and analyzing user information which comprises but is not limited to employment information, skilled direction, experience and price; 2, analyzing task information, wherein the task information comprises but is not limited to basic information and additional information; the basic information collection includes but is not limited to task titles, task description, task categories, budget ranges, time requirements, task importance and geographic position requirements; 3, establishing a multi-dimensional matching model, and mapping the user information and the task features; step 4, optimizing and sequencing matching results by utilizing a machine learning algorithm; and 5, dynamically adjusting the matching weight, and continuously improving the matching precision according to historical data. According to the task matching method based on the user information and the task features, the task allocation efficiency and stability are improved, and personalized task recommendation is provided.

The invention belongs to the technical field of geographic information data processing, and discloses a graph attention-based road slope surface displacement time sequence prediction method, which comprises the following steps of: obtaining surface displacement time sequence data of a plurality of monitoring stations and associated environmental influence data, and constructing a weighted adjacency matrix based on geographic positions of the monitoring stations, defining an initial spatial topological relation; carrying out feature fusion on the displacement data and the environment data, and constructing an attribute-enhanced feature matrix; respectively inputting the weighted adjacency matrix and the feature matrix into a graph convolutional network and a graph attention network for parallel processing; extracting structured spatial features by the GCN through a fixed topological structure, and generating a first feature representation; the GAT adaptively allocates a dynamic weight by using an attention mechanism, extracts a non-uniform spatial dependency feature, and generates a second feature representation; and fusing the two feature representations, inputting a time sequence modeling module to analyze time dependence, and finally outputting a surface displacement prediction result at a future moment. According to the method, the accuracy of surface displacement prediction is remarkably improved.

The invention provides a 5G message, short message and voice fusion information touch method and system, and relates to the technical field of information processing. The method comprises the following steps: acquiring to-be-sent information content, real-time geographic position information of a user and an initial multi-mode user portrait; optimizing the initial multi-modal user portrait by using the to-be-sent information content and the real-time geographical location information of the user to obtain a target multi-modal user portrait; analyzing the information content to obtain an analysis result, and determining a target communication strategy corresponding to the information content by using a reinforcement learning framework based on the target multi-mode user portrait and the analysis result; based on the target communication strategy, determining a target communication resource allocation scheme according to the real-time geographical location information of the user and the network condition by adopting a dynamic resource allocation algorithm; and based on the target communication resource allocation scheme, executing an information transmission process, and introducing a differential privacy protection mechanism to encrypt the information transmission process. According to the method and the device, the information content reaching accuracy is improved.

The invention provides a surveying and mapping result management method and system based on big data, and the method comprises the steps: obtaining geographic space surveying and mapping data through employing an unmanned plane, a vehicle-mounted laser radar and a sensor, and recording the time, position and equipment information of the surveying and mapping data in real time; a regularizer based on online linear optimization classifies the surveying and mapping data according to geographic positions, collection time and data types, and uploads the classified surveying and mapping data to a distributed storage system; performing data cleaning, format unification and quality verification on the stored surveying and mapping data to generate standardized surveying and mapping data; constructing a knowledge base based on a large language model (LLM), performing semantic analysis and feature labeling on the standardized surveying and mapping data by using geographic space operators in the knowledge base, and establishing a spatial index of the standardized surveying and mapping data; and receiving a user retrieval request, and performing privacy protection retrieval on the standardized surveying and mapping data based on the spatial index.

The invention provides a coordinate system conversion method, system and device and a storage medium, and relates to the technical field of surveying and mapping, and the method comprises the steps: obtaining a first coordinate type of a plurality of coordinate systems to be converted and a second coordinate type of a target coordinate system set by a user; determining a conversion parameter of each coordinate system to be converted by combining the first coordinate type and the second coordinate type; according to the conversion parameters, converting each to-be-converted coordinate system into a target coordinate system, and converting a first coordinate point under each to-be-converted coordinate system into a second coordinate point under the target coordinate system; determining geographic feature parameters associated with the to-be-converted coordinate systems according to the geographic position information of the areas corresponding to the to-be-converted coordinate systems; and adjusting each second coordinate point in combination with the geographic feature parameters and the coordinate system incidence matrix to generate a target coordinate point. The technical effect of the invention is that the relative position relation between the coordinate points after the coordinate system conversion is consistent with the original relation before the conversion.

The invention relates to an improved NSGA-III-based multi-target geographic site selection optimization method and system, belongs to the technical field of optimization in business management and resource planning, and particularly relates to resource allocation and site selection decision making by using a calculation model. The technology aims to solve the problems of slow scheme convergence, non-uniform solution set distribution and low calculation efficiency when multi-target site selection is carried out under limited resources. According to the scheme, geographic space data is preprocessed, and an initial population representing different site selection schemes is generated; carrying out optimization iteration by adopting an improved NSGA-III algorithm, and calculating a plurality of objective functions such as coverage rate, normalized population density and medical service accessibility; and performing individual selection and population updating by utilizing improved reference point generation and vertical distance measurement. The method is mainly used for improving the efficiency and effect of commercial and municipal decisions such as urban planning, medical resource configuration, energy station layout and logistics network optimization.

