253 results about "Geographic site" patented technology

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 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.

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.

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.

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 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.

In some embodiments, a method for training a machine learning device includes: ascertaining geographic location information of at least one portion of a first image associated with a label; associating with the label a second image including at least a portion having substantially the same geographic location information as the at least one portion of the first image; optional alignment or coregistration of the first and second image to maximize mutual information overlap; forming a training dataset comprising the first and second images as input images and the label that the first and second images are associated with as outputs; optional binary categorization and curation of the resulting training dataset to ensure accuracy; and training the machine learning model using the augmented dataset.

The invention discloses an output optimization method, system and device under complementary scheduling and a medium. The method comprises the following steps: acquiring data of cascade hydropower, a wind field and a photoelectric field; a graph neural network is constructed based on the geographic position data, the weight of an edge is configured according to historical power generation data, and nodes of the graph neural network represent fans, photovoltaic arrays and hydropower stations at different geographic positions; carrying out meteorological prediction according to the current short-term meteorological data based on the constructed graph neural network; and constructing an evaluation model based on the double-layer Monte Carlo-conditional risk, outputting a probability density function of output prediction according to the evaluation model, and executing output optimization. According to the method, the propagation condition of possible meteorological elements in the non-uniform observation network is captured by establishing the graph neural network; and comprehensive evaluation of water, wind and light is realized by constructing an evaluation model, and a reference direction of short-term complementary output optimization is given through a probability density function, so that the scheduling effect of complementary optimization is improved.

The invention discloses a sample sending process monitoring system fusing image recognition and geographical location information, comprising a multi-source information acquisition module for acquiring image information around a sample and geographical location information of the sample in a sample sending process; the sample sending abnormal behavior recognition module based on image recognition is used for detecting pedestrian abnormal behaviors, camera abnormal shielding and camera angle abnormal adjustment in a sample area according to the image information; the sample sending abnormal behavior recognition module based on the geographic position information is used for extracting space-time trajectory characteristics of the sample according to the geographic position information of the sample and detecting a time abnormal trajectory, a space abnormal trajectory and a space-time abnormal trajectory according to the space-time trajectory characteristics; and the early warning module is used for generating an abnormal behavior signal or a non-abnormal signal according to the detection result of the sample sending abnormal behavior and the abnormal track behavior, and sending early warning information according to the abnormal behavior signal. The method has the advantages of small algorithm size, easy migration, low cost and the like, and can improve the user experience.

The invention discloses a social relation chain value evaluation method and system based on multi-dimensional data modeling, and the method comprises the steps: integrating a social platform API, a user behavior log, geographic position data and equipment information through a data collection module, carrying out the cleaning and standardization of a preprocessing module, dividing a geographic region through a space-time modeling module based on K-means clustering, and carrying out the calculation of the value of a social relation chain. An exponential decay function is introduced to dynamically update an interaction weight, an emotion analysis module adopts a BERT model to carry out emotion classification on comments, a role classification module marks community roles through a rule engine, and finally a value calculation module fuses feature parameters of data of all dimensions to construct a propagation value evaluation model. According to the method and the system, the propagation value evaluation accuracy is remarkably improved, the misjudgment rate is greatly reduced, the social e-commerce propagator screening efficiency, the local life service precise popularization coverage rate and the brand propagation positive word-of-mouth recognition accuracy are improved, and scientific decision support is provided for social fission marketing.

The invention discloses a dynamic distributed scanning method and system based on an IPv6 geographic tag, and relates to the technical field of the Internet, and the method comprises the steps: carrying out the region division of an IPv6 seed address through combining with geographic information, obtaining the IPv6 seed addresses of a plurality of geographic regions, constructing an address space tree of each geographic region, determining the change dimension of the address space tree, and carrying out the calculation of the change dimension of the address space tree; generating candidate sub-modes based on the change dimension, and selecting a sub-mode from the candidate sub-modes; generating an address according to the sub-mode, and further obtaining a target address; performing comprehensive evaluation on each sub-mode region based on the seed address density and the network development condition to obtain an initial score, and scanning a target address in each sub-mode region according to the initial score; in the scanning process, the initial score is updated by adopting a score updating mechanism, and scanning is continued based on the updated score. Geographic positions and mechanisms based on IPv6 seed addresses are fused, so that the number of real active addresses is hit to the maximum extent under a limited scanning budget, and the detection efficiency is improved.

