190 results about "Data grid" patented technology

The invention relates to the technical field of data visualization, in particular to an earthquake emergency information rapid visualization method and system. The method comprises the following steps: acquiring earthquake monitoring real-time data; based on earthquake monitoring real-time data grid division, earthquake region population density distribution and key facility positions are generated, and an earthquake region sensitivity matrix is generated; dynamically simulating a seismic wave propagation process based on the seismic monitoring real-time data and the seismic region sensitivity matrix, and generating fluctuation propagation time sequence data; and identifying epicenter topography and landform vector data of the earthquake monitoring real-time data, and respectively evaluating topographic relief and geological stability to obtain earthquake topographic relief index data and earthquake geological stability score data. According to the invention, rapid and accurate assessment and visualization of earthquake damage distribution are realized through a data visualization technology, so that the earthquake emergency response efficiency and the disaster rescue decision scientificity are improved.

The invention provides a running state monitoring method and monitoring platform for an intelligent coffee machine, and relates to the technical field of running state monitoring, and the method comprises the steps: connecting a built-in sensor of the coffee machine, and obtaining a self-sensing state parameter; acquiring external monitoring data through external monitoring equipment of the coffee machine; performing internal data grid mapping according to the self-sensing state parameters, and constructing an internal sensing data network; performing alignment segmentation on external monitoring data, and establishing internal and external response data pairs; operating state recognition is conducted, an operating state recognition result is obtained, and coffee machine regulation and control feedback is conducted. The technical problems that in the prior art, due to the fact that operation state monitoring mostly adopts single-point data collection or passive alarm, the timeliness of state monitoring is weak, and the user experience and the service life of the coffee machine are affected are solved, intelligent recognition and regulation and control feedback of the operation state of the coffee machine are achieved by combining external operation monitoring with self-inspection parameters, and the user experience is improved. And the operation efficiency of the coffee machine is improved.

The invention discloses an AI marketing advertisement putting optimization system and method fusing multi-dimensional data, and relates to the technical field of data processing, and the system comprises a historical record obtaining module which extracts the historical putting record of a target optimization block; the terminal data interaction module interacts with the advertisement putting management platform based on the historical putting record to obtain multi-dimensional terminal data; a grid division module performs grid division on the target optimization block to generate a putting grid and time sequence label data; the mapping model construction module constructs a label mapping model based on the grid time sequence label data, the historical delivery record and the multi-dimensional terminal data; the advertisement task processing module generates an advertisement label cluster by using a label mapping model according to the advertisement task information; and the putting scheme optimization module realizes the optimal matching of the advertisement task and the label cluster through a multi-objective optimization algorithm, and outputs an advertisement putting scheme, thereby achieving the technical effects of improving the data utilization rate, providing predictive putting optimization and improving the putting income.

The invention relates to the technical field of data assimilation, and discloses a data assimilation method, device, equipment and medium, the method comprises the following steps: firstly obtaining observation data and meshing, the observation data comprising at least one variable; or, a background field of at least one time and corresponding observation data are obtained, the observation data are gridded, and the background field and the observation data both comprise at least one variable; next, the constructed data assimilation model is trained by using the grids corresponding to all the variables to obtain a trained data assimilation model; and inputting the to-be-processed gridding observation data or the to-be-processed background field and the gridding observation data into the trained data assimilation model, and outputting a corresponding analysis field. The data assimilation method, device, equipment and medium provided by the invention have the characteristics of high reasoning speed, high assimilation precision and the like, and are suitable for data assimilation in the fields of weather climate, ocean, land surface and the like.

