467 results about "Background data" patented technology

The invention relates to the technical field of e-commerce data processing, in particular to an e-commerce sales platform background data management method and system. The method comprises the following steps: S1, collecting a commodity dynamic data stream, a user behavior event stream and a promotion strategy stream in real time, and generating a standardized data stream through time sequence alignment; s2, constructing a dynamic coupling data cube; s3, executing a real-time decision: in response to the payment request, selecting an inventory distribution or replacement commodity pushing strategy based on a commodity-user coupling matrix value; in response to the resource overload state, triggering a resource scheduling strategy; and S4, dynamically adjusting calculation parameters of the coupling matrix according to decision execution feedback. By solving the problems of real-time standardization processing of multi-source heterogeneous data and real-time coupling of dynamic inventory and user behaviors, the data processing capacity, inventory distribution efficiency and recommendation accuracy of the platform are remarkably improved.

The invention relates to the technical field of semantic processing, in particular to a context-aware SQL (structured query language) generation method based on table field semantic enhancement, which comprises the following steps of: acquiring financial management and investment combination data of a user and mode information of a background database, constructing a mixed semantic index database, receiving natural language query input by the user, and generating a query result. Performing intention judgment on the query by utilizing the lightweight intention classification model, and if the intention is judged to be matched, calling a parameterized SQL template bound with the query intention and filling parameters to generate a final SQL query; if it is judged that the query intention is an exploration type intention, executing a two-stage SQL generation process, including generating an SQL skeleton according to the query intention, performing target type field recall based on the SQL skeleton, and filling the recalled field into the SQL skeleton to generate a final SQL query; and monitoring the execution performance of the final SQL query, and updating the query popularity metadata and the calculation cost metadata. According to the method, the SQL generation efficiency is improved through intelligent shunting and self-optimization.

The invention relates to the technical field of soil remediation management, in particular to a method and system for soil remediation and digital management, and the method comprises the steps: data construction: fusing multi-source monitoring soil environment parameters with space-time background data such as a GIS layer and a meteorological time sequence to form a data set; state quantification: outputting a comprehensive state index for quantifying restoration urgency and complexity through the soil health assessment model; scheme generation: matching the restoration target library and the resource library, and generating a digital restoration scheme containing an expected state trajectory through an optimization algorithm; closed-loop control is carried out, feedback data comparison tracks are continuously collected, if the deviation exceeds a threshold value, the index is recalculated, the scheme is dynamically adjusted, and the system comprises a data construction module, a state quantification module, a scheme generation module and a closed-loop control module and executes the method. According to the method, the data reliability and evaluation scientificity are improved, the scheme adaptability is guaranteed, dynamic and controllable remediation is realized, and digital and efficient management of soil remediation is promoted.

The invention relates to the technical field of image data processing, and discloses an AI target change detection method fusing a time sequence remote sensing image, which comprises the following steps of: calculating a difference information entropy value of a remote sensing image on a satellite-borne edge calculation unit, and comparing the difference information entropy value with a trigger threshold value; only when the information entropy value is higher than the threshold value, the change area is extracted to form an incremental information packet to be transmitted to the ground; and after analyzing the incremental information packet, the ground station generates an instruction according to the identified environmental interference characteristics and regional stability, feeds back the instruction to the satellite-borne unit, and bidirectionally adjusts a trigger threshold value. According to the invention, an information screening decision is preposed to a data generation source, so that invalid transmission of massive invariable background data is avoided; therefore, the acquisition delay of the key change information is obviously reduced; the established satellite-ground closed-loop feedback mechanism enables the whole monitoring method to continuously optimize the judgment standard during use, and the applicability and reliability of the method are improved.