The invention provides a spatio-temporal index construction method, a track point query method, devices, equipment and a product, and the spatio-temporal index construction method comprises the steps: obtaining vehicle track point data, the vehicle track point data comprises the following attribute information of a vehicle track point: a track point identifier, a timestamp and a geographic position; according to the timestamps and the track point identifiers, a B-group tree index is constructed, index key information of leaf nodes in the B-group tree index comprises the timestamps and the track point identifiers, and the B-group tree index is a time index of the vehicle track points; and according to the geographic position and the track point identifier, an R-family tree index is constructed, the space entry information of the leaf node in the R-family tree index comprises the geographic position and the track point identifier, and the R-family tree index is the space index of the vehicle track point. According to the method and the device, the efficiency of querying the track points in the time dimension and / or the space dimension can be improved.

The invention relates to the technical field of electronic commerce, in particular to a personalized analysis method for cultural and creative products based on collaborative filtering, which comprises the following steps: acquiring browsing, collection and purchase behavior data of a user, calculating interval change of adjacent behaviors, and adjusting behavior influence based on browsing frequency, collection density and purchase conversion. And calculating a behavior contribution proportion in combination with the collection frequency and the stay duration, and extracting a short-term behavior trend to obtain a user behavior change trend parameter. According to the method, the behavior change rate and the time interval are combined for screening, the recommended content can quickly adapt to user interest changes, the recommendation matching degree is improved through utilization of social interaction data, social recommendation is more targeted, the scene applicability of the recommended content is enhanced through consideration of environmental factors such as geographic positions and weather, and the user experience is improved. The dynamic calculation of the multi-dimensional weight optimizes the recommendation sequence, and improves the long-term effectiveness and user experience of the recommendation system.

A system generating an environment for an operation using a set of assets includes processor(s) configured to: obtain data associated with task(s) to be performed by a set of assets, wherein: 1) the set of assets comprises semi-autonomous drones and 2) the data associated with the task(s) comprises parameter(s) pertaining to a geographic location in which at least one asset is to perform the task(s); determine a discretized representation of the geographic location, wherein the discretized representation comprises discrete elements each corresponding to a volume associated with the geographic location; annotate the discretized representation to create an annotated representation with the parameter(s) pertaining to the geographic location with a subset of the discrete elements based on a determination that the parameter(s) pertain to the geographic location; determine a plan to perform the task(s), wherein the plan is based on the annotated representation; and cause the task(s) to be performed.

Described herein are techniques and mechanisms for geographic routing. A database system may store data records corresponding with user accounts and including historical routing information characterizing geographic routes determined in association with the user accounts. A communication interface may receive a request from a remote computing device authenticated to a user account and identifying an initial geographic location and a terminal geographic location. A geographic routing engine may determine a route including turn-by-turn instructions for moving from the initial geographic location to the terminal geographic location. A generative language model interface may complete a navigation prompt to include novel text identifying supplemental route information. A user interface generation interface may transmit an instruction to the remote computing device to present a user interface that includes the turn-by-turn instructions and some or all of the supplemental route information.

An online system receives a request to access an interactive geographical map of sources from a client device associated with a user. The system retrieves data describing a geographical location associated with the user. The system identifies one or more sources within a threshold distance of the location and retrieves data including information describing items available at each source. For each source, the system accesses and applies a machine-learning model to predict a user engagement score indicating a likelihood of one or more interactions by the user with a set of items available at the source if the source is included in the map. Based on the score for each source, the system selects a set of sources and generates the map, in which the map indicates the geographical location of each selected source. The map is then sent to the client device, causing the device to display the map.

The invention relates to the technical field of geographic knowledge, in particular to a geographic spatial data knowledge graph construction method and system based on geographic element classification. Performing fine-grained hierarchical division on the first-level classifications of the geographic elements according to geographic positions and spatial distribution in the first-level classifications of the geographic elements to obtain sub-classifications of the geographic elements in the first-level classifications of the geographic elements; constructing a geographic element knowledge ontology library according to each geographic element subclass; extracting thematic geographic entities, thematic geographic entity relationships and thematic geographic entity attributes based on the geographic element knowledge ontology library, constructing a thematic geographic space knowledge triple, and storing the thematic geographic space knowledge triple into a Neo4j graph database to form a thematic geographic element data knowledge graph, the geographic space data can be retrieved and queried by utilizing the knowledge graph. According to the method, geographic space knowledge can be fully utilized to realize conversion from geographic space data to knowledge data, and dynamic retrieval and query of geographic space objects are realized.

