130 results about "Dimensional analysis" patented technology

The invention discloses a dynamic feeding speed adjusting method self-adaptive to production line takt, and relates to the technical field of production line automation control, and the method comprises the following steps: 1, constructing a production line takt sensing system, setting sensing units at all key stations of a production line, and setting a plurality of monitoring points on a material transmission path of the production line; according to the invention, various sensing assemblies are arranged at key stations, various state information of materials in the process from station entering to transmission can be captured in real time in combination with monitoring points on a transmission path, and information reliability is ensured through data screening; therefore, the central processing unit can comprehensively master the actual operation condition of the production line, and firm data support is provided for follow-up adjustment. On the basis of characteristic parameters of multi-dimensional analysis, continuous correction is carried out in combination with historical data, and the defect that a traditional fixed model cannot adapt to beat fluctuation is avoided; in this way, the feeding speed can be adjusted on the basis of the current real production line takt all the time, and timeliness and pertinence of adjustment are ensured.

The invention relates to the technical field of data processing, in particular to an engineering geological survey data processing method and system, and the method comprises the following steps: obtaining hole site space positioning and lithologic boundary information, collecting a structure segment sequence, extracting resistance change direction classification disturbance behaviors, recognizing node sequence conflicts, and judging hydrological turning positions. Identifying the corresponding relation between the structural section and the water level track, and generating a structural section water level merging mapping table. According to the method, the spatial information, the lithology identification, the sampling level and the penetration resistance of the drilling structure sections are collected and serialized, disturbance identification and non-sampling section classification are performed based on the resistance change trend between the sections, and node conflicts are identified in combination with the numbering relation and the lithology combination; continuous modeling and classified merging of geological information on the spatial level are achieved, the linkage adaptability of data in a multi-dimensional analysis scene is enhanced, misjudgment interference caused by information isolation is avoided, and dynamic recognition and hydrological response analysis of a geological structure are supported.

The invention relates to a centralized heating balanced regulation and control method, device and equipment and a medium. The method comprises the steps that firstly, the heat supply area of a user and the heat use state of a neighbor are collected, the basic flow of the jet device is calculated according to an industrial standard formula, and final flow containing resistance characteristic data is obtained through secondary correction by combining a neighbor heat use state correction coefficient and an environment temperature influence factor. Extracting flow and inlet and outlet pressure difference from jet device parameters, adjusting a valve to enable the resistance proportion to reach a preset interval, calculating parameters such as unit area heat consumption by combining real-time flow and supply and return water temperature difference, generating regulation and control basic data through coupling analysis, adjusting the jet device when the regulation and control basic data reach the standard, and generating a dynamic scheme by combining a thermal load prediction model. And finally, capturing the flow pulse signal according to a fixed period to calculate a difference value, generating a valve control signal according to a threshold value, acquiring the water supply and return temperature after execution, and coupling with a dynamic scheme to generate a regulation feedback signal. By adopting the method, accurate regulation and control can be realized through multi-dimensional analysis, and the flow distribution accuracy and the heat supply balance are improved.

The invention relates to the technical field of intelligent warehousing, and particularly discloses a warehouse material identification method based on data analysis, and the method comprises the steps: collecting operation event data and material coordinate information in real time through a UHF-RFID reader-writer array and a visual positioning system, and generating an operation event time sequence; calculating a material mixing risk value, an access frequency factor and an access confusion degree index, analyzing coordinate data to detect a displacement sudden change and a boundary crossing event, generating a position anomaly degree index, fusing multiple indexes to obtain a goods allocation inspection priority score, generating an anomaly inspection instruction when the score exceeds a threshold value, and marking anomaly types such as mixing, deviation and boundary crossing. According to the invention, real-time acquisition and multi-dimensional analysis are carried out on the operation event data and the material coordinate position information of the warehouse goods allocation, and the operation event time sequence characteristics and the position dynamic change are combined to construct a quantitative index system to identify the abnormity of the goods allocation, so that accurate identification of warehouse materials and timely early warning of the abnormal state are realized, and the working efficiency is improved. Therefore, the refinement level and the operation efficiency of warehouse management are improved.

