712 results about "Data preservation" patented technology

The invention discloses a comprehensive algorithm for distribution and scheduling of AGV (Automatic Guided Vehicle) carrying tasks. S1: an SCADA system; equipment communication, data acquisition and storage, protocol analysis and logic processing; s11, the communication protocol, the address and the communication rhythm of the equipment are configured through the system, data acquisition data are stored in ES (ElasticSearch), the data acquisition data are stored for one year and backed up regularly, and the system achieves service logic processing through an LUA script. The carrying efficiency of the AGV is integrally improved, and the execution time of carrying a single task by the AGV is shortened by 10%; the production capacity of a workshop is improved, and the carrying rate exceeds 96% under the condition of no interference; the workshop logistics cost is reduced, and the overall number of AGVs is reduced by 10%; and the first pass yield of material carrying is improved by 15%. The deep fusion data analysis capability enables the whole system to predict demands more accurately, avoid conflicts, optimize the overall production efficiency, optimize the production process, reduce waiting and resource waste, and improve the flexibility of path planning and the reliability of task completion.

The invention discloses a heterogeneous data processing method and device and a storage medium, and relates to the technical field of data processing.The method comprises the steps that to-be-processed heterogeneous data are obtained, field identifiers in the heterogeneous data are extracted, and then the field identifiers in the heterogeneous data are identified on the basis of a pre-trained semantic identification model; performing semantic matching on the field identifier and a target field in a preset database to generate a field-level mapping relationship, generating a step-by-step processing logic adaptive to a heterogeneous data format according to the field-level mapping relationship, executing verification operation on the step-by-step processing logic in a code sandbox, and performing verification operation on the step-by-step processing logic in the code sandbox. And after the verification is passed, storing the output target field data to a structure database. According to the heterogeneous data processing method and device, the extracted field identification is subjected to semantic matching, and the extracted target field is verified in combination with the code sandbox, so that the accuracy of heterogeneous data processing is improved.

The invention discloses a decision support method for time-space dynamic data of Internet of Vehicles based on knowledge retrieval enhancement, which comprises the following steps: collecting perception data inside and outside a vehicle, and separating general data and private data; preprocessing the data, and compressing and encrypting the private data; performing data processing by adopting a data knowledge dual-drive mode and a large language model, and converting the data into structured data; constructing a super-relation knowledge graph, and carrying out vectorization processing based on an embedded vector model; performing node importance evaluation based on the super-relation knowledge graph, and performing data updating and increment; storing the private data locally, uploading the general data to a public database of the cloud, and defining a dynamic access range of the public database; and extracting a user questioning entity by using the local entity recognition model, matching data existing in the local and the cloud, obtaining background knowledge contents, and generating an enhanced retrieval result. According to the method, the problems of acquisition of decision support information and use safety of data in an Internet of Vehicles environment are solved.

The invention provides an unmanned aerial vehicle intelligent inspection method and system combining a three-dimensional point cloud modeling and flight path planning technology. The system comprises a data acquisition module, a data processing module, a platform uploading module, a three-dimensional point cloud modeling module, a flight path planning module and a task execution module. By combining the three-dimensional point cloud modeling and flight path planning technology, the whole process is automatic, a closed loop is formed from data acquisition to flight path generation, manual intervention is reduced, automation, refinement and intelligentization of unmanned aerial vehicle routing inspection are achieved, and the routing inspection efficiency and safety are remarkably improved. The method has the advantages that point cloud data is processed through a pre-constructed point cloud data processing model, the quality of the point cloud data is improved, sub-centimeter-level modeling is realized in combination with a BIM technology, the precision of three-dimensional point cloud modeling is high, track planning is based on real three-dimensional geometry, and fine inspection is supported. And through data storage of different file types, the transmission processing efficiency is improved, the space information of the three-dimensional point cloud is fully utilized in the route planning, and refined inspection is supported.