Systems and methods are provided to select a set of candidate listings having geographic locations within a geographical area, fit a bound for a maps viewport to the set of candidate listings, generate a maximum score for the set of candidate listings based on a booking probability for each listing, a distance of the listing location from a center of the bound for the maps viewport, and visibility based on other listings. The systems and methods further optimize the listings shown in the maps viewport by removing and replacing farthest listings up to a predefined number of listings to be removed and computing a cumulative booking score for each set of listings to compare to the maximum score. The systems and methods cause display in a maps viewport in a user interface of a computing device of a set of listings that has a maximum score.

The invention is suitable for the technical field of privacy data processing, and provides a privacy grading and sharing control method for tourist travel itineraries, and the method comprises the steps: obtaining travel itinerary data of tourists; dividing the travel data into at least three basic privacy levels based on a preset region sensitivity classification rule, a user identity classification rule and an equipment type classification rule; in the basic privacy level, performing fine-grained sub-level division on the data according to interval division of travel duration, classification of activity risk levels and a historical sharing frequency threshold; based on the basic privacy level and the fine-grained sub-level, geographic position fuzzification and user identity anonymization processing are carried out on the travel data of the high-sensitivity level, and the access range of a shared object is limited through permission grading; and the sensitivity of the fine-grained sub-level is adjusted according to the real-time sharing frequency, and the sharing permission is updated, so that the accurate balance of the travel itinerary data between privacy protection and sharing effectiveness can be realized.

In one embodiment, a method includes a computing system collecting first sensor data, of a particular geographic location, from a first type of sensor. The computing system may process the first sensor data to identify one or more first objects at the particular geographic location. The computing system may access an existing high-definition (HD) map associated with the particular geographic location. The existing HD map includes one or more second objects and is generating using second sensor data collected with a second type of sensor. The computing system may determine whether the one or more first objects are included in the existing HD map. In response to determining that the one or more first objects are not included in the existing HD map, the computing system may update the existing HD map to generate an updated HD map that includes the first objects and the second objects.

The invention discloses a geographic position identification method of a streetscape image and a model training method and device.The training method is used for training a multi-modal model based on comparative learning and comprises the steps that the model is used for obtaining image feature vectors of streetscape image samples in an image sample set of a geographic area; obtaining text feature vectors of streetscape image sample text tags of a plurality of geographic areas in the tag sample set by using the model; combining the text feature vectors and the streetscape fusion features by using a model to obtain multi-modal fusion features of a plurality of geographic areas; acquiring the similarity between the image feature vector and the multi-modal fusion features of the plurality of geographic areas by using the model; and performing loss calculation according to the similarity and the geographic region label of the streetscape image sample, and adjusting model parameters according to a loss calculation result. The technical scheme provided by the invention is beneficial to improving the training efficiency of the model, enriching the implementation modes of geographic position recognition and improving the accuracy of geographic position recognition.

An interactive platform for researching and analyzing a set of topics to elicit opinions and choices via a user device. The interactive platform creates one user profile based on a unique identification of a first user. The interactive platform presents the set of topics to the first user and receives selections of a set of responses or choices corresponding to the set of topics that are processed, segregated, and stored in real time. Furthermore, the interactive platform enables reception of a user response for the set of topics based on own analysis of the first user. Moreover, the selections are limited to a daily number of opinions. The set of responses may be quantified and presented to a plurality of users registered on the interactive platform. Furthermore, the interactive platform enables segregation or categorization of the set of responses based on, for example, age, geographical location, and other categories.

The invention discloses a user geographic position positioning method and device, terminal equipment and a storage medium, and the method comprises the steps: obtaining target social data of a social user, and the social data at least comprises target latitude and longitude and target user text data; according to a pre-established geographic position prediction model, geographic position information of a social user corresponding to the target social data is determined, and the pre-established geographic position prediction model is used for processing sample data, determining a multi-dimensional user relation graph corresponding to the sample data, and predicting the geographic position of the social user according to the multi-dimensional user relation graph. A multi-dimensional user relation graph is adopted to train a multi-scale feature fusion model based on a graph attention network, and a social network graph and a position association graph are constructed through the social relation of users and hidden position correlation; processing through the proposed multi-scale feature fusion model to obtain the overall representation of the user; the position of the user is deduced through the user positioning classifier, and the accuracy and efficiency of user position prediction are improved.

