140 results about "Datafication" patented technology

The invention relates to the technical field of electric power management and control, and discloses an electric power BIM type data GIS discount classification method and system, and the method comprises the following steps: 1, constructing an electric power industry exclusive classification system and semantic mapping, and building a three-stage classification frame based on a GIS and an electric power industry standard; 2, unifying a space coordinate reference and a topological relation, and verifying topological consistency between components and between the components and topography and roads through a GIS (Geographic Information System) tool; 3, multi-scale classification and dynamic LOD model generation are carried out, and LOD model details are automatically switched according to a GIS scale; 4, performing data format conversion and intelligent lightweight processing, performing lossless compression on key components, and performing simplified compression on secondary components; and step 5, performing classification verification and dynamic updating mechanism, and comparing whether BIM and GIS base map position classification is correct or not, thereby realizing data synchronization. According to a dynamic classification framework and an intelligent lightweight strategy in the power industry, the BIM model efficiently adapts to the spatial analysis requirement of the GIS, and the data fusion and application efficiency is improved.

The invention provides a machined part logistics transportation path planning management system, and relates to the technical field of data processing, and the system is used for reconstructing the spatial relationship of path nodes, splitting and combining the arrangement sequence and time sequence characteristics of the path nodes, and storing the path nodes in a database; calculating a dynamic quantitative index of a preset transportation path between a time dimension and a resource occupation dimension to obtain a time sequence tensor factor, identifying an offset track of a machined part between the preset transportation path and an actual transportation path, extracting transportation behavior characteristics between path nodes, calculating a time sequence disturbance degree of transportation path offset to a scheduling plan, and obtaining a scheduling result; the method comprises the steps of obtaining a scheduling influence coefficient, correcting a preset transportation path, adjusting the passing sequence and priority of path nodes, synchronously updating scheduling information, and carrying out linkage matching on path change information and a workshop plan to obtain linkage scheduling data. According to the invention, the whole-course data modeling and dynamic scheduling management of the transportation process of the workpieces are realized.

The invention is suitable for the technical field of crossing of material science and computer science, and provides a method and device for predicting the thermal conductivity of a composite material, and the method comprises the steps: obtaining the datamation structure characteristics of a to-be-predicted composite material microstructure; inputting the datamation structure feature into a pre-trained machine learning prediction model, and outputting a predicted macroscopic physical performance value by the machine learning prediction model; wherein the machine learning prediction model is obtained through training by utilizing a structure-performance database, the structure-performance database comprises a plurality of data pairs, and each data pair comprises a datamation structure feature representing the microstructure of the composite material; and a predetermined macroscopic physical performance value corresponding to the digitized structural feature. Therefore, when the performance of the composite material is predicted, the calculation efficiency and the prediction accuracy can be considered.

The invention relates to the technical field of geographic information, in particular to a territorial transaction dynamic monitoring and analysis system based on multi-source data fusion, which comprises a data integration and storage unit, a knowledge graph construction unit, a real-time verification unit, a trusted transaction verification unit and a dynamic monitoring and decision support unit. According to the method, heterogeneous data are integrated through a multi-modal data lake architecture, space-time reference unification is carried out, a transaction element association network is constructed by utilizing a knowledge graph technology to generate a dynamic verification rule, and real-time compliance filtering of a transaction process is realized in combination with an Flink flow processing engine; and transaction price rationality verification and subject correlation analysis are completed by means of an improved isolated forest algorithm and a graph convolutional network, and evidence storage is performed based on a block chain technology, so that full-process intelligent management of land transaction data, accurate identification and prevention and control of risks, and efficient and datamation support of supervision decision are realized.

The invention relates to the field of strong wine detection, and discloses a strong wine visual non-target metabonomics origin traceability method, which comprises the following steps: firstly, collecting strong wine original data, digitizing and outputting the collected strong wine original data to obtain strong wine output data; performing preliminary analysis by using a clustering analysis method to obtain first analysis data; performing secondary analysis on the first analysis data by using a principal component analysis mode to obtain second analysis data; and finally analyzing the second analysis data by partial least square discriminant analysis or orthogonal partial least square discriminant analysis, and screening, comparing and identifying the characteristic compounds to obtain the non-target metabonomics origin traceability place of the strong wine. According to the method, the problems that a non-target metabonomics traceability technology easy to visually display does not exist in the prior art, and a standardized operation instruction integrating efficient pretreatment, non-target screening, rapid traceability, accurate confirmation and visual display does not exist are solved.