The invention relates to the technical field of computers, and discloses a metadata storage method and device, computer equipment and a storage medium. Obtaining the current proportion among the average flash memory erasing times of the hard disk, the average power-on time of the hard disk, the metadata variation quantity and the metadata snapshot quantity, and determining the times proportion among the average flash memory erasing times; according to the average power-on time, the average flash memory erasing frequency and the frequency ratio, adjusting the current ratio to obtain a target ratio; determining a metadata variation, and generating a metadata snapshot in the memory according to the target proportion, the metadata variation and the metadata; and flashing the metadata snapshot in the memory to a hard disk corresponding to the metadata in the metadata snapshot. The problems that when metadata are stored, the proportion of delta and base is difficult to adapt to the current state of the SSD, and the service life and the average power-on time of the SSD cannot reach the optimal state are solved.

The invention relates to the technical field of cell preparation quality evaluation, in particular to a cell preparation whole-process quality intelligent evaluation system and a method thereof, and the system comprises a data acquisition module, a preprocessing module, a mining module, a modeling module, a report automatic generation module and a data storage module. The modeling module is used for constructing a cell product index evaluation system and a product traceability model and comprises a cell culture state evaluation model and an environment monitoring analysis module, and the environment monitoring analysis module is used for carrying out traceability analysis by using a time sequence convolutional neural network; the automatic report generation module intelligently evaluates the quality of the whole process and generates a report, the data storage module manages data and model storage, sharing and calling, the system constructs a cell quality evaluation system based on multi-dimensional data, integrates multiple dimensional indexes such as morphology, surface markers and functionality, realizes comprehensive evaluation, and improves the evaluation efficiency. And the one-sidedness of single index evaluation is avoided.

The invention discloses a trust evaluation data storage tracing method and system based on a block chain technology, and particularly relates to the technical field of data storage management, and the method comprises the following steps: recording trust evaluation data in a block form based on the distributed storage characteristics of a block chain, automatic management of data submission, verification, storage and updating is realized by using an intelligent contract, data authenticity and non-tampering are ensured, time stamps are added for data through a timestamp function, a time-ordered operation chain is formed, a data tracing function is provided, an authorized user is allowed to inquire a data source and historical operation records, and the user experience is improved. Based on data access characteristics, a storage area is dynamically adjusted, and efficient utilization and optimal management of storage resources are achieved; according to the method, the storage position of data can be dynamically adjusted, hot data are stored in a high-performance storage area, cold data are migrated to a low-cost storage area, the access efficiency of high-frequency data is guaranteed, and the storage cost is optimized.

The invention provides a large language model reasoning method and device, electronic equipment and a storage medium, and the method comprises the steps: searching a storage space for a historical high-storage-efficiency tensor corresponding to each stored request according to a mapping table under the condition that a current request is received, and converting the historical high-storage-efficiency tensor into a historical target tensor; executing a current round of reasoning through the large language model according to the current request, obtaining an intermediate tensor corresponding to each layer of the large language model in the current round of reasoning process, and obtaining a current target tensor required by attention layer calculation of the large language model in the intermediate tensor; searching a current high-storage-efficiency tensor as a precursor of the current target tensor, storing the current request and the corresponding current high-storage-efficiency tensor in a storage space as historical intermediate data, and updating the mapping table; and inputting the historical target tensor and the current target tensor into the attention layer for calculation to obtain the reasoning text corresponding to the current request, thereby effectively reducing redundant calculation.

The invention relates to the technical field of three-dimensional point cloud scanning, and discloses a three-dimensional laser scanner and a real-time point cloud scanning method and system, and the method comprises the following steps: setting a dot spacing, setting the rotating speed of a drive motor, and setting the transmitting frequency of a laser transmitting and receiving module; controlling the motor to rotate to drive the laser to emit laser; when laser starts to be emitted, the reading module collects angle parameters of the coded disc in real time and measures a laser flight time value through the laser flight time measuring module; combining the angle parameter, the laser flight time value and the laser reflection intensity value read in the last time of laser emission into a frame of data and storing the frame of data in an original data buffer area; reading frame data of the original data buffer area in real time, and calculating to obtain a three-dimensional coordinate; and taking the three-dimensional coordinates and the laser reflection intensity value as a frame of data and storing the frame of data in a result buffer area. The problem that the real-time application requirement is difficult to meet in the prior art is solved, and the method has the advantage of being capable of reducing the operand.