The invention relates to the technical field of data processing, and discloses an unmanned aerial vehicle photo and video management method and system based on a geographic position. The method comprises the following steps: extracting geographic attribute data from an unmanned aerial vehicle photo EXIF and video subtitles; establishing a spatial database, storing photos as a point graph layer, and storing videos as a line graph layer; renaming the file according to the shooting time and the camera model; importing the point-line graph layer into GIS software to generate a visual graph; searching and screening target area media through spatial analysis; and performing statistical analysis on the media set to generate a comprehensive report. According to the method, unmanned aerial vehicle photo and video data can be managed at the same time, geographic position information is fully utilized, multi-dimensional space retrieval is supported, and the method is suitable for various application scenes, so that the complexity and errors of manual arrangement are eliminated, and the management efficiency and retrieval precision of unmanned aerial vehicle media data are improved.

The invention discloses a traffic accident risk determination method and device, electronic equipment and a storage medium, and belongs to the technical field of intelligent traffic. In the method, a specified geographic area is divided into a plurality of grids, traffic data of the specified geographic area in past T time periods are acquired, and the risk of a traffic accident is determined based on the traffic data in the T time periods; the method comprises the steps of generating T parts of graph structure data and T parts of grid structure data, enabling any one piece of graph structure data to represent the dependency relationship of traffic accidents on geographic semantics, enabling any one piece of grid structure data to represent the dependency relationship of the traffic accidents on geographic positions, then analyzing the spatial-temporal correlation of the traffic accidents on geographic semantics based on the T parts of graph structure data, and obtaining the spatial-temporal correlation of the traffic accidents on geographic semantics. Based on the T grid structure data, the time-space relevance of the traffic accident in the geographic position is analyzed, and the traffic accident risk value of each grid in the (T + 1) th time period is determined by integrating the analysis results of the T grid structure data and the time-space relevance, so that a traffic accident prediction scheme is provided.

The invention provides a positioning method, device and system based on a visual image and a storage medium, and belongs to the technical field of computer vision. The method comprises the following steps: acquiring earth surface feature information based on a to-be-positioned image acquired by observing a to-be-positioned area by a user terminal; matching a contour line corresponding to the earth surface feature information and geographic position information of each contour point on the contour line from an earth surface form library; and determining the pose information of the user terminal in the geodetic coordinate system based on the pixel position information of the target contour point in the to-be-positioned image and the geographic position information of the target contour point. According to the invention, the earth surface image and form information when the to-be-positioned area is the satellite navigation denial area can be rapidly obtained by using space remote sensing, and the information is matched with the earth surface image, so that positioning efficiency and precision are taken into account while positioning and orienting are carried out in the satellite navigation denial area for individuals, unmanned aerial vehicles or light carriers.

A computer implemented method includes: obtaining a plurality of predictive data, each predictive data indicative of respective predictive values of a characteristic corresponding to geographic locations at a worksite; obtaining in-situ data indicative of in-situ values of the characteristic corresponding to the geographic locations at the worksite; determining a respective accuracy of each predictive data based on the respective predictive values of the characteristic and the in-situ values of the characteristic; identifying, based on the respective accuracy of each predictive data, a set of qualified predictive data comprising two or more of the predictive data; determining whether a selection condition is present at the worksite; selecting one qualified predictive data, of the set of qualified predictive data, as selected qualified predictive data based on the determination of whether the selection condition is present at the worksite; and controlling a mobile work machine based on the selected qualified predictive data.

The invention provides a data compliance migration method which comprises the following steps: acquiring data protection regulation change information through a regulation monitoring module, extracting key terms and geographic position parameters, and generating a compliance parameter set; triggering data classification identification according to the regulation change information, analyzing content features and sensitive levels of stored data, and determining risk classification of data blocks; distributing the data blocks to different transmission queues according to the risk classification, and generating a data migration task list; dynamically scheduling a data migration time window and a transmission quantity according to the risk classification and the optimal migration path; starting a parallel data transmission process, and executing a data migration operation; carrying out integrity check on the transmission data through a check algorithm, and confirming a transmission state; and the monitoring module is used for detecting service response time in the migration process and adjusting the migration progress and the switching opportunity.

The invention discloses a post recommendation method and device, equipment, a storage medium and a program product. The method comprises the following steps: in response to a client login request of a user, obtaining real-time geographic position information of a job application client; screening out at least one first-class aging recruitment enterprise of which the regional information is matched with the real-time geographic position information in the aging recruitment order metadata set which is maintained in real time; filling the description information of each first-class aging recruitment enterprise into a recommendation page, and displaying the recommendation page; and in response to a check ending request of the user for the recommended page, normally opening a conventional function interface of the job application client to provide a job application service for the user. According to the technical scheme of the embodiment of the invention, before a conventional job hunting function is provided for the user, a batch of recruitment enterprises matched with the real-time geographic position information of the user can be screened out for advanced recommendation for the user, so that the workload of brokers is greatly reduced, and meanwhile, the in-job achievement rate of members can be effectively guaranteed.