The invention provides a typhoon intensity evaluation method and system, electronic equipment and a storage medium. The typhoon intensity evaluation method comprises the steps that a satellite data set is acquired; the satellite data set comprises brightness temperature data and latitude and longitude data of a plurality of data grid points; determining a plurality of data grid points in the typhoon calculation area to obtain position information of a typhoon center point; related data grid points are intercepted in the satellite data set, and the typhoon calculation area is divided into a plurality of concentric circular ring areas based on the maximum value of the distance between the typhoon center point and the related data grid points; calculating typhoon intensity evaluation parameters of each concentric annulus region; and taking the brightness temperature data of the related data grid points, the position information of the typhoon center point and the typhoon intensity evaluation parameters as current analysis data to obtain an evaluation result of the typhoon intensity. According to the method, the typhoon intensity can be continuously evaluated in real time without being limited by terrains, traffic and human activities, remote evaluation of the typhoon intensity is achieved, and higher safety is achieved.

The invention relates to an artificial precipitation enhancement operation area identification method and system based on multi-source data, and relates to the technical field of meteorological intervention operation, and the method comprises the steps: building a multi-resolution dynamic data grid system, and enabling a coarse-grained grid layer to cover the whole operation area, and to be used for bearing the macro data of a satellite cloud picture and a conventional radar; the fineness grid layer is used for receiving and mapping real-time data provided by the high-resolution radar; receiving real-time data of all cloud blocks, mapping the real-time data to corresponding grid layers, and projecting the data collected at different time points to a unified time reference frame to obtain a cloud system state view; predictive interpolation is carried out by using the latest data of the conventional radar and the macroscopic trend of the satellite cloud picture in combination with the motion vector and confidence weighting so as to obtain cloud system information; and forming a visual cloud system three-dimensional view, identifying and tracking a target cloud block with an artificial precipitation enhancement potential, and generating an operation instruction. The method has the effect that the target cloud block with the operation value can be identified and tracked to generate the accurate operation instruction.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium for encoding input data comprising input data values corresponding to respective input data grid points of an input data grid, such as image, video or audio data.

The invention relates to the field of ocean current remote sensing, and relates to a vector flow inversion method combining a single-station ground wave radar and a satellite-borne SAR, and the method mainly comprises the steps: calculating the frequency deviation of a first-order Bragg peak of the ground wave radar, carrying out the inversion of the sea surface radial flow of the ground wave radar, and carrying out the inversion of the sea surface radial flow of the SAR through employing a Doppler centroid anomaly method; interpolating a ground wave radar radial flow result to an SAR data grid through bilinear interpolation; inverting a single-station vector flow based on a ground wave radar radial flow result, projecting single-station vector flow data with high confidence coefficient to an SAR range direction, calculating a difference mean value of a projection flow velocity and an SAR radial flow velocity, and further calibrating the SAR radial flow; and combining a ground wave radar radial flow result with the calibrated SAR radial flow to invert a vector flow. According to the method, the defect of ocean current observation through a single means is overcome, high-precision inversion of the combined vector flow is achieved, and the method has important significance on ocean environment monitoring, disaster forecasting, shipping safety and the like.

A system and method for combining data from disparate business intelligence systems and data sources. The method includes aggregating data in real-time across multiple, disparate data platforms of more than one third party, by mapping nonmatching data parameters used in the different platforms to a common data field. The business intelligence systems are queried to identify responsive data fields, which are then meshed in a translation and / or unification module into the common data field for display. The meshing of the data allows for efficient filtering according to user inputs. The system and method further include applications to allow users to create parameter mappings for the data meshing.

The present invention discloses an unified multiple access (MA) based system for uplink transmission of data by multiple users. The system comprises an user interface integrated transmitter modules for transmitting the data from multiple user transmitters over waveforms through a cooperative unified data grid structure including grid points, said unified data grid structure including each user transmitter allocation of a few non-overlapping grid points for loading respective data bearing symbols, with zeros loaded onto unallocated grid points. The user transmitter is configured to transmit a sparsely loaded grid resembling to the unified two-dimensional data grid structure involving data-bearing Quadrature Amplitude Modulation (QAM), where a part of available grid points of the grid as allocated is loaded with QAM symbols and remaining grid points are loaded with zero symbols. A waveform modulator corresponding to user transmitter is also provided in the present system for waveform modulation of said sparsely loaded grid as per the waveforms enabling transmission for multi-antenna reception of the waveforms to a base station or an access point.