The invention provides a method and system for improving the timeliness rate of sample inspection, and relates to the technical field of sample processing. The method comprises the steps of collecting an identity number and a real-time task node number, recording a log after comparison succeeds, recording deviation and generating a compliance identifier if comparison fails, checking a space permission according to the identifier and updating a handover permission, if a specimen is in a warehouse-out state and the permission is effective, updating the specimen to be in transportation and generating a signature chain entry, and sending the signature chain entry to a server; and if the path is abnormal, locking the transportation state and re-planning the path, and generating a handover trigger instruction. According to the invention, through real-time matching of the identity of the collector and the task node and combination of code scanning time recording, accurate control of the operation process is realized, human errors in the specimen processing process are avoided, the concept of spatial authority and the beacon technology are introduced to ensure the accuracy of the geographic position of specimen handover, and the security and traceability are enhanced. The response speed and the processing flexibility are also improved, and the timeliness and the accuracy of specimen inspection are remarkably improved.

The invention discloses an intelligent two-dimensional code inspection method, an intelligent two-dimensional code inspection device and intelligent two-dimensional code inspection equipment for a survey mark, and a computer readable storage medium. The method comprises the following steps: generating two-dimensional code image data based on acquired benchmark information; wherein the benchmark information comprises a serial number, a roll call, a type, a grade, a geographic position, a supervision unit, a maintenance unit and a supervision telephone; scanning a two-dimensional code mark arranged on the top surface of the corresponding benchmark protection disc through a mobile terminal to obtain two-dimensional code image data; wherein the two-dimensional code mark corresponds to the two-dimensional code image data; obtaining the benchmark information according to the two-dimensional code image data, and displaying the benchmark information based on a page format; acquiring input inspection data through the mobile terminal; and performing inspection early warning processing based on the inspection data. The inspection efficiency of the survey mark is improved, and the labor cost is reduced.

The invention provides a meter reading path planning method and system based on multi-target constraint, and relates to the technical field of meter reading path planning, and the method comprises the steps: obtaining a to-be-read meter task set, and extracting historical state data of a geographic position and an associated metering device as feature data; predicting the predicted operation duration of each meter reading task according to the feature data; performing spatial clustering division on the task set to be subjected to meter reading through an improved watershed algorithm to form a plurality of task clusters; taking minimization of the total driving distance and the total prediction operation duration as optimization targets, performing initial path planning, and generating an initial operation sequence of each task cluster; and executing the initial job sequence, calculating the deviation between the actual job duration and the predicted job duration, and re-performing path planning on the meter reading tasks which are not executed subsequently to generate an updated job sequence. The technical problems of task allocation imbalance, path static solidification and poor multi-target collaboration in meter reading path planning in the prior art are solved.

The invention discloses a remote sensing image retrieval method and device, electronic equipment and a medium. The method comprises the steps that a remote sensing image retrieval request is acquired; analyzing the retrieval request through the target large model to obtain an initial retrieval condition; according to the initial retrieval condition and a pre-constructed interest point database, determining a target geo-fence retrieved by the current image; and based on the initial retrieval condition and the target geo-fence, performing retrieval in a remote sensing image database to obtain a target remote sensing image. Therefore, retrieval request analysis of complex geographic description and fuzzy text description is realized through the target large model, so that the remote sensing image retrieval intention of a user is accurately understood, and meanwhile, an accurate target geographic fence is obtained in combination with the pre-constructed interest point database, remote sensing retrieval is locked in a more accurate geographic position range, and the remote sensing retrieval accuracy is improved. Therefore, the retrieval precision of the target remote sensing image is improved.