The invention belongs to the technical field of virtual automobile exhibition, and particularly relates to a virtual automobile exhibition system based on digital twinning. The system comprises a digital twinning construction module which generates a lightweight model and supports first-person visual angle dynamic updating; the user behavior analysis module is used for mapping data such as a sight track into a weighted directed graph, and predicting vehicle types and configuration requirements by using a multi-head graph attention network; the personalized configuration selection module is used for generating a configuration scheme in combination with digital twinborn parameters; the virtual test driving module is used for providing immersive experience based on the configuration scheme and the scene; and the background data analysis module integrates the data to generate a user portrait so as to optimize the exhibition content. According to the system, dynamic virtual-real mapping, accurate demand prediction and data-driven intelligent exhibition are realized, and the user interaction depth and the car purchase efficiency are improved.

The invention relates to the technical field of data processing, in particular to an operation and maintenance object information query and work order automatic generation system based on NFC (Near Field Communication) equipment, which comprises an NFC identity recognition module, an equipment parameter summarization module, a work order information verification module, a work order structure generation module, a work order push confirmation module and a work order submission terminal based on NFC, and reading the NDEF data of the NFC tag of the equipment through the NFC reader-writer. According to the invention, automatic acquisition of equipment identity is realized through near field communication, multi-dimensional data consistency verification is carried out in combination with a chip sequence, all equipment information is automatically linked with a background data set, multiple parameters acquired on site are subjected to system logic screening, and work order key information is automatically distributed to a standard structure field. A data packaging link is controlled by a unified standard template, multiple safety verification and full-process state monitoring are executed in a submission stage, error risks are reduced in each link by means of systematic processing, a data tracing link is continuously improved, and field response and overall circulation efficiency are remarkably improved.

Methods and apparatuses are described herein for configuration of background data transfers (BDTs) between local area data networks (LADNs). An apparatus may receive a message indicating a request from a user equipment (UE) for a data transfer of data originating from the UE. The apparatus may send, to a database, a request for subscription information associated with the UE and a policy profile associated with the UE to determine whether there is an existing BDT policy. The apparatus may receive, from the database, a response indicating whether there is an existing BDT policy that can be re-used. The apparatus may determine, based on the received response, a BDT policy for the data transfer and a LADN to service the data transfer. The apparatus may send, to the LADN via a radio access network (RAN) node, a notification message of an arrival time and data rate for the data transfer.

The invention relates to an air-space-based infrared imaging simulation platform based on CUDA (Compute Unified Device Architecture). The air-space-based infrared imaging simulation platform comprises a global calculation class, a three-dimensional position calculation module, a camera generation module, a sun calculation module, a background data extraction module, a target calculation module and an imaging effect calculation module. The platform meets the requirement of high-precision signal-level space-space-based infrared detection imaging simulation, the simulation image data generation efficiency is greatly improved under the condition that the signal-level imaging simulation precision in a space scene is guaranteed, and rapid generation of imaging simulation data of a space platform joint observation target in a multi-observation track scene is achieved. And the universality of the platform is improved by using modular data and development.

The invention belongs to the technical field of data and graph conversion, and discloses a data information and graph conversion management system applied to a design drawing, and the system comprises a data collection module which collects design data from a device end, a main system end and a background database, and guarantees the stability and accuracy of data collection through a built-in verification mechanism; after receiving the data of the acquisition module, the data preprocessing module unifies the data in different formats into a system standard format, removes redundant records and corrects logic errors, so that the data structure is unified and the formats are compatible; the unit conversion module receives the preprocessed data, and performs unit conversion on flow and pressure parameters by utilizing a rule base according to a factory standard and an equipment source unit, so that the data units are unified; and after the rule operation module obtains data with unified units, a merging calculation model is called to carry out data classification, traffic sum calculation and traffic load verification.

The invention relates to an underwater visible light signal recovery method based on transfer learning, and aims to solve the problems of signal noise, distortion and communication performance reduction caused by disturbance of water turbidity, flow velocity, ambient light intensity and the like on an underwater visible light communication (UVLC) system. In combination with transfer learning and a generative adversarial network (GAN), data are acquired through a self-developed hardware platform, background data are generated through MATLAB simulation, simulation and real image features are fused by using a conditional generative adversarial network (cGAN) to generate simulation data, signal recovery capability is trained by using a U-NetGAN model, and finally the system is deployed at a receiving end. Compared with the prior art, the scheme overcomes the problems that traditional modulation is poor in adaptability under disturbance of water turbidity, flow velocity and the like and is difficult to deal with a complex underwater environment; the defects that a deep learning method depends on large-scale data and cross-scene generalization is weak are overcome. Through the combination of transfer learning and GAN, the UVLC system communication performance is significantly optimized, the delay is low, the complexity is low, and actual deployment requirements are better met.