The invention relates to the technical field of hydraulic fracturing, in particular to a coal and rock mass hydraulic fracturing effect evaluation method based on micro-seismic monitoring, which comprises the following steps of engineering geology investigation and survey, and fracturing data collection, screening and processing. Calculating the theoretical fracturing volume Vr of the coal and rock mass; calculating an actual fracturing volume Vf based on an octree; calculating a hydraulic fracturing fracture volume ratio K, and evaluating the integral fracturing effect of hydraulic fracturing; evaluating a fracturing crack expansion range based on the micro-seismic frequency nuclear density; the fracturing crack propagation strength is evaluated based on the micro-seismic energy nuclear density; and local reinforcement pressure relief is carried out on the area with insufficient fracturing. According to the method, the octree is used for calculating the fracturing volume, errors caused by non-response areas of micro-seismic events are effectively removed, and the requirement for large-scale data gridding volume calculation generated by fracturing can be met.

A system for event-driven distributed data network analysis, the system includes: a multitude of domain data nodes, each comprising a stream storage, a multitude of transformation pods, and a product API, with each domain data node ingesting heterogeneous event streams, validating schema compliance, performing enrichments, and making data products available under versioned schema contracts; each domain data node further comprises a hardware-based edge intelligence appliance comprising an enclosure, a compute module with heterogeneous processing units selected from CPUs, GPUs, and TPUs, a secure enclave module for confidential execution of transformation code on encrypted data, a protocol-structured stream storage medium supporting multi-level retention, and industrial I / O interfaces configured for direct interaction with sensors, programmable logic controllers, and cloud-native services; an event mesh backbone processor configured to connect the multitude of domain data nodes via a publish-subscribe architecture, with the backbone guaranteeing exactly one-time delivery, partition-level sorting, and geo-replicated durability; a Contextual Intelligence Engine coupled with the Event Mesh Backbone processor, the engine comprising a semantic graph memory and a Streaming Graph Reasoner configured to map raw events into an ontology, perform graph joins in real time, and recognize composite causal patterns across multiple domain data nodes; a governance and policy control unit integrated into both the data and control layers. This layer enforces zero-trust security, role-based access control, real-time provenance tracking, and regulatory compliance; and An actuation interface coupled with the contextual intelligence engine and the governance layer. The actuation interface is configured to generate control commands for operational technology devices and digital workflows, thus closing the loop from data acquisition to autonomous decision-making.

The invention relates to the technical field of electric digital data processing, and discloses a 3D intelligent stocktaking method and device, and the device comprises a 4D millimeter wave radar disposed at the top of a stock bin, S1, obtaining the data of a corresponding coverage area detected by the 4D millimeter wave radar; s2, preprocessing the acquired data; S3, processing the preprocessed data by a point cloud data grid filtering algorithm to obtain point cloud data on grids on a global grid map; s4, checking the integrity of the data, and if blank grids exist in the global grid map, filling the grids of the blank data in the global grid map by using a point cloud smooth interpolation algorithm to form a final smooth point cloud; and S5, reconstructing the surface of the material, and constructing a three-dimensional diagram of the surface of the material according to the final smooth point cloud determined in the step S4. Through the 4D millimeter wave radar and various algorithms, the real-time and all-around monitoring of the material bin is realized, and accurate three-dimensional material level imaging is provided.

The present application discloses a data fusion method and system based on ERA5 reanalysis data and satellite observation data, and relates to the technical field of meteorological data fusion. The method comprises: firstly converting the altitude coordinates of the reanalysis data set from air pressure values ​​to corresponding altitude values, so as to facilitate subsequent matching and fusion; then dividing the reanalysis data set after the altitude coordinate conversion into a grid model according to a preset resolution, and calculating and fusion the parameters of the reanalysis data and the observation data according to the space-time grid as a unit; for each space-time grid, firstly calculating the mean value and standard deviation of the reanalysis data of the space-time grid, and then using the satellite observation data obtained by matching, calculating the mean value and standard deviation of the observation data, and finally determining the fusion data grid model; the present application adopts satellite observation data, and through the design of a reasonable data fusion algorithm, better corrects the ERA5 reanalysis data set, which is more in line with the actual atmospheric change characteristics.