The invention belongs to the technical field of constructional engineering, and particularly relates to an intelligent special construction scheme recommendation terminal based on an information network, and the recommendation terminal comprises a scheme compiling and review module which is used for carrying out the retrieval and matching of a related standardized technical scheme template through inputting a keyword, and intelligently assisting a scheme compiling worker to compile a construction scheme online; the technology online disclosure module is used for generating and approving second-level and third-level technical disclosure and implementing management and control; and the scheme implementation module is used for performing key process management and risk point monitoring through an intelligent construction site and a BIM technology, and ensuring datamation and visual management in a scheme implementation process. According to the intelligent special construction scheme recommendation terminal based on the information network, management and control are carried out around the whole chain of the technical scheme, the whole process management and control of the whole technical scheme are associated for management, the process can be traced, data can be archived, a global technology whole process management supporting platform is built, and the informatization and digitization level of the whole process of technology management is improved.

The invention relates to the technical field of intelligent traffic, and discloses a highway toll station traffic efficiency evaluation system and method based on multi-source time sequence data, and the system comprises a data analysis module, a preprocessing module, a feature processing module, a dual-model evaluation module and a grading evaluation module. The method is applied to the system. The method focuses on expressway toll station passing efficiency evaluation to form a multi-source time sequence data driven dual-index evaluation system, realizes real-time accurate evaluation of the toll station operation state, provides scientific and datamation decision basis for operation management, and effectively solves the problems of insufficient data fusion, monotonous evaluation standard and the like of traditional manual monitoring.

The invention relates to the technical field of space planning analysis, in particular to a land space planning analysis system based on big data, which comprises a boundary discrimination module, a purpose offset module, a coordination analysis module, a change identification module and an ownership selection module. According to the method, an efficient spatial information circulation and feedback chain is constructed by combining boundary space structure extraction, use weight distribution mapping, population use collaborative feature analysis, resource configuration change trend tracking and an ownership affiliation unit optimization mechanism; global linkage judgment of core elements such as spatial forms, purposes, population and resources in a complex territorial structure is achieved, the whole-course quantitative perception ability of planning and management is enhanced, land purpose optimization, resource allocation dynamic balance and accurate orientation of ownership relations are promoted, data transparency of a space governance link and continuity of a decision closed loop are improved, and the space governance efficiency is improved. Flexible adjustment and fine management of a spatial pattern in a multi-dimensional scene are supported, and the datamation and intelligence level of a territorial space treatment system is enhanced.

The invention provides a three-dimensional sedimentary facies modeling method and device based on planar graph constraint, and the method comprises the steps: loading a sedimentary facies graph and a thickness graph to a three-dimensional space, projecting a planar graph to an oil reservoir grid through space coordinate transformation, and coarsening the planar graph into an oil reservoir grid surface attribute; establishing a rapid sedimentary facies model by utilizing the plane sedimentary facies diagram, and establishing lithologic probability volume data by utilizing the plane thickness diagram and through coKriging interpolation; and the logging sedimentary facies data serve as hard data, the rapid sedimentary facies model serves as spatial constraint, the probability body serves as trend constraint, and a sequential indication simulation algorithm is utilized to generate the sedimentary facies model. According to the three-dimensional sedimentary facies modeling scheme based on the planar graph constraint provided by the invention, information such as the logging facies, the planar facies and the thickness graph is comprehensively utilized, the understanding of geologists can be introduced between wells, the problems of mathematics and datamation of a conventional method are solved, and the precision of a sedimentary facies model is improved.

The invention discloses a real-time acupuncture point mapping method based on a bone degree deflection method and a human body posture key point model, and relates to the technical field of traditional Chinese medicine digitization. According to the real-time acupuncture point mapping method based on the bone degree discount method and the human body posture key point model, acupuncture point coordinates are calculated by combining the standard bone degree discount proportion with the objective distance between the human body posture key points, traditional empirical positioning is converted into datamation and standardization calculation, personal errors are reduced, BMI parameters are introduced to formulate a BMI interval correction table, and the real-time acupuncture point mapping accuracy is improved. The three-dimensional coordinates of the acupoints are accurately corrected through the coordinate correction coefficient, it is ensured that acupoint mapping of users of different body types is highly matched with the actual subcutaneous position, the purpose of improving the acupoint positioning effect is achieved, a corresponding acupoint mapping template is selected according to the judgment result of the human body orientation, a real-time AR picture is generated in an AR superposition rendering mode, and the user experience is improved. And real-time mapping of human body acupuncture points is realized.