The invention provides a visualization method and device for the combustion process of a circulating fluidized bed boiler, and the method comprises the steps: collecting the operation data of the circulating fluidized bed boiler in real time through a distributed control system at an upper computer, and storing the collected data in a CSV format; in the lower computer, a three-dimensional modeling tool is used for establishing a three-dimensional model of the solid boiler, and grid division is carried out; controlling the upper computer to generate boundary condition data of numerical simulation according to the acquired CSV data, transmitting the boundary condition data to the lower computer, and reading the latest boundary condition data by using the lower computer to perform real-time simulation calculation; performing post-processing on a simulation calculation result by utilizing the lower computer to obtain a picture and curve data, and transmitting the picture and curve data to the upper computer through a network; and the upper computer is controlled to display the visual results of the temperature field, the velocity field, the pressure field, the gas component concentration field and the ash combustible content in real time through a platform interface in the forms of static diagrams, dynamic diagrams and trend curves. According to the method, the combustion process of the circulating fluidized bed boiler can be rapidly visualized, the operation state of the boiler can be predicted, and guidance is provided for operation optimization and parameter adjustment.

The invention belongs to the technical field of computer software, and particularly relates to an automatic statistical method and system based on software defect texts, comprising a preprocessing module used for importing information containing software defect text data into the system, preprocessing the software defect text data, removing useless symbols and redundant texts in the texts, and storing the useless symbols and redundant texts in the system; the preprocessing module is used for preprocessing a. Txt file and storing the preprocessed data into the. Txt file in a specified format, the extraction module is used for extracting keyword features from the preprocessed. Txt file, the keyword features comprise at least one of defect identification, defect type, defect level, repair suggestion, defect category, defect description, processing suggestion, reason analysis and rectification scheme, and the statistical analysis module is used for carrying out statistical analysis on the keyword features. And the statistical analysis module is used for performing statistical analysis on the extracted keyword features. According to the method, related information of software defects can be efficiently and accurately counted, manual participation in column-by-column counting is reduced, and the efficiency of defect detection and management and the accuracy and efficiency of a statistical result are improved.

The embodiment of the invention provides a data processing method and device, equipment, a storage medium and a program product. Comprising the steps of judging whether a transmission mode of an application layer for a to-be-written data write request is a direct read-write mode or not; if the mode is not the direct read-write mode, continuing to judge whether a client cache mechanism is started or not; if the client cache mechanism is started, continuing to judge whether the to-be-written data or metadata of a parent directory of the to-be-written data carry a cache acceleration mark or not; if the to-be-written data or the metadata of the parent directory of the to-be-written data carry a cache acceleration mark, obtaining the size of an idle memory block of a preset cache; when the size of the free memory block is greater than or equal to that of the to-be-written data and the to-be-written data is not overlapped with the data in the preset cache, storing the to-be-written data in a memory block pre-allocated by the preset cache; and traversing the memory block list of the preset cache, and storing the to-be-written data to the target storage. The method is used for achieving the effect of improving the data processing performance.

The invention discloses a CAD application system design scheme data management method and system, and relates to the computer cartographic technology, and the method comprises the steps: in a target design scheme creation stage, separately creating design model data and design view data of a target design scheme, and copying to obtain intermediate design model data and intermediate design view data; a design scheme data editing stage: loading part of design model data associated with editing data, executing editing, and storing edited update data to the intermediate design model data and the intermediate design view data after editing; and synchronizing the intermediate design model data and the intermediate design view data to the design model data and the design view data of the target design scheme in a design data storage and submission stage. According to the method, through the data middle layer, high consistency and integrity of design scheme data can be well guaranteed through two-stage submission.

The application provides a weather load-based air conditioner energy control method and device and a storage medium, wherein the method comprises the following steps: saving PLC bottom layer instrument data, indoor temperature sensor data and public data to a cloud platform server; processing the above data, calculating first index data in units of predetermined working time, calculating an optimized load amount according to the first index data; selecting a date closest to a predicted load day comprehensive temperature T in historical operation data as a reference day, taking the load of the reference day as a reference day load; and adjusting air conditioner energy according to the optimized load amount through two preset optimization conditions and the reference day load. The application predicts future load change rules by mining the corresponding relationship among climate, indoor temperature and load change rules through historical data, so as to realize the purpose of precise energy supply and effectively avoid energy waste.