The invention discloses a data leakage early warning method, device and equipment based on buried point collection and a storage medium, and relates to the technical field of system exception monitoring, and the method comprises the steps: obtaining exception log information and historical data information sent by a buried point collection service node; performing aggregation counting on the abnormal log information according to preset time granularity to obtain abnormal quantity statistical data of each time granularity; performing transverse and longitudinal analysis on the abnormal quantity statistical data and the historical data information according to a preset transverse and longitudinal analysis strategy to obtain a comparison deviation value; and performing data leakage early warning according to the comparison deviation value. According to the method, time-sharing processing and multi-dimensional analysis are carried out on the abnormal log data of the system, so that real-time early warning and service subdivision monitoring of buried point data leakage are realized, and the reliability and fault positioning efficiency of the system are improved.

The invention discloses a multi-dimensional analysis house building health monitoring and early warning system and method, and relates to the technical field of monitoring and early warning. During operation of the system, various sensors are deployed to monitor the physical states of different materials in a building, collect surrounding environment data and transmit the data to a central processing unit in real time, and through a data fusion algorithm, real-time monitoring and early warning are achieved; the method comprises the following steps: integrating sensor data from different materials into a unified data set, preprocessing and normalizing the data, constructing a multi-material interaction mathematical model, calculating an effective stress sigma eff of a building structure, constructing a building overall health assessment model, and calculating a building health comprehensive index HI; according to the building health comprehensive index HI and the comparison result of the health index of each material and the safety threshold value, the health change of the building is detected in real time, an intelligent decision support system is provided, and building management personnel are helped to carry out long-term maintenance planning and resource optimization distribution.

The invention relates to the technical field of software testing, and discloses an agent-based multi-dimensional test sample automatic generation method and system.The agent-based multi-dimensional test sample automatic generation method comprises the steps that code changes are captured, interface definitions are extracted, and multi-source data are fused for consistency verification; constructing a multi-dimensional dependency graph and analyzing the change influence to obtain an associated interface list; generating a multi-dimensional test scene; performing parameter traceability and consistency derivation, and initializing test data and environment to obtain a complete test data set; generating a use case code, and performing hierarchical optimization and executable verification; test arrangement optimization and automatic execution are carried out, and faults are monitored and diagnosed in real time; carrying out multi-dimensional analysis and defect identification, dynamically evaluating the value of a test case and optimizing a test strategy to obtain a comprehensive test report; according to the invention, full-process automation of test case generation is realized, the test efficiency and quality are improved, and the test maintenance cost is reduced.

The invention discloses a hydraulic engineering management and control system and method based on digital twinning, and relates to the technical field of digital twinning, and the method comprises the steps: firstly collecting and preprocessing channel condition data in real time, then comprehensively processing the data to obtain a sediment deposition factor and a congestion prediction factor, and analyzing whether sediment deposition exists according to the sediment deposition factor and the congestion prediction factor; if yes, whether the channel is congested or not is predicted according to the latter, if congestion is predicted, a congestion early warning is given out, and if no deposition exists or congestion does not exist, the process is ended correspondingly or prediction continues. The method combines flow velocity and flow direction abnormal parameters to form sediment deposition factors, bypasses underwater direct detection bottlenecks by means of digital twin modeling and simulation algorithms, improves sediment deposition judgment accuracy through multi-dimensional analysis, constructs congestion prediction factors based on a standard and actual water flow difference value and the flow direction abnormal parameters, and performs threshold exceeding early warning. The blocking risk is recognized in advance, and time is won for hydraulic engineering maintenance regulation and control.

The invention provides a method for predicting the working failure rate of a railway vehicle relay, and the method comprises the steps: classifying data according to a preset dimension to generate a structured feature set, constructing a time sequence feature matrix, and defining a multi-dimensional analysis coordinate system based on the classification dimension of the feature set; determining an initial prediction constraint condition according to the relay life distribution model and the fault mode library, executing dynamic prediction simulation on the feature set based on the time sequence feature matrix, simulating degeneration behaviors of the relay under various working conditions through a state transition simulation engine, generating an initial fault rate curve, and calculating the fault rate of the relay according to the initial fault rate curve. And finally, carrying out iterative correction on the initial fault rate curve by adopting an integrated optimization algorithm to generate a multi-dimensional fault rate prediction model. The invention further provides a system for predicting the working failure rate of the railway vehicle relay. According to the method, the adaptability and accuracy of prediction are greatly improved, and the degeneration behavior of the relay under the actual complex working condition can be simulated more truly.