The invention discloses an old building reconstruction design method and system based on BIM and real-time monitoring, and relates to the field of old building reconstruction design, and the technical scheme is that the method comprises the steps: constructing a three-dimensional observation environment, carrying out the multi-stage three-dimensional collection of a to-be-reconstructed building, and obtaining observation data with unified coordinates and time stamps; performing stage comparative analysis on the observation data, and performing space matching and data integration under BIM constraint to form three-dimensional time sequence information oriented to each building component; based on the three-dimensional time sequence information, establishing a historical memory model under component identifiers of the BIM model, and extracting a time sequence evolution rule of deviation and defects of each component; and according to a time sequence evolution rule, establishing a transformation evaluation model, comprehensively analyzing the safety, durability and use functions of each component of the building, and generating a transformation design scheme. The method has the beneficial effects that through multi-period three-dimensional acquisition and BIM fusion analysis, the whole-process datamation and intelligent management of old buildings from state monitoring to reconstruction design is realized.

The invention discloses an Internet-based intelligent human resource management method and system, and relates to the technical field of intelligent human resource management, and the system comprises an automatic recruitment subsystem, a performance management subsystem, an employee service management platform, an intelligent optimization adjustment module, and a personnel data management module. The automatic recruitment subsystem is used for selecting and collecting data information of applicants meeting company post requirements, screening the data information and then automatically arranging interviews, inputting the applicants according to interview results, and arranging corresponding skill training according to personal skill information of the applicants. According to the intelligent human resource management system, datamation and intelligentization of various businesses of human resource management are realized, the operation process is simplified, and the management efficiency is improved; through real-time management of employee information, the employee condition can be mastered more accurately, human resources are reasonably allocated, the overall competitiveness of an enterprise is improved, the diversified requirements of modern enterprises in the aspect of human resource management are met, and the management efficiency and the decision quality are improved.

The invention provides an enterprise data analysis method, a computer readable storage medium and terminal equipment, and relates to the technical field of electric digital data processing, and the method specifically comprises the steps: obtaining enterprise economic production abnormal data and related financial statement data; marking abnormal events related to process change and equipment maintenance cost to form a first screening set, and extracting additional cost data and economic loss indexes; comprehensively analyzing the cost to generate an initial loss coefficient, and collecting a benefit evaluation index to generate an initial profit coefficient; and comparing and analyzing the two, calculating a loss adjustment index, and comparing the loss adjustment index with a preset threshold value to execute a corresponding strategy. Through the three-layer system of'initial loss coefficient-initial profit coefficient-loss adjustment index ', the economic loss and profit increase degree of the abnormal event is quantified, full-dimension profit and loss comprehensive balance is realized, a datamation basis is provided for decision making of enterprise process change, equipment maintenance and the like, and fine management of economic activities is facilitated.

The invention discloses an intelligent management system and method for rubber production, and the system comprises a system user interface, a business process management module, a yield calculation service center and a resource library, and the data output end of the system user interface is connected with the data input end of the business process management module. The data output end of the business process management module is connected with the data input end of the yield calculation service center, the data output end of the yield calculation service center is connected with the data input end of the system user interface, and the yield calculation service center comprises an incoming material management module, a discharging management module, a yield calculation module and a production progress management module. And the yield calculation module is in data connection with the resource library. The invention aims to reduce the dependence on a large amount of manpower, reduce the labor cost, simplify the management process and improve the production efficiency; through real-time automatic data acquisition, storage and analysis, a complete production data chain is established, and an enterprise is helped to carry out accurate monitoring and datamation management on each link from raw materials to finished products.