The embodiment of the invention provides an intelligent penetration testing method and device based on deep reinforcement learning, and the method comprises the steps: constructing a network information environment, setting basic parameters, initializing the network information environment, and constructing an act-critic structure with an independent strategy network and an independent value network; modeling the Markov decision process of the penetration test into a quaternion group lt; s, A, R, Pgt; a Markov model is constructed; constructing a priority playback experience pool; performing penetration testing based on a Markov model, calculating and outputting an attack action to a network information environment through a strategy network based on a current penetration state to obtain a next penetration state, rewarding the attack action through a value network, and storing data in a priority playback experience pool; and calculating and determining a mode of preferentially selecting sampling according to the priority of experience, repeating the penetration test operation of the Markov model until the function is converged, and outputting an optimal penetration strategy.

The invention provides a steering gear autonomous zero calibration control system and a steering gear autonomous zero calibration control method. The steering gear autonomous zero calibration control system comprises a data acquisition module used for acquiring required bus message information; the vehicle mass calculation module is used for calculating the vehicle mass; the steering wheel angle calculation module is used for calculating a corresponding steering wheel sensor angle value; the tire pressure calculation module is used for receiving the tire pressure measured by the tire pressure sensor; the straight-line driving judgment module is used for judging whether the vehicle is in a straight-line driving state or not according to the wheel rotation angle obtained by the wheel rotation angle sensor in the steering controller; the zero angle control module is used for vehicle zero angle control calibration; and the data storage module is used for storing the data in the corresponding NVRAM after the vehicle learns new zero angle data. The problem that a steering wheel is not correct due to the fact that the electric power steering zero angle of the vehicle deviates from the zero position due to changes of the mass and the tire pressure of the vehicle is solved.

The invention provides a long-term service metal grain size identification method based on machine learning. The method comprises the following steps: exciting the surface of a test piece to generate ultrasonic waves; acquiring ultrasonic information generated by exciting the test piece, and inputting the ultrasonic information into a sample database for feature comparison; predicting the grain size according to the prediction model, and calculating an error according to the grain size pair of the tested piece; evaluating the safety of the long-term service metal of the test piece according to the grain size error of the test piece and the grain size predicted by the prediction model, and outputting a detection result; the ultrasonic information generated by exciting the test piece is subjected to data storage for enriching a sample database, and a machine learning algorithm can learn and construct a more complete data model. During use, a laser ultrasonic technology and a non-contact detection mode are adopted, the surface of a test piece does not need to be damaged, damage to a main steam main pipe is avoided, meanwhile, shutdown is not needed, and the detection cost and time are remarkably reduced.

The invention discloses an AI accelerator card operation and maintenance method and device based on performance index collection, equipment and a medium, and relates to the technical field of cloud computing, and the method comprises the steps: obtaining a performance index collection request sent by a target host after the communication connection with the target host is established, and determining target peripheral interface equipment information; determining the number of currently mounted accelerator cards and the type of the accelerator cards through a preset accelerator card manufacturer dictionary table and target peripheral interface equipment information, and initializing a performance index acquisition thread according to the number of the accelerator cards and the type of the accelerator cards; verifying a local accelerator card driver and an equipment management library of the AI accelerator card, and after verification is passed, calling the equipment management library to perform performance index acquisition of the AI accelerator card based on the performance index acquisition request and the performance index acquisition thread; and storing the performance index data in a preset database, performing judgment according to a preset performance index alarm rule, and performing display at a target front end so as to perform operation and maintenance on the AI accelerator card.

The invention relates to the technical field of data maintenance, in particular to a data preservation method for a server and an application system. The method comprises the following steps: acquiring an emergency backup request, analyzing the emergency backup request, and determining a trigger time point; according to the triggering time point, historical backup data are called, and current newly-added data are determined according to the historical backup data; analyzing the current newly-added data to obtain data features; according to the data features, performing multi-dimensional disassembly on the current newly-added data to obtain fragment data; and obtaining network topology information at the current moment, and according to the network topology information and the data characteristics, determining a differentiated backup scheme of the fragment data to perform data preservation operation. The probability that the infected data enter the backup link is reduced, and the recognition accuracy of the high-sensitivity data is improved. According to the method, the network topology information at the current moment is obtained, and the differentiated backup scheme of the fragment data is determined according to the network topology information and the data characteristics to perform data preservation operation, so that the utilization rate of network resources is improved.