The invention discloses a stratigraphic range constrained sequence modeling method, which relates to the technical field of three-dimensional geologic modeling, and comprises the following steps: preparing data including drilling data, regional geologic map data and a regional DEM, standardizing the drilling data including a standard stratigraphic table, a drilling basic information table and a drilling layered information table, the format of the form is unified as. Xlsx and a standard stratum table, the standard stratum table records the lithology of the whole stratum, and arrangement is carried out from top to bottom according to the new-to-old relationship; according to the sequence modeling method based on the stratum range constraint, the modeling boundary of each stratum is subjected to forced constraint, sequence modeling is carried out by using the stratum range constraint, the distribution condition of each stratum in a modeling area can be subjected to forced constraint, and meanwhile, modeling is carried out by combining drilling data and area elevation data, so that the model is finer, and the modeling efficiency is improved. And the error between a section cut through three-dimensional analysis of a sectioning model and the like and an original section is small.

The invention discloses a blasting construction harmful effect control method and system, a medium and a product, and relates to the field of engineering construction. The method comprises the steps that a three-dimensional analysis model is constructed according to geologic structural plane data of a to-be-blasted area and spatial orientation data of a protected object, and a target area where the flying stone main throwing direction conflicts with the orientation of a vibration sensitive area is recognized based on the three-dimensional analysis model; constructing a blasting sequence according to the spatial range of the target area, the geologic structural plane occurrence and a preset safe throwing sector area; coupling simulation is conducted on the blasting sequence through the blasting dynamics simulation model, whether the flying stone throwing track and the vibration distribution meet the preset safety requirements or not is verified, and if not, blast hole grouping or detonation time difference is adjusted, and iterative optimization is conducted till a final blasting scheme meeting the flying stone throwing track and the vibration distribution at the same time is obtained; and outputting a final blasting scheme. By implementing the technical scheme, the harmful effect of blasting construction can be effectively controlled.

The invention provides a hydraulic engineering prevention and control information digital management method and system, and the method comprises the steps: firstly obtaining a real-time data stream, extracting overflow risk features through employing a data fusion technology, and then screening out a core feature index from the overflow risk features through constructing a feature weight analysis logic; then, performing anomaly detection on the core characteristic indexes, and when an abnormal index is detected, generating a dynamic risk distribution diagram corresponding to the abnormal index and determining an influence range so as to predict a change trend of the abnormal index in a future target time period in a risk distribution area and lock a risk evolution time interval; and finally, carrying out comprehensive risk analysis based on the abnormal indexes and the initial characteristic indexes associated with the abnormal indexes, and generating standardized early warning information for outputting. According to the method, real-time monitoring, multi-dimensional analysis and accurate early warning of the overflow risk of the target reservoir are achieved, the response efficiency of water conservancy risk early warning is improved, and then the safety management level and the disaster prevention and reduction capacity of the water conservancy project are effectively improved.

The invention discloses a graded blasting construction method for a shallow-buried soft rock tunnel sensitive section. The method comprises the steps that measuring points are arranged in a tunnel chamber, a ground surface non-cavity section and a cavity section, and blasting vibration data are obtained; peak vibration velocity prediction models are established in a partitioned mode, an attenuation model is adopted in a chamber, a correction term is introduced into a non-cavity section of the earth surface to correct the attenuation model, and a multivariable model is established for the cavity section through dimensional analysis by integrating the horizontal distance, the elevation difference, the explosive quantity, the rock mass density and the tensile strength; determining a ground surface vibration velocity safety threshold, and quantifying a cavity vibration velocity amplification coefficient and an influence range thereof; based on the peak vibration velocity probability distribution and a preset safety level, establishing a safe dose prediction model and a safe range model; and dividing control areas according to the model, and implementing graded construction. According to the method, the vibration propagation law can be accurately described, the cavity amplification effect can be quantified, dynamic prediction of the blasting safety explosive quantity and range is achieved, and disturbance of blasting vibration to surrounding rock is effectively controlled through hierarchical management and control.