The invention provides an avalanche disaster risk method, system and device and a medium, and relates to the technical field of avalanche disaster response and prevention. The method comprises the following steps: acquiring avalanche occurrence data and disaster-pregnancy background data of a target area, and determining avalanche disaster-pregnancy factors according to the disaster-pregnancy background data; based on the avalanche occurrence data of the target area, taking an avalanche point as a positive sample, collecting a non-avalanche point as a negative sample, constructing training data, constructing a random forest model, and training the random forest model by using the training data to obtain an avalanche dynamic evaluation model; and based on the avalanche dynamic evaluation model, evaluating the avalanche disaster risk of the target area. The problem of how to obtain a dynamic avalanche risk assessment model by focusing on the change of meteorological factors in the snow season avalanche high-incidence period and provide key factors needing to be monitored for avalanche early warning in different months of the snow season is solved.

The invention provides a safety risk control method for geological storage of carbon dioxide and electronic equipment. A distributed optical fiber sensing system is arranged in at least one injection well of the target sealing and storage area in the axial direction of a shaft and penetrates through a main cover layer and a reservoir; the method comprises the following steps: acquiring background data through a distributed optical fiber sensing system, and establishing a multi-parameter baseline model including a temperature field, a strain field and background noise; temperature, strain and sound wave vibration signals are collected in real time, and key features are extracted; the key features extracted in real time are compared with a preset risk feature library, the types of risk events are identified, and the identified risk events are graded according to the spatial range and intensity of the abnormal signals; and according to the type and the grade of the risk event, generating and executing a corresponding control instruction. According to the embodiment of the invention, the optical fibers are distributed in the whole area along the shaft and the target stratum, a three-dimensional monitoring network covering the sealing body is constructed, and the hysteresis quality of traditional point type measurement and periodic exploration is overcome.

A computing system and associated methodology of evaluating and matching colored sparkle appearance of coatings containing at least one effect pigment type are disclosed. The methodology processes a digital image of a coating sample obtain pixel-specific sparkle point data and pixel-specific background data, both of which are formatted in accordance with an advanced color appearance model that corresponds to human color perception. A colored sparkle visual scaling value is calculated from the pixel-specific data, wherein the visual scaling value indicates colored sparkle characteristics of the coating sample. The visual scaling value of the coating sample is compared against the visual scaling value of a previously-characterized candidate coating specimen. The results of the comparison are used to determine how well the candidate coating specimen matches (in colored sparkle characteristics) the coating sample.

The invention relates to the technical field of communication, and discloses a measurement and control communication parameter transmission state monitoring system, which comprises a data acquisition and adaptation module which is responsible for acquiring an original parameter data stream by measurement and control equipment, performing unified formatting processing on the original parameter data stream and then sending the original parameter data stream to a state optimal estimation module. A technical scheme of constructing a state space model at an edge end, performing optimal state estimation on original measurement and control parameters in combination with a Kalman filter, and performing statistical distribution deviation quantification on a filtered residual sequence by using KL divergence is adopted, a system high-fidelity operation state is extracted from strong noise background data, and progressive weak abnormity is early warned in advance and accurately. Compared with a scheme of carrying out fixed or simple statistical threshold alarm on an original measurement value, the problems that state misjudgment is caused by measurement noise interference, progressive performance degradation cannot be effectively sensed, fault discovery is lagged and the early warning capability is insufficient are solved.

The embodiment of the invention provides a transparent rendering method and device based on weight mixing order independent transparent rendering, equipment and a computer readable storage medium. The method comprises the following steps: acquiring three-dimensional scene data to be rendered; calculating the total opacity of the transparent objects in the three-dimensional scene data in the constructed auxiliary buffer area in a weighted accumulation mode; calculating background data of opaque objects in the three-dimensional scene data in the constructed main frame buffer area; and combining the total opacity and the background data to form an output image to finish rendering, so that the rendering efficiency and the visual effect can be remarkably improved in a complex scene.