The application discloses a basketball training effect evaluation method and system based on data analysis, relates to the technical field of training effect evaluation, collects physiological index data and establishes a first time axis, establishes a pass network and a defense cooperation network and establishes a second time axis, calculates pass practical effect data and defense cooperation practical effect data according to the pass network and the defense cooperation network, carries out correlation analysis on the data, outputs correlation analysis results, carries out screening according to the correlation analysis results, outputs screening results and generates an evaluation result signal, the application combines physiological indexes and practical effect data, comprehensively evaluates the basketball training effect, accurately locates training requirements, provides personalized guidance, improves training efficiency and quality, objectively reflects the training effect through data analysis, reduces subjective judgment, promotes the scientific and data-based development of basketball training, and provides strong support for the continuous progress and innovation of basketball sports.

The application discloses an elevator full-data simulation test system, and relates to the technical field of elevator testing.The scheme comprises a multi-source data acquisition module, a digital twin modeling module, a full-scene simulation test module, a data processing and analysis module, a closed-loop optimization module and a terminal interaction module.The application realizes full-cycle multi-dimensional data coverage of the elevator, integrates mechanical, electrical, environmental, personnel and fault data, improves the completeness of test data, constructs a full-dimensional model based on digital twin technology, realizes multi-element coupling simulation, simulates various working conditions, fits actual operating conditions, iterates the simulation model, outputs optimization schemes, improves test efficiency and optimization effect, supports custom parameters, meets the test requirements of various types of elevators, does not require a physical test platform, greatly reduces test costs and shortens the test cycle, and avoids safety risks in physical tests.

The invention discloses an enterprise digital transformation scheme generation method and device, and relates to the technical field of enterprise development analysis, and the method comprises the steps: S1, constructing an industry knowledge base; s2, pre-training the large language model; s3, finely adjusting the pre-trained large language model; s4, acquiring datamation basic information and query problems of the target enterprise; s5, performing retrieval in the industry knowledge base, and generating a retrieval enhancement result; s6, splicing the enhancement result and the query problem to obtain a splicing result; s7, outputting a result by the fine-tuned large language model; by performing fine adjustment on the pre-trained large language model, the resource consumption in the fine adjustment process is remarkably reduced, and the capturing capability of the model on industry characteristics and enterprise personalized demands is improved; the problems of knowledge illusion and lag caused by the fact that a traditional scheme depends on a static template are effectively solved. And the finally output digital transformation scheme text can have stronger professionalism and scene adaptability.

The invention relates to the technical field of water pollution treatment, and discloses a multi-scale coupled drainage basin high-resolution pollution source emission list construction method, which comprises the following steps: acquiring multi-scale administrative division statistical data, and preprocessing the multi-scale administrative division statistical data to obtain multi-scale pollution source basic data; converting the basic data space of the multi-scale pollution source into gridding space distribution data of each pollution source in a target drainage basin range by utilizing a space mapping relation between an administrative scale and a gridding drainage basin scale; calculating multi-source pollution emission data based on the gridding spatial distribution data of each pollution source in the target drainage basin range; and superposing the multi-source pollution emission data on the watershed grid scale, and constructing a watershed high-resolution pollution source emission list. According to the method, accurate description of drainage basin pollution source emission and identification of key pollution units are realized, and the scientization, refinement and datamation levels of regional water environment treatment can be effectively improved.

The invention discloses an operating system based on industrial internet equipment control, which comprises an equipment information acquisition module used for acquiring basic information and fault history of equipment; an equipment fault confirmation module and a training method selection module which are used for systematically collecting basic information and fault history of equipment so as to provide accurate data support for formulating a personalized training scheme; proper training steps are automatically selected, so that the safety and pertinence of a training scheme are ensured; the training method selection module intelligently recommends the most appropriate training method according to the specific condition of the equipment, and dynamically adjusts the training intensity through the training intensity calculation unit, so that the training is more scientific and reasonable; the virtual reality training module utilizes an immersive environment and interactive training to improve the participation degree and the training effect of the equipment, and the training effect evaluation unit unifies the judgment standard through a datamation evaluation method, does not depend on experience purely, and effectively reduces the misjudgment rate.

The invention discloses an intelligent analysis and model self-iteration psychological sand table auxiliary system, which is characterized by comprising a data acquisition device, a model training platform, a session analysis platform and a back-end server to realize intelligent psychological sand table auxiliary analysis. The data acquisition device inputs acquired sand tool multi-angle images into the model training platform to train a target detection model; and the back-end server maps the output category ID of the target detection model with a preset sandy tool psychological significance knowledge base, and generates a comprehensive analysis report for reference of a consultant by using a task-supervised fine-tuned large language model. Compared with the prior art, the method has the advantages that AI recognition results and psychological knowledge are deeply fused, real-time intelligent recognition and analysis are achieved, and an end-to-end closed-loop solution from sand tool datamation, model training, sand table process panoramic recording to analysis report generation is provided for application in psychological sand table treatment auxiliary scenes.