The invention discloses a seasonal frozen region salinization roadbed deformation monitoring and early warning method based on a neural network. Comprising the steps of static attribute data acquisition, dynamic monitoring data acquisition, action process data acquisition, data gridding fusion, construction and training of a first neural network model, construction and training of a second neural network model, regular monitoring and intelligent diagnosis and intelligent prediction and beforehand early warning. Data fusion is performed on spatial continuous data, investigation data, traffic load, freeze-thaw cycle and other action process data of a vertical deformation field and a salt concentration field of a roadbed, and then a serial neural network model is utilized to predict the disease type and severity of the roadbed under current and future working conditions. Full-chain intelligent analysis from multi-source data fusion, deformation prediction to disease identification is realized, the problems of monitoring fragmentation and early warning lag of a traditional method are solved, and the perception ability and the beforehand early warning level of the health state of the salinized roadbed in the seasonal frozen region are remarkably improved.

The invention provides a large model data protection method, system and equipment based on a data grid, and relates to the technical field of model data processing. The large model data protection method based on the data grid comprises the steps of S1, data classification and marking, S2, access control and authority management, S3, data encryption, S4, data desensitization, S5, data backup and recovery and S6, monitoring and auditing. Through data classification and marking, sensitive data can be accurately identified, and different protection strategies are formulated according to the sensitive degree of the sensitive data, so that undifferentiated protection on all the data is avoided, resources are saved, and meanwhile, the protection strength on the data which really needs to be protected is emphatically enhanced.

The invention provides a method, a system, equipment and a medium for realizing online viewing of an original style of an Excel file, and belongs to the technical field of online file processing, the method comprises the following steps: a front-end Web page receives the Excel file uploaded by a user, stores the Excel file in a rear-end server and records stored file information; the Excel file is read, an xlsx.js library and an excel.js library are used for analysis, and analysis results are integrated; missing cell filling and style information conversion are carried out on the analyzed Excel file, cells with merging attributes in the Excel file are marked, and a format capable of being recognized by a data grid editor is obtained; and rendering a table consistent with the style of the original Excel file on a front-end Web page based on a format which can be identified by the data grid editor. The problem that a traditional online Excel viewing tool cannot completely reserve original file style information is solved, and the user experience is improved.

The invention relates to the technical field of blood cell analysis, and particularly discloses a blood cell analysis system and method based on computer vision, which uses an image recognition and generation technology based on computer vision to carry out grid division and semantic feature extraction on blood image data. Performing global text generation and semantic coding on each blood image data grid block feature after semantic extraction so as to perform adjustment response aggregation on attention of different blood local areas in each blood image data grid block feature according to blood image text description semantic features; therefore, intelligent optimization of the blood image data is realized. In this way, the complex deep-layer mutual influence association relationship between cells can be captured, so that a more accurate diagnosis basis is provided. Meanwhile, the processing strategy can be dynamically adjusted according to the specific description content of the blood image so as to better adapt to diversified samples, and the method does not only depend on fixed preprocessing parameters.

There are provided systems and methods for dynamic data query routing for managing access to datasets having multiple versions. A service provider, such as an electronic transaction processor for digital transactions, may provide data for different applications including local device-side software applications and web-based or server-side applications. The data may be read and provided within the application, for example, for output or processing, as well as operated on in the applications to update, add to, or delete from corresponding records. When retrieving or loading data, a data quantum may be used in a data mesh to abstract database physical locations and utilize logical names that allow for applications to code and query for data without direct entanglement with databases and corresponding stored datasets for the data. A router may then be used to route requests and queries for the data to optimized databases for the data.