The invention provides a copper concentrate sample traceability method based on X-ray fluorescence spectrum and isotope detection, and relates to the technical field of copper concentrate traceability. Data sampling is carried out on subjective factors and objective factors in the copper concentrate sample sampling process, data storage is carried out based on a block chain to improve the safety and accuracy of data, discretization, standardization, abnormal value correction and principal component analysis processing are carried out on the data analysis result of the copper concentrate sample, and therefore data standardization is guaranteed, and the accuracy of the data analysis result is improved. Based on a first mining area feature fingerprint database set obtained through historical data mining, determining a target mining area to which the copper concentrate sample belongs and a corresponding first similarity; by means of the technical scheme, standardization processing of the copper concentrate analysis result can be achieved, then the consistency rule is extracted, the confidence probability is given out for the traceability result in combination with the sampling process data, and therefore the obtained traceability result is more accurate.

The invention discloses a software and hardware co-simulation field recovery method and device, equipment and a medium. Comprising the steps of defining a recording starting point and a storage time point of a simulation site; from the recording starting point to the storage time point, capturing transaction flow and causal metadata from the hardware simulation environment of the simulation site to the software test platform, and meanwhile, storing a state snapshot of the verified design in the hardware simulation environment; and when a recovery instruction is received, performing simulation field recovery based on the transaction flow, the causal metadata and the state snapshot. By defining the time range of data capture, a clear boundary is delimited for subsequent data storage, and pertinence and integrity of data records are ensured. A basis is provided for semantic reconstruction of a software test platform by capturing a transaction flow and causal metadata, a state snapshot ensures that the verified design hardware state can be accurately restored, and complete storage of recovery data on the two sides of software and hardware is achieved. And the system does not need to be restarted from the starting point during recovery, so that a redundancy initialization process is avoided, and the simulation debugging efficiency is improved.

The invention discloses a man-machine collaborative remote sensing image intelligent labeling method and device based on a visual large model. The method comprises the steps of obtaining remote sensing image data to be labeled, and performing image enhancement processing to obtain enhanced remote sensing image data; inputting the enhanced remote sensing image data into a visual large model for mask segmentation processing, and outputting a plurality of target segmentation masks and corresponding confidence coefficients; marking layer graphs with different colors on the to-be-marked remote sensing image data to form marked remote sensing image data, and displaying the marked remote sensing image data to a user; and the user performs confirmation operation, and stores the labeled remote sensing image data as a GeoTIFF file format image with geographic reference information. In the embodiment of the invention, the image labeling precision of complex ground objects, multiple regions and the like is obviously improved.

A memory device may sometimes undergo post package repair. Systems and methods described herein may help preserve data of the memory device as part of the post package repair operations. Systems and methods described herein may enable receiving a post package repair command and an indication of a target memory address, performing an on-chip data preservation on a target portion of memory based on the target memory address, and performing post package repair on the target portion of memory based on the target memory address.

The invention discloses a GeoServer-based map tile generation method and device, a GeoServer-based map tile release method and device and electronic equipment. The method comprises the following steps: acquiring source data from a geographic information system; performing reprojection and resampling operation on the source data according to a preset projection coordinate system and resolution to obtain specific resolution data; cutting the specific resolution data to obtain data of a specific area; determining a tile space range of each map tile, segmenting the data of the specific area according to the tile space range of each map tile, and obtaining tile preliminary data of each map tile; performing data format conversion on the tile preliminary data of each map tile to obtain map tile data in a target tile format; and storing the map tile data in the target tile format to a database, and publishing the map tile data in the target tile format in a GeoServer server.

The invention discloses a vehicle intra-domain communication data transmission method and system, a storage medium and electronic equipment, and the transmission method comprises the steps that a dynamic library receives request information sent by an application program and sends the request information to a protocol stack background program, and intra-domain communication connection is established; identifying a socket event according to a socket of the communication connection; receiving communication data sent by the application program and the protocol stack background program, and storing the communication data in the shared memory area; reading corresponding communication data from the shared memory area according to the socket event, and sending the communication data to an application program and / or a protocol stack background program; the dynamic library can quickly respond to various events and process request information from different application programs in time, and the shared memory can realize quick storage and reading of data, so that frequent data copying and transmission are avoided, and the communication efficiency is greatly improved. The combination mode can give full play to the event-driven characteristic of the dynamic library and the high-speed data sharing advantage of the shared memory.