The invention provides an enterprise intelligent early warning method based on an artificial intelligence model, and the method comprises the steps: extracting the spatial-temporal trajectory features of a target product in combination with a circulation data set, recognizing a circulation time interval, carrying out the mapping of geographic position information and the time interval through a geographic information system, and generating a spatial-temporal feature matrix of product circulation; grading the abnormal product circulation by combining the abnormal geographic position deviation value, the dispersion index corresponding to the dispersion degree, the product batch scale, the arrival time and the network site scale; according to different levels of abnormal risks, sending an early warning signal to a management platform, and determining early warning triggering time and an object; according to the early warning signal triggering condition, generating an abnormal intervention adjustment scheme, monitoring a product circulation track, and obtaining track change data after intervention; and updating the spatial-temporal characteristic matrix according to the trajectory change data, and re-inputting the data into the deviation detection and dispersion degree analysis process through a cyclic feedback mechanism to obtain a new anomaly recognition result.

Techniques for obtaining digital transaction data including transaction geolocation information associated with a real-world geolocation. The techniques further including generating a transaction geolocation index as a function of the transaction geolocation information. The techniques further including accessing an indexed notarized ledger stored in the at least one memory from the plurality of notarized ledgers where the geographic location index corresponding to the indexed notarized ledger satisfies a query based on the transaction geolocation index. The techniques further including instantiating a transaction record memorializing the digital transaction data with respect to the real-world geolocation. The techniques further including instantiating a ledger transaction adhering to a format of the indexed notarized ledger based on the transaction record. The techniques further including recording the ledger transaction representing the transaction record on the indexed notarized ledger in the at least one memory.

A method may comprise storing a first service provider record associated with a first project located at a first geographic location, receiving a request for project identifiers located within a section of a geographic area, providing a subset of the first set of the one or more project identifiers to be displayed on a second map the first user device, receiving a selected project of the project identifiers, providing a project page indicating categorical identifiers associated with the first project indicating at least some work performed, a link to at least one service professional's profile page, an opinion review and an insight review, receiving a selection of the link to the at least one service professional's profile page, and providing, a profile page of the at least one service professional, the profile page including contact information of the at least one service professional.

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 relates to the technical field of geographic information processing, in particular to a field proof file information encryption tamper-proof method of a land change investigation technology, which comprises the following steps: using authorization authentication, and initializing a camera; acquiring attitude information of the equipment when the investigator takes a picture, and calculating a direction angle of the picture by combining with geographic position information of the equipment; the positioning map is integrated into the shot picture, and watermarking is carried out on the shot picture; writing the required geographic metadata into an image file of a shot picture, and encoding and packaging according to a standard format; according to the method, the technical requirements of all links are packaged into the SDK, it is guaranteed that the proof file meets the requirements, it is guaranteed that the data of the proof file is encrypted and safely transmitted, operation is convenient and fast, quality is controllable, and the method is easy to implement and popularize. And the land change investigation business field work proof efficiency is improved by more than 40%.

This application discloses a method, apparatus, electronic device, and medium for retrieving remote sensing images. The method includes: acquiring a retrieval request for remote sensing images; parsing the retrieval request using a target big data model to obtain initial retrieval conditions; determining the target geofence for the current image retrieval based on the initial retrieval conditions and a pre-constructed point-of-interest (POI) database; and performing a search in the remote sensing image database based on the initial retrieval conditions and the target geofence to obtain the target remote sensing image. Thus, by using a target big data model, retrieval requests with complex geographical descriptions and ambiguous textual descriptions can be parsed, thereby accurately understanding the user's remote sensing image retrieval intent. Simultaneously, by combining this with a pre-constructed POI database, a precise target geofence can be obtained, locking the remote sensing retrieval within a more accurate geographical location range, thereby improving the retrieval accuracy of the target remote sensing image.