The invention discloses a gas-liquid two-phase flow measurement method based on a bent pipe and an acoustic emission technology, and belongs to the field of gas-liquid two-phase flow measurement. The method comprises the steps that the average liquid holdup HL of two-phase flow in a pipeline is measured, and the instantaneous speed Vc of a gas phase and a liquid phase passing through the 45-degree section of the bent pipe is calculated; identifying a gas-liquid two-phase flow pattern in the pipeline; taking the Vc, the HL, the apparent liquid velocity VSL and the apparent gas velocity VSG as variables, and adopting a dimensional analysis method to propose a correlation between the Vc and the VSL and between the HL and the VSL and between the VSL and the VSG according to different flow patterns; calculating an effective voltage value RMS of the acoustic emission signal, and establishing a correlation between the RMS and the VSL and VSG; fitting parameters in the correlation formula; newly collected Vc, HL and RMS are input into the fitted correlation formula, VSL and VSG are output, and therefore measurement of the gas-liquid two-phase flow is completed. Compared with a single-phase metering method after separation commonly used in the oil and gas industry, the device has the advantages of being simple in structure, low in measurement cost, capable of achieving real-time measurement, non-invasive and the like.

The present application relates to the technical field of geological data processing, and more particularly to a low-permeability reservoir geological dessert prediction method and system and a medium. The method comprises the following steps: obtaining low-permeability reservoir geological data; preprocessing the low-permeability reservoir geological data to obtain standard low-permeability reservoir geological data; performing multi-dimensional feature recognition on the standard low-permeability reservoir geological data to obtain multi-dimensional geological feature data; extracting key low-permeability reservoir information from the multi-dimensional geological feature data to obtain key low-permeability reservoir information; and extracting low-permeability reservoir cores from the key low-permeability reservoir information to generate low-permeability reservoir core data. Through data processing technology, pattern recognition technology and machine learning technology, the present application realizes multi-dimensional analysis of low-permeability reservoir geological features and correlation analysis in combination with the seismic characteristics of low-permeability reservoirs, thereby improving the accuracy of low-permeability reservoir geological dessert prediction.

The application discloses a kind of lake total phosphorus concentration spatio-temporal evolution and driving factor identification method, and the application relates to water environment monitoring technical field, constructs water body, sediment and in and out lake river multi-medium linkage analysis system, carries out multi-scale spatio-temporal evolution analysis and multi-path mechanism quantization, realizes the accurate identification of scene main control driving factor, and the standardization analysis process is formed by verification solidification, the application has the advantages that by constructing water body, sediment and in and out lake river multi-medium linkage full-dimensional analysis system, simultaneously integrate multi-source spatio-temporal data covering full lake area function partition, complete hydrological year cycle, carry out the coupling analysis of multiple time scales and multiple spatial dimensions, break through the industry common defects that the evolution law of total phosphorus concentration is not comprehensive, data is insufficiently representative, and the whole chain variation characteristics cannot be clarified, caused by the fact that the prior art only focuses on single medium of water body, uses scattered point position low-frequency monitoring data.

The invention provides a service sheet auditing and scoring method and equipment based on an engineer score and a return visit result, and relates to the field of service item management. The method comprises the following steps: performing multi-dimensional analysis on a preset contract text to obtain a plurality of service item standards; obtaining a service order and a return visit result, carrying out index extraction on the service order to obtain a plurality of first scoring indexes, obtaining a first scoring value obtained by scoring the first scoring indexes by an engineer according to a scoring standard, and carrying out index extraction on the return visit result to obtain a plurality of second scoring indexes and a second scoring value; performing weight distribution according to the index data and the score data to obtain a target distribution weight corresponding to the index data; obtaining a trigger condition, and dynamically adjusting the target allocation weight based on the trigger condition to obtain a dynamic adjustment weight; and neural network fusion processing is performed according to the dynamic adjustment weight, the index data and the score data to obtain an audit score result, so that accurate score calculation can be performed on the service sheet more comprehensively.