The invention discloses an alkaline electrolytic cell multi-physics field distribution prediction system and method based on deep learning, and in the prediction system, a multi-physics field coupling simulation module is used for obtaining unstructured multi-physics field coupling simulation data of an alkaline electrolytic cell; the grid data conversion module is used for acquiring structured grid data, geometric features and a symbol distance matrix, and constructing a data form required by a subsequent deep learning model; the deep learning training module is used for training the structured grid data through a deep convolutional neural network to generate a multi-physics field prediction model; and the prediction and visualization module is used for loading the trained model for real-time prediction and realizing visual presentation of a result. The method can be used for real-time prediction and design optimization of the running state of the alkaline electrolytic cell.

The invention relates to the technical field of geographic information systems and space computing, in particular to an amusement equipment safety risk early warning system based on big data. Comprising the following parts: a geospatial data gridding storage module, which is used for collecting multi-dimensional geographic information and space-time state information of an amusement park; the multi-dimensional geographic information refers to space coordinates and proximity relations of amusement equipment; the space-time state information refers to temperature change data in each starting and stopping process of the amusement equipment; and the geographic space correlation degree calculation module is used for calculating an accumulated risk and an instantaneous risk of the amusement equipment based on the multi-dimensional geographic information and the space-time state information. According to the method, geographic space grid storage, dynamic topological association and risk visualization technologies are fused, and intelligent safety monitoring of amusement equipment is achieved; spatial and temporal characteristics are analyzed based on a cumulative / instantaneous risk formula, the early warning capability is improved in combination with closed-loop management of a people flow thermodynamic layer, missed reports are reduced, the operation and maintenance efficiency and the equipment life are optimized, and intelligent decision making is assisted.

The invention relates to a sea surface wind wave field parameter integrated inversion method combining HFR and SAR, and the method mainly comprises the steps: extracting the positive and negative first-order echo spectrum peak values of HFR, carrying out the inversion of a sea surface wind direction, and carrying out the interpolation of an HFR wind direction result to an SAR data grid through bilinear interpolation; based on the registered HFR wind direction result, utilizing a CMOD5. N model and an SAR backscattering coefficient to invert the wind speed; constructing a wind wave spectrum based on the inverted wind speed and wind direction results; calculating a surge spectrum peak wave number, a surge spectrum peak amplitude and a surge propagation direction by using the SAR image information, and constructing a surge spectrum based on the surge spectrum peak wave number, the surge spectrum peak amplitude and the surge propagation direction; and superposing the obtained wind wave spectrum and the surge spectrum to obtain a sea wave spectrum result, and further inverting the significant wave height. According to the method, the defect of sea state parameter observation through a single means is overcome, integrated high-precision inversion of the wind wave parameters is achieved, and the method has important significance on marine environment monitoring, disaster forecasting, shipping safety and the like.

The invention relates to the technical field of atmospheric environment risk early warning, in particular to an atmospheric environment simulation diffusion method and system based on GIS and virtual reality. When atmospheric environment simulation diffusion is simulated, multi-source data used for atmospheric simulation diffusion simulation is firstly obtained, then data processing is carried out on the multi-source data, and the atmospheric environment risk early warning is carried out. In the data processing step, when the atmospheric environment simulation diffusion of the pollution source is simulated, the resolution of the geographic grid and the resolution of the pollution source data grid are connected, so that the information loss caused by data mismatching in the data fusion process can be reduced, and the reliability of the atmospheric environment simulation diffusion result is improved.

A wireless communication system for enhanced reliability of wireless communication and reducing peak power in wireless data transmission across different waveforms comprising transmitter modules coupled to waveform modulators including waveform two-dimensional resource or data grids representative of a signal processing domain for transmitting data bit bearing symbols across varied waveforms under controlled sparsely / partially loading of fewer modulated data symbols of the available grid points of a larger two-dimensional resource or data grid for transmission as spaced fewer data symbols with loading zero symbols at remaining empty grid points. The modulated data symbols under controlled sparsely / partially loading including said fewer modulated data symbols being allocated in the resource or data grid and distanced there between based on a factor for partial loading and full number of symbols accommodable in the resource or data grid to reduce cross interference amongst symbols and minimize error rate.