The invention relates to the technical field of data reasoning, in particular to an intelligent dispute analysis system based on big data, and the system comprises an event collection module, a dispute analysis module, a scheme generation module, an emergency scheme module and an auxiliary decision generation module. Generating an original data set; extracting event key elements of the original data set to obtain a preliminary analysis report; in combination with the attribution feature data and the party background data, carrying out attribution secondary analysis on the preliminary analysis report to generate a personalized mediation scheme; when an emergency triggering condition is identified, rescue resource data are integrated based on an event geographic position, and an emergency disposal plan is automatically generated; and generating an auxiliary decision report based on the personalized mediation scheme and the emergency disposal plan. The dispute solving efficiency can be improved.

The invention relates to the technical field of emergency management, and particularly discloses a visual emergency management intelligent response system based on GIS and multi-terminal collaboration, which comprises a mobile terminal APP, a PC management terminal and an application layer, and is characterized in that the mobile terminal APP and the PC management terminal perform data interaction with a background database through a data communication interface; the application layer comprises an emergency management service module which is used for rapid reporting, positioning, multi-stage confirmation and disposal flow closed loop of emergencies; the emergency plan management service module is used for uploading, editing, querying and sharing plans; the emergency resource management service module is used for visual management and intelligent query of emergency materials; and the address book and duty table management service module is used for contact management and automatic and dynamic management of a duty table. According to the visual emergency management intelligent response system based on GIS and multi-terminal cooperation, the emergency response efficiency can be improved, the management cost can be reduced, and meanwhile, the information integrity is guaranteed.

The invention discloses an urban road and form integrated intelligent generation method based on a heterogeneous graph network. The method comprises the following steps: collecting a target design site and road, plot and building data of a city where the target design site is located; selecting a planning background data range; constructing a heterogeneous graph structure adjacent matrix, and performing feature extraction and model pre-training to obtain a pre-trained heterogeneous graph neural network based on a road structure and an urban form; importing the planning background data into the pre-training model, and predicting road and form integrated generation of the target design site; planning background data is mapped to a potential space, road and plot morphological parameters are learned, the parameters are optimized in combination with a cross entropy loss function and a back propagation algorithm, and a road network and spatial morphological scheme matched with the plot features is generated; and finally, realizing visual display of the scheme through a UMAP method and a three-dimensional rendering engine, and outputting professional drawings and interactive three-dimensional models containing parameters such as road grades, land use functions, building density and the like.

According to the character background editing method and device, the storage medium and the computer equipment provided by the invention, after the original video data with the character and the target background data without the character are obtained, the target video can be firstly determined to generate the large model; according to the target video generation large model, sample video data with figures are taken as sample labels, sample reference backgrounds after portrait elimination in the sample video data and sample reference data after synthesis of portrait masks extracted from the sample video data and sample background data without figures are taken as training samples; the target video generation large model is obtained after training, which is equivalent to that expected output is real and unmodified data when the target video generation large model is trained, so that after the background data in the original video data is replaced by the target background data through the target video generation large model, relatively real target video data can be obtained; and thus, the character background editing effect in the video creation scene is effectively improved.

The invention discloses a meteorological data fusion platform based on a GIS (Geographic Information System). The meteorological data fusion platform comprises a meteorological service module, a GIS service module, a data fusion module and a system management module, the meteorological service module provides meteorological information query and information early warning query services for users; the GIS service module is used for providing position information and map browsing service for a user, so that the user can carry out map operation and space analysis; the data fusion module removes error values of the meteorological data, analyzes traditional meteorological data, completes spatial interpolation, and carries out early warning and prediction on future weather data based on fused data; and the system management module is used for user permission distribution and background data maintenance. According to the method, the basic map of the district and county-level region can be well overlaid, so that the weather forecast data of the district and county-level region can be accurately positioned, the weather service requirement is met to the greatest extent, and the optimal auxiliary decision-making basis is provided for weather predictors.