This disclosure proposes an evaluation method and system for auxiliary coal blending, relating to the field of coal blending technology. The evaluation method for auxiliary coal blending includes the following steps: collecting basic blending data, which includes at least coal blending information, combustion parameters, environmental parameters, and equipment status data; establishing a multi-dimensional analysis model based on the basic blending data, and analyzing the basic blending data through the multi-dimensional analysis model to obtain analysis results; generating visualization charts based on the analysis results at a preset cycle; establishing an A / B comparison analysis mechanism; inputting the blending scheme verified by the A / B comparison analysis, along with the applicable conditions of the blending scheme, into a dynamic knowledge base; and establishing a review mechanism to analyze long-term data trends and continuously optimize the multi-dimensional analysis model and the dynamic knowledge base. This disclosure achieves closed-loop management of the entire process of blending schemes, from data collection, multi-dimensional evaluation, visualization, comparison verification to knowledge accumulation and continuous optimization.

The invention provides a salt-cavern gas storage operation stability test method and application, and the method comprises the following steps: S1, measuring the volume, shape and depth data of a salt-cavern solution cavity, and building a three-dimensional analysis model according to the measured data; s2, importing the three-dimensional analysis model into FLAC 3D software, and dispersing the three-dimensional analysis model of the salt cavern cavity into a plurality of tetrahedron units; s3, determining the ground stress gradient of the location of the salt cavern cavity; a crustal stress field of the three-dimensional analysis model is determined, a three-way isobaric self-weight stress field is adopted, the lower surface of the three-dimensional analysis model simply supports and restrains vertical displacement, and four longitudinal surfaces are subjected to simply supports and restrains in the corresponding normal directions; s4, presetting salt rock and interlayer distribution in the three-dimensional analysis model according to the actual salt rock and interlayer terrain of the salt cavern cavity; and S5, calculating and simulating the static stability of the three-dimensional analysis model, and calculating and simulating the long-term stability of the three-dimensional analysis model.

The invention provides a method and device for carrying out cost optimization prediction through multi-dimensional business travel behavior analysis, and belongs to the technical field of enterprise business travel management.The method comprises the steps that business travel data are collected, cleaning, duplicate removal and entity alignment operation are carried out, and a business travel behavior data set is constructed; executing a preset query script on the business travel behavior data set, extracting characteristic indexes from preset dimensions, executing descriptive analysis, diagnostic analysis and clustering analysis, and generating a business travel behavior analysis report; and inputting the business travel behavior data set and the business travel behavior analysis report into a cost optimization prediction model to carry out business travel demand prediction, business travel price prediction and business travel travel optimization, generating an optimal travel travel scheme set, pushing the optimal travel travel scheme set to the employee user, collecting a feedback result of the employee user on the optimal travel travel scheme set, updating the business travel behavior data set, and obtaining a business travel result. And incremental training and iterative optimization are carried out on the cost optimization prediction model. Through multi-dimensional analysis and prediction, the travel cost is optimized, and the management efficiency is improved.

The application provides a power distribution network early fault recording starting feature selection method and a recording starting judgment method, and belongs to the technical field of power distribution network early fault identification. The feature selection method comprises the following steps: performing multi-dimensional analysis on the power distribution network early fault recording data, constructing a feature set, and extracting waveform morphology and time-frequency domain features; calculating fault feature benefit cost, considering the calculation complexity and fault saliency; sorting in descending order of benefit cost, and selecting the first M features as the recording starting features. The recording starting judgment method comprises the following steps: collecting a zero sequence current signal, transforming the signal by using an improved variation mode decomposition method, and extracting low-frequency components; selecting transient energy and phase plane trajectory features; extracting the transient energy and phase plane trajectory of the transformed signal based on a sliding time window, and calculating a mutation variable; fusing the Laplace distribution into a fault probability index, and setting a double threshold to trigger the recording. The recording starting method constructed by the application has higher sensitivity and adaptability, and can quickly respond to fault precursors.