The invention relates to the technical field of project datamation management, and discloses an engineering project digital asset management platform. The engineering project digital asset management platform comprises an acquisition module which is connected with an enterprise database to acquire project data of an enterprise; the classification module establishes a first item set and a second item set for the item data according to the item attributes and the work types; the analysis module determines the predicted working duration of each working type by using the data in the second project set; the uploading module is used for acquiring and transmitting a to-be-uploaded project official document; and the display module not only displays data in the first item set and the second item set according to the item attribute and the working type of the selected target, but also is used for acquiring the working type of the selected target and displaying the preset working duration of the working type in the second item set based on the working type. Through cooperative work of the acquisition module, the classification module, the analysis module, the uploading module and the display module, the data processing efficiency and accuracy are improved, and an effective management tool is provided for project management.

This disclosure presents an embodiment of a method and system for address and entity recognition based on a large language model and retrieval enhancement. One specific implementation of the method includes: data processing of an acquired multi-source address dataset and a point-of-interest dataset to generate a candidate entry dataset; performing a mixed retrieval on the acquired unstructured text to be processed based on the candidate entry dataset to generate a retrieval candidate entry dataset; constructing a set of instruction prompts from the unstructured text to be processed and the retrieval candidate entry dataset; inputting the instruction prompt set into a preset entity recognition model to obtain a structured entity recognition result; generating a formatted recognition result based on the structured entity recognition result; and, in response to determining that the formatted recognition result represents a successful verification result, identifying the formatted recognition result as the target entity recognition result. This implementation improves anti-interference capability, reduces dependence on labeled data, and lowers data costs.

The application belongs to the technical field of housing steel structure quality inspection data management, and specifically discloses a housing steel structure quality inspection data management system based on BIM, which comprises a data detection module, a structure analysis module, an installation analysis module, an abnormality confirmation module and an abnormality feedback terminal. The application compares the measured value of the component size with the reference value to mark the size deviation component, combines the multi-dimensional analysis of the thickness deviation and thickness distribution uniformity of the corrosion-resistant layer, and carries out two-dimensional deviation evaluation based on the mechanical strength and the protection performance, so as to ensure the structure bearing capacity of the component, thereby avoiding the corrosion of steel caused by insufficient corrosion-resistant layer. Meanwhile, the multi-dimensional deviation of the installation data, such as the position coordinates, position inclination angle, welding lap amount, welding cavity area and soldering amount, of the component and the standard data is determined, the installation deviation component is comprehensively determined, the quantitative evaluation of the steel structure installation precision is realized, and the reliability of the component installation is effectively ensured.

The invention discloses a carbonate rock distribution area soil heavy metal traceability method, and belongs to the technical field of soil heavy metal traceability, and the method comprises the following steps: (1) geological background analysis: constructing a regional association type geological background reference; (2) soil sample collection and chemical analysis: providing basic data for traceability work; (3) chemical fingerprint feature extraction: constructing a form-isotope two-dimensional fingerprint, and improving the source distinguishing precision; and (4) spatial distribution modeling and traceability: multi-dimensional data collaborative analysis is carried out, and accurate traceability is realized in combination with spatial visualization. On the basis of the geological background, the natural source reference is defined; establishing a characteristic system database by taking chemical fingerprint data as a core; the receptor model parameters are optimized, and the distinguishing ability of a natural source and an artificial source is enhanced; and the spatial distribution data is used as a carrier to verify the source spatial relevance, so that the traceability precision is effectively improved finally.

The invention relates to the technical field of wire production, in particular to a tension self-adaptive control method and system in enameled wire production, and the system comprises an initialization and matching module, a disturbance observation estimation module, a feed-forward compensation calculation module and a composite control output module. According to the scheme, intelligent initialization and rapid matching of the new production task control parameters are realized by constructing and querying the process knowledge graph. According to the method, historical optimal production experience is stored in a datamation mode, and a reference tension set value close to an optimal solution and controller parameters can be automatically provided under the working conditions of different wire diameter, speed and temperature combinations. Therefore, the debugging time after specification switching is greatly shortened, the production efficiency is improved, a control system is ensured to start to operate from a high-level starting point, and the quick response capability of a production line to multi-variety and small-batch orders is remarkably improved.