Systems and methods for real-time data integration, analysis, and notification within a mobile application system are provided. Embodiments include initializing a data layer and a pre-processing phase to store structured and unstructured data with a distributed database policy. A real-time data grid (RTDM) continuously extracts data from various platforms using signal processing methods and machine learning techniques for noise removal and data feature extraction. An advanced analysis and machine learning (AAML) engine processes the data, while a decision construct derives appropriate actions. A push notification service is activated based on an event-driven architecture (EDA) or a publish-subscribe (publish-subscribe) system to deliver customized notifications. The technical precision ensures that relevant information reaches the end user in time. The system optimizes operation through a self-adaptive feedback mechanism and protects data through encryption.

In various example embodiments, systems and methods for data grid platforms are proposed. User-associated attribute data is accessed from multiple attribute sources. Analysis of the attribute data is performed. Based on this analysis, actions corresponding to the user are executed.

The invention belongs to the technical field of artificial intelligence, and relates to an AI psychological tutoring system with emotion intelligence and privacy calculation double engines, comprising: a data acquisition and fusion module for generating a fusion input stream with time-space alignment; the emotional state analysis module is used for generating a dynamic emotional state matrix; the privacy strategy generation module is used for triggering a privacy calculation engine to construct a differential privacy domain according to the dynamic emotional state matrix and generating hierarchical data grids; the privacy recoding module is used for executing privacy recoding on the fused input stream according to the hierarchical data grids to generate an anti-reverse engineering ciphertext packet; the self-adaptive strategy generation module is used for generating a self-adaptive tutoring strategy tree; and the closed-loop intervention execution module is used for driving the terminal equipment to execute feedback of the self-adaptive tutoring strategy tree and generating a closed-loop psychological intervention flow. According to the invention, the problem that a real-time capture and response mechanism for user feedback is lacked due to the fact that most interaction modes are one-way output is solved.

In accordance with an embodiment, described herein are systems and methods for use of an in-memory data grid as a vector database, with linearly-scalable data ingestion, for use in generative artificial intelligence (AI), data visualization, or other applications that include the use of a large language model (LLM) or a retrieval-augmented generation (RAG) process. In accordance with an embodiment, where AI-related tasks or processes, such as content ingestion and vectorization, or vector similarity searches, can be performed in parallel, the in-memory data grid provides efficient scaling and execution of such processes. When tasked with large amounts of content to be vectorized—for example in a cloud environment or as part of an on-premise solution—the system can scale its processing of the content, in parallel where indicated, to perform an optimal utilization of available computing hardware resources, and expeditiously perform required tasks or processes.

The invention provides a method for obtaining a three-dimensional body through two-dimensional seismic reflection data gridding, and belongs to the field of seismic data processing. Through a technical means of constructing a virtual grid through rotation, a two-dimensional measuring line is converted into a three-dimensional data body which is uniformly distributed in space, and subsequent data processing is not limited to one direction any more. Specifically, latitude and longitude coordinates of each discrete reflection data are obtained and converted into UTM projection rectangular coordinate values, and coordinate values of a longitude minimum point are determined; calculating the optimal azimuth angle of the grid according to the plane distribution characteristics of the discrete points, and determining the grid spacing along the azimuth angle direction and the vertical azimuth angle direction; the grid is rotated to the three-dimensional grid direction, the coordinates of the point with the minimum longitude value after rotation are extended outwards by a half grid interval, and the coordinates of the point serve as base points of the grid; all the coordinate points are rotated in the same way, data falling into the same grid are superposed, then the coordinate number of each point in the grid is calculated, and a three-dimensional data volume is obtained accordingly.

The present invention relates to a data grid system for realizing data collaboration based on a private message structure, which includes a control plane, a data plane, and data packets; the control plane, the data plane, and the data packets are connected in sequence; the system performs data transfer collaboration in a decentralized manner of the data grid. The present invention changes the concept that a large amount of data must be centralized in traditional centralized data collaboration for use, focuses on the domain attributes of data, and allows each domain to participate in data collaboration and transfer to achieve the goal of data joint governance and decentralization.