The invention discloses a whole course health management system based on artificial intelligence, and the system comprises a user mobile terminal which is used for receiving a rehabilitation plan, obtaining the health data of a user through a data collection device, and transmitting the health data of the user to a background data management module in real time; the doctor mobile terminal is used for acquiring the health data of the user, performing illness state analysis on the user based on the health data of the user, generating a rehabilitation plan when the health data is abnormal, and synchronously transmitting the rehabilitation plan to the background data management module and the user mobile terminal; and the background data management module is used for realizing data interaction between the user side and the doctor side, and performing real-time analysis and risk early warning on the health data of the user based on the time sequence prediction model or / and the risk assessment model. According to the method and the system, the whole course of disease health management with collaboration, intellectualization and individuation can be provided.

The embodiment of the invention provides a thermal power plant network security early warning management system and method, which are characterized in that communication flow data of networking equipment in a thermal power plant network are monitored, time sequence analysis based on a deep learning technology is carried out on the communication flow data to extract time sequence change mode characteristics of the communication flow, and meanwhile, the time sequence change mode characteristics of the networking equipment in the thermal power plant network are extracted. The method comprises the following steps: extracting a set of communication flow time sequence mode characteristics of known ransomware from background data, and performing fine-grained ablation analysis on the communication flow time sequence mode characteristics of networking equipment and the set of communication flow time sequence mode characteristics of the known ransomware; therefore, abnormal traffic mode feature representation similar to the communication traffic of the networked equipment in the communication traffic mode of the known ransomware is identified and enhanced, so that intelligent identification and early warning of potential ransomware attack behaviors of the networked equipment are realized. In this way, the abnormal traffic characteristics of the ransomware attack behavior can be more effectively captured.

A method and apparatus comprising computer code configured to cause a processor or processors to obtain augmented reality (AR) data of a media component of at least one of audio and video; determine a plurality of days of a week and any of a number of occurrences of and an end date of a 5G media-streaming (5GMS) background data transfer (BDT); and control, based on an indication of a resource of a 5GMS media session handler (MSH) indicating any of a started, stopped, and teared-down state, transfer of a media stream of the media component by the 5GMS BDT according to a result of determining the plurality of days of the week and the any of the number of occurrences and end date.

The invention discloses a water regimen data acquisition dual-machine redundancy method and system, and the system comprises a main machine and a standby machine which are directly connected through an independent heartbeat interface. The main machine periodically sends heartbeat messages and local network configuration information to the standby machine through a heartbeat interface; and the standby machine monitors heartbeat in real time, judges that the main machine is abnormal once not receiving the heartbeat within a preset time, automatically takes over the IP address of the main machine, actively sends an address resolution protocol message according to pre-stored network configuration information so as to quickly update a forwarding table of the network equipment, immediately switches the state of the standby machine to be the main state, and synchronizes the state to a database. According to the method, automatic sub-second fault switching is achieved, the risk of key data loss is greatly reduced, continuity and integrity of water regimen telemetering data are guaranteed, meanwhile, the operation load of a background database is remarkably reduced through a main and standby mode, and the reliability of water regimen telemetering is improved. The problems that the load of the database is too heavy and automatic seamless switching of network channel data acquisition cannot be realized are solved.

The invention discloses a warranty service processing method and device, equipment, a storage medium and a product, and relates to the technical field of text generation, and the warranty service processing method comprises the steps: obtaining target background data of a warranty application, and based on a large language model, recognizing warranty application elements in the target background data, and filling the obtained target warranty elements into a warranty application template to obtain a target warranty text, and visually displaying the target warranty text to enable a user to preview the warranty text, and submitting the target warranty text to a warranty service system to complete warranty service processing. According to the method, the client is assisted in filling the form through the background data, the corresponding warranty text is generated and visually displayed, so that the user does not need to manually fill tedious and error-prone warranty application elements and can preview the warranty text before submission, repeated warranty text modification, submission and approval processes are avoided, and the user experience is improved. Therefore, the processing efficiency of the warranty service is improved.