Method and apparatus for predictive dump capture are provided. A prediction indicating that a failure within a computing system will occur at an anticipated time is received. One or more existing processes are assessed over a time window to identify data for preservation, wherein the time window begins at the reception of the prediction and extends to the anticipated time of the failure. Workloads of the computing system are quiesced based on the assessment. A memory dump process is initiated to save data in memory of the computing system. Backup resources are searched to expedite the memory dump process.

The invention discloses a large model deployment and service method and device for realizing intelligent customer service based on container arrangement, equipment and a medium, and relates to the field of artificial intelligence, and the method comprises the steps: constructing a standardized container mirror image which comprises an inference engine, a model acceleration library and a model encryption and decryption assembly and is adaptive to an intelligent customer service scene; establishing a graphic processing unit resource management system in the container arrangement cluster; storing model data of the intelligent customer service model to a target storage system, and determining a mounting mechanism corresponding to the model data; generating a container arrangement and deployment file based on a graphic processing unit resource management system, the operation demand of the standardized container mirror image and a mounting mechanism corresponding to the model data; and submitting the container arrangement deployment file to a container arrangement platform, so that the container arrangement platform carries out intelligent customer service model deployment, and the deployed intelligent customer service model is utilized to receive a user request and return a corresponding target response. According to the method, the deployment complexity is reduced, and the model deployment efficiency and stability are improved.

The invention belongs to the technical field of data management, and particularly discloses a traditional Chinese medicine personalized diagnosis and treatment data summarization processing method and system and a program product, which can master the deep and nonlinear relationship between traditional Chinese medicine diagnosis and treatment symptoms and syndromes, realize deep semantic understanding and remarkably improve the data matching accuracy. Scattered cases can be classified according to syndromes, and personalized experience of different doctors of traditional Chinese medicine is dynamically absorbed, so that an experience library is evolved continuously; the safety and privacy of traditional Chinese medicine diagnosis and treatment data storage can be ensured, and a technical basis is provided for diagnosis and treatment knowledge tracing and right confirmation; personalized diagnosis and treatment knowledge of a specific physician group can be conveniently decrypted, and digital inheritance of traditional Chinese medicine diagnosis and treatment experience is facilitated. According to the method, deep simulation of traditional Chinese medicine diagnosis and treatment logic can be realized through innovative feature fusion and similarity calculation, and an experience library which can continuously grow and can effectively regularize personalized diagnosis and treatment data of traditional Chinese medicine doctors is formed through a dynamic and safe encryption archiving mechanism.

The invention discloses a self-adaptive underground dust remover based on a neural network, which comprises a walking control mechanism and a dust removal mechanism, the walking control mechanism is used for controlling the dust removal mechanism to move to a specified position and angle, and the data acquisition module is responsible for monitoring various operating parameters and environmental data of the dust removal mechanism in real time; the data storage module is responsible for storing the data collected by the data acquisition module; the data analysis and prediction module is responsible for mining and analyzing the historical data stored in the data storage module, establishing a prediction model and predicting the future use condition of the dust removal mechanism; the optimization control strategy module is responsible for automatically adjusting operation parameters of the dust removal mechanism according to an output result of the data analysis and prediction module; according to the invention, the data analysis and prediction module performs deep mining and analysis on historical data by using LSTM, automatically identifies rules and trends, establishes a prediction model, and discovers possible problems and risks of the dust remover in advance.

The invention belongs to the technical field of computer technology server data processing, and discloses a method and a system for generating observable data through lightweight collection of WEB container logs. According to the method, a mode of expanding a filter of a WEB container is adopted, a user-defined filter is added to generate data in a set format, and the data is output to a log file; the method comprises the following steps: extracting data in a log, processing the data, and then calling a log storage module to store the data in a storage; creating an index according to the label, and maintaining a mapping relationship between the index and the original log content; and converting the log data into an observable view by utilizing the maintained index and data file storage structure. According to the method, lightweight design serves as the core, logs serve as carriers of original data, the resource cost of the data from generation, collection to display is reduced, the observability requirement is met, and the provided data can meet aggregation display of common various dimension index data.