The invention provides a method for constructing a bearing test distortion model of an ice-resistant structure under the action of a dynamic ice load, and belongs to the field of test similar reduced scale model design under an ice breaking load of the ice-resistant structure. The problem that in the prior art, the strain rate of a fully-similar model is dissimilar due to the scale effect is solved; a traditional distortion model design method has the problem of dissimilar energy distribution. The method comprises the following steps: establishing a fully similar model from an ice-resistant structure prototype to a geometric and plate thickness equal ratio reduced scale; establishing a plate thickness distortion reduced scale model by using the same material on the basis of the geometric similar reduced scale model; preliminarily determining a collision contact position of the thickness distortion reduced scale model; a dynamic ice load similarity criterion is applied, correction factors are deduced through dimensional analysis, and ice body parameters and collision speed of a distortion model system are adjusted, so that the ice breaking capacity and dynamic structure response are similar to those of a prototype system. The device is mainly used in the field of polar region icebreaking.

The application discloses a feature warehouse feature value monitoring method and system, relates to the technical field of feature warehouse monitoring, and comprises the following steps: analyzing historical feature warehouse record data, and acquiring the review label of each historical feature value group; the label records the situation of the feature value group and explains; multi-dimensional feature performance analysis is carried out on the historical feature value group, different dimensional feature performances are determined, a multi-dimensional feature performance group is formed, and a feature performance baseline model is constructed based on the group and the corresponding review label, which is used for representing the normal performance mode of the historical feature value; real-time multi-dimensional analysis is implemented on a real-time feature value group, data comparison is carried out with the baseline model output data, a feature deviation index is calculated, and data anomaly early warning is sent for the real-time feature value group with the deviation index greater than or equal to a preset value; and the application realizes automatic monitoring of feature data, and improves the robustness and abnormal detection precision of a machine learning pipeline.

The invention relates to the technical field of down-the-hole drill ball tooth drill bit wear measurement, in particular to a down-the-hole drill ball tooth drill bit wear value real-time measurement method and system, and the method comprises the steps: carrying out the optimization and registration of an initial three-dimensional model, and obtaining an overall wear quantized value of a down-the-hole drill ball tooth drill bit; analyzing a mapping relation between the while-drilling parameters and the overall wear quantized value, and constructing a database between the while-drilling parameters and the drill bit wear value; deriving a dimensionless variable according to a dimensional analysis method and a database, and performing combined screening on the dimensionless variable, a second-order polynomial and a cross term to determine a dimensionless variable combination influenced by drill bit wear; and substituting the dimensionless variable combination into the multiple linear regression model to establish a mathematical relationship model between the drill bit wear and the while-drilling parameters, thereby realizing the real-time measurement of the wear value of the ball tooth drill bit of the down-the-hole drill. According to the method, non-dimensional variables of the while-drilling parameters are obtained based on dimensional analysis, the model is built in combination with multiple linear regression, the wear value of the ball tooth drill bit of the down-the-hole drill is measured in real time, and construction efficiency and safety are improved.

The invention relates to the technical field of power grid project cost management and business intelligence, and discloses a project cost multi-stage intelligent analysis and examination method, system, equipment and medium, and the method comprises the steps: building a power grid project cost data warehouse, and achieving the integration and standardization of multi-source cost data; establishing an OLAP multi-dimensional analysis model, and supporting general cost comparison and key index analysis in a budget calculation stage, feasibility research estimation, preliminary design budget calculation, completion settlement three-calculation comparison, first supply material check and review list consistency check in a settlement stage; designing an intelligent decision engine based on data mining, and generating review opinions through association rules, a classification algorithm and an anomaly detection technology; and a BI visual instrument panel is developed, and multi-dimensional display, real-time monitoring and interactive analysis of the power grid cost data are realized. Through systematic application of the BI technology, deep mining, intelligent decision and visual display of engineering cost analysis are realized, and the efficiency and precision of cost review are remarkably improved.

The invention relates to a data analysis technology, and discloses a city governance data quality multi-dimensional analysis method, device and equipment, and the method comprises the steps: obtaining a to-be-analyzed data block, carrying out the quantitative analysis of the to-be-analyzed data block based on preset data dimensions, and obtaining a standardized sub-score corresponding to each data dimension; obtaining a performance feedback index of the downstream large model, dynamically adjusting the distribution weight of each data dimension by using a predefined mapping rule base according to the performance feedback index, and performing normalization processing on the adjusted weight to obtain a normalized weight of each data dimension; performing weighted summation on the standardized sub-score of each data dimension and the corresponding normalized weight to generate a final comprehensive quality score of the to-be-analyzed data block; and obtaining a quality multi-dimensional analysis result according to a preset quality partition interval in which the comprehensive quality score is located, and distributing the to-be-analyzed data block to a corresponding processing path for data processing. According to the invention, the efficiency of quality multi-dimensional analysis of urban governance data can be improved.