The application discloses a kind of based on multi-source data fusion's catering intelligent decision-making method and system, it belongs to site selection decision-making technical field, by using big language model to carry out knowledge extraction to multi-source data, and to this construction catering site selection knowledge graph, based on knowledge graph automatically calculates geographic position index, traffic accessibility index, consumption potential index and the objective weight of competitive environment index, simultaneously using big language model to the qualitative description of the region to be selected is retrieved to obtain membership vector, according to objective weight and membership vector calculation comprehensive suitability degree score, the recommended site selection region is obtained by ordering comprehensive suitability degree score, it quantifies index weight by catering site selection knowledge graph, avoids subjective dependence on expert experience, quantifies index using big language model, significantly improves the accuracy and efficiency of catering site selection, adapts to large-scale multi-source heterogeneous data scene, and in the face of dynamic factors can respond to update in time, convenient for application and promotion.

A location-based safety alert system can gather data describing potential health- and safety-related issues at various geographic locations (e.g., crime statistics, disease spread rates, weather reports, and travel advisories). The location-based safety alert system can develop models that characterize how dangerous a location is based on the data describing it. The location-based safety alert system can apply the model, as circumstances at a location change, to compute danger scores that reflect how dangerous the location is at that time. Using the danger scores, the location-based safety alert system can alert users of dangers present in areas of interest to them (e.g., where they will be traveling to soon, where they have family members living, or where they are presently located). The alerts can notify users of the risk present at a geographic location as well as advise them of services and resources available to mitigate the risk.

The invention provides a multi-mode sensing inspection method based on terminal equipment. The multi-mode sensing inspection method comprises the following steps: collecting video data, audio data, geographic position data and IMU (Inertial Measurement Unit) data; video frames are extracted based on language trigger thinning, pose trigger thinning and visual trigger thinning; and finally, identifying hidden dangers based on the extracted video frames. According to the method, significant thinning processing of the video frames is realized through various kinds of perception information, the input load of the large model is greatly reduced on the premise that key semantic information is not missed, the problems of frame input limitation and low analysis efficiency of the multi-mode large model in analysis of the long-time industrial inspection video are solved, and the method is suitable for large-scale industrial inspection. Therefore, the efficiency and accuracy of large model analysis are improved. And the frame extraction process does not depend on a fixed frame rate, but is based on semantic driving of human behaviors and equipment states, so that the extracted key frame is more effective.

The invention relates to a signature processing method based on intelligent character recognition, which comprises the following steps: acquiring the page height of a file, and converting the file into a reference coordinate system according to the page height; automatically identifying key fields in the file; determining an initial signature area corresponding to the key field through an edge detection algorithm; through a template matching algorithm or a preset model, searching a region matched with the template in the file or determining a region output by the model, and determining a signature position; fusing the initial signature area with the signature position, and determining a target signature position; acquiring a timestamp, a geographic position and equipment information for performing signature operation at the target signature position; inputting the timestamp, the geographic position and the equipment information into a preset behavior model to obtain an abnormal behavior probability; and according to the abnormal behavior probability, determining whether to give an abnormal alarm.

The invention discloses a similar event judgment method and device based on geographic position information conversion and a medium, belongs to the technical field of computer software, and aims to solve the technical problem of how to realize flexible and accurate similar event judgment and meet the requirements of different service scenes. According to the technical scheme, one or more judgment modes of geographic position conversion coordinate comparison, geographic position coordinate direct comparison, keyword comparison and completely equal comparison are selected, weight scores are configured for the selected judgment modes respectively, and the weight scores are used for indicating the importance degree of different judgment modes in final similar event judgment; and comprehensively analyzing the selected judgment mode, judging whether the events are similar events or not through weighted scores according to the configured geographical location distance and threshold value, feeding back the judgment result of the similar events to a user, and carrying out batch operation on the events by the user according to the feedback result, and checking the details of the events in detail for further processing.