The invention relates to an electrical angle calibration method and system for a joint actuator. The method constructs an intelligent calibration closed loop that is deeply integrated with a production line management system (MES). The method comprises the following steps: scanning a product identification code and automatically preloading an optimal parameter; the actuator automatically detects the encoder signal, performs closed-loop adjustment on the gain, and records data at the same time; if the fault occurs, calling a rule base to perform multi-dimensional root cause pre-judgment and interception; after the signal is qualified, high-precision electrical angle compensation is executed, and a compensation value is locally stored and uploaded to a digital file; the system realizes self-learning and continuous optimization by periodically analyzing historical data; and finally, generating a uniquely bound full-link traceable file. The system comprises an upper computer, a joint actuator, a programmable power supply and a CAN communication module. According to the invention, full automation, intelligence and datamation of calibration are realized, the problems of low efficiency, poor consistency, dependence on manpower and the like are solved, and the production takt, quality and traceability are remarkably improved.

The invention discloses an intelligent management method and system for enterprise work plans, relates to the field of enterprise intelligent management, and can solve the problems of poor collaboration and nonstandard flow caused by information dispersion, low permission and progress management and control efficiency, no datamation risk pre-judgment and optimization mechanism in enterprise work plan management at the present stage. Comprising the following steps: determining a basic management environment of an enterprise according to an enterprise organization structure and authority system, cloud side end collaborative hardware and system operation parameters; determining a hierarchical task list according to the basic management environment and the enterprise strategic target; according to the hierarchical task list, allocating each hierarchical task to a corresponding execution main body and pushing a task notification message to the execution main body; and acquiring real-time progress data of each level of task, and performing closed-loop management on the execution process of each level of task according to the real-time progress data. The method and the device are used for intelligently managing the enterprise work plans.

The present invention discloses a data structure for a hyperspectral image fusion algorithm based on data-oriented integration, which includes the following main data layers: a low-resolution hyperspectral and multispectral input data layer; a spectral dictionary data layer; a spatial coefficient matrix data layer; and a solution space data layer representing fusion result parameters. Each data layer interacts in sequence and has global compatibility. This data structure is used in a data-based fusion algorithm for improving the spatial resolution of hyperspectral images. The algorithm optimizes the spatial coefficients based on the data attributes of the hyperspectral and multispectral images in combination with external additional data, learns the spectral dictionary using a non-negative matrix dictionary learning method, and performs algorithmic fusion on the hyperspectral and multispectral images to obtain a hyperspectral image with a target high spatial resolution.

The application discloses a similar network behavior user identification method based on an unsupervised variational autoencoder, and relates to the technical field of network security. The method is based on super-large network communication metadata, uses an unsupervised variational autoencoder model, learns deep law features of user network behaviors from massive user network flow metadata, abstracts network behaviors of users into high-dimensional vector representations of essential behavior modes, and finally identifies users by using the similarity between vectors. Specifically, the method comprises network flow metadata, network behavior statistical feature extraction, behavior feature image processing, deep learning model training, deep feature extraction and similar behavior user identification.

The application provides a water quality monitoring and intelligent control method and system based on big data, and a medium. The method comprises the following steps: monitoring a target water treatment device and extracting real-time water quality characteristic data at an inlet, processing the real-time water quality pollution degree coefficient, and determining whether the target water treatment device needs to be started; if the target water treatment device needs to be started, water quality characteristic data corresponding to a first preset time node and a second preset time node at the inlet is obtained, water quality characteristic change rate data is processed, corresponding processing is performed according to physical characteristic change rate data, chemical characteristic change rate data and biological characteristic change rate data, corresponding physical index change rate abnormality coefficient, materialized index change rate abnormality coefficient and biological index change rate abnormality coefficient are obtained, and a reverse osmosis module, an activated carbon filter module and an ultraviolet disinfection module of the target water treatment device are respectively subjected to start determination response, so that the water quality monitoring and intelligent control technology based on big data is realized.