The application discloses a user dynamic activity degree calculation method, device and system based on ETC data, and belongs to the technical field of data analysis. The method comprises the following steps: obtaining toll data and associated consumption data corresponding to a unique identifier of a user under an ETC account of the user; aligning the two in time and space through a preset time-space correlation condition, constructing a toll-consumption event chain, and calculating a current dynamic activity degree value of a geographic node based on a time-space decay dynamic weight model; dividing the activity degree into levels according to double thresholds, rendering the levels in a differentiated visual style, and superimposing a consumption feature icon to realize visual dynamic updating. The application breaks through the limitation of single-dimensional analysis, integrates toll and consumption data, realizes accurate quantification of the activity degree through a time-space decay model, intuitively presents user behavior characteristics, improves the application value of ETC data, and provides data support for expressway operation analysis, high-activity-degree area identification and accurate decision-making.

The invention provides application of a tetrahedral structure to reduction of debris flow peak flow, a construction method of a peak flow reduction rate prediction model, a peak flow reduction rate prediction method and a peak flow regulation and control method, and relates to the technical field of debris flow treatment. According to the design, the tetrahedral structure is applied to reducing the peak flow of the debris flow. The prediction model construction method is obtained through a dimension analysis method, and the peak flow reduction rate is calculated through the prediction model. The peak flow regulation and control method is implemented based on the prediction result of the peak flow reduction rate. The method focuses on specific regulation and control of the peak flow of the mountain debris flow, exclusive application of a tetrahedral structure is adopted as the core, the regulation and control precision of disaster-causing key parameters is precisely improved, a peak flow reduction rate prediction model and method are constructed in a matched mode, multi-dimensional core parameters are integrated, the precise pre-estimation effect is scientifically quantified, and a closed-loop process from simulation optimization to field landing is achieved. The method is suitable for various disaster scenes, and takes prevention and control efficiency and engineering economy into consideration.

The invention discloses a power transformation loop reliability multi-source data fusion method, system and equipment based on a natural language processing technology and a medium, and belongs to the technical field of power transformation loop reliability, and the method comprises the steps: carrying out the intelligent management of machine account data and operation data of a power transformation loop, constructing a standardized data base, and outputting a data set; based on the data set, realizing association and integration of cross-system data through multi-dimensional feature matching, and outputting a fused data set; on the basis of the fused data set, a natural language processing model is adopted to study and judge a shutdown event affiliation loop and an event type; and based on the event type research and judgment result, performing full-dimension analysis on the operation data, completing loop state classification and shutdown statistics, and generating loop reliability operation data. According to the method, by fusing natural language processing and graph neural network technologies, intelligent management and deep semantic fusion of the multi-source heterogeneous data of the power transformation loop are realized, and the problems of poor data quality, weak relevance and the like in a traditional method are effectively solved.

The invention relates to the technical field of integrated go intelligent replaying, in particular to a go intelligent replaying system based on multi-dimensional analysis. The system comprises the following steps: acquiring a video record of a chess playing game to which a chess player belongs, determining chess pieces held by the chess player, and sequentially extracting chess piece placing images of the chess pieces held by the chess player according to a chess piece placing sequence based on the video record and the held chess pieces; determining the number of occupied point locations of the chess pieces held by the chess player and the number of occupied point locations of the chess pieces of the opponent in each chess piece placing image based on each chess piece placing image, and segmenting the chess playing period based on the number of occupied point locations of the chess pieces held by the chess player to obtain chess playing segments; determining a key hand of each chess playing segment, and obtaining a chess hand thinking coefficient corresponding to the key hand and a chess influence index of the key hand; and marking the key hands of the chess playing segments based on the chess hand thinking coefficient and the chess influence indexes of the key hands, so that the subjectivity in a go replaying system can be reduced, the replaying efficiency is improved, and the replaying feedback efficiency is improved.