The invention discloses a communication method and device, and relates to the field of communication. The communication method can reduce network energy consumption during background data transmission, and comprises the following steps: a first network element receives a first request from an application function network element for requesting a strategy of background data transmission between the application function network element and a terminal device, and sends a first response for responding to the first request to the application function network element, the first response comprises at least one first strategy and an energy consumption parameter corresponding to each first strategy in the at least one first strategy; and the application function network element determines a second strategy from the first strategies according to the energy consumption parameters corresponding to the first strategies, and transmits the background data according to the second strategy.

The invention discloses a transmission line icing state analysis and early warning method and system based on a synthetic aperture radar satellite image, and belongs to the technical field of radar satellite remote sensing monitoring, and the method comprises the steps: S1, carrying out the data collection of a synthetic aperture radar image of a transmission line monitoring region based on meteorological condition forecasting, and carrying out the data collection; obtaining background data of the power transmission conductor in an uniced state; s2, performing data acquisition and preprocessing based on the synthetic aperture radar satellite image in the icing state of the power transmission line monitoring area to obtain icing data in the icing state of the power transmission line; and S3, performing analysis and early warning based on the background data of the power transmission conductor in the uniced state and the iced data of the power transmission conductor in the iced state. According to the invention, through the SAR satellite imaging technology, rapid power transmission line icing state monitoring and real-time early warning work are carried out, the problem of limited monitoring capability and range of current manual and online monitoring sensors is solved, and new added value is provided in the aspect of power transmission line operation and maintenance.

The invention relates to the field of photovoltaic product carbon footprint accounting, and discloses a data screening and evaluation method and system for supporting development of a photovoltaic product carbon footprint background data set based on an environmental assessment file. According to the method, a multi-level structured environmental assessment file label system is constructed, a multi-dimensional data source quality evaluation index is established, a nonlinear confidence enhancement scoring function, a multi-level weighting mechanism and a key index elimination mechanism are provided, and a data source quality comprehensive evaluation scheme is formed. In the data extraction stage, a data category division scheme based on the key composition of photovoltaic products and a harmonic enhanced unit standardization processing method are adopted. Meanwhile, a multivariate cross check mechanism fusing industry reference value check and triple balance check is constructed, a three-dimensional data quality scoring model is introduced, and a data quality comprehensive evaluation system is formed. According to the application, the carbon footprint data quality of the photovoltaic product is remarkably improved, and data support is provided for industrial carbon accounting.

The invention provides a transformer substation background data validity test method. The method comprises the following steps: firstly, acquiring model data, establishing a measuring point index and replacing an enabling index through a first terminal, namely a point detector, at the front end, pulling a database file and a picture file through a second terminal, namely a monitoring background, analyzing the database file and the picture file, and verifying the consistency of the model, so as to confirm the data consistency condition and the enabling attribute condition; substation background data validity checking is completed by replacing data checking of files and data messages, so that the automation level of the checking process is improved, and then the efficiency and validity of substation database data checking are improved; and the corresponding file retaining report is generated in the inspection process, and the inspection process of monitoring the data validity in real time can be realized, so that the timeliness of the substation background data validity inspection is improved.

The invention discloses an economic data intelligent analysis system and method based on big data, and the method comprises the steps: obtaining background data including public economic data and macrocurrency policy text description; a neural network model based on deep learning is adopted to carry out feature coding on the two features to enhance the understanding ability of the model for the deep meaning of background data, and public economic data item coding features and macrocurrency policy semantic coding features are obtained; performing collaborative analysis on the public economic data item coding characteristics and the macrocurrency policy semantic coding characteristics to mine deep semantic association between the public economic data item coding characteristics and the macrocurrency policy semantic coding characteristics, and capturing a dynamic relationship between the currency policy and an economic index based on the deep semantic association; and outputting an analysis result of the corresponding economic data analysis problem by using the large language model. Therefore, the system can provide more comprehensive and accurate economic data analysis results, and helps users to better understand economic phenomena and policy influences.