427 results about "Data Adjustments" patented technology

The invention discloses a real-time behavior monitoring and dynamic optimization system for an advertisement putting strategy, and relates to the technical field of advertisement putting and user behavior analysis. A real-time multi-source user behavior data acquisition module acquires data; the distributed storage and indexing module supports fragmented storage, capacity expansion and multi-dimensional indexing; the behavior feature extraction and analysis module extracts features and identifies a time sequence rule; the putting effect evaluation module compares data through an index system and positions an effect short board; the user portrait dynamic updating module adjusts the label weight according to the latest data; the strategy optimization decision module optimizes parameters in combination with the portrait and the evaluation result; the execution scheduling module issues an instruction and monitors a state; the historical data mining and model training module is used for mining rules and iteratively training the model; and the visual interaction configuration module provides an interface and supports parameter configuration and data, effect and optimization suggestion display. According to the invention, full-scene real-time monitoring and cross-platform identity association of user behaviors are realized, and support is provided for refined advertisement marketing.

The invention provides a spatio-temporal data fusion-based power distribution network load prediction method and system, and relates to the technical field of power distribution network load prediction, and the method comprises the steps: collecting related data of a power distribution network, carrying out the wavelet transform decomposition of historical load data, obtaining a load feature matrix, constructing a hierarchical graph convolution network based on topological structure data, and extracting topological correlation features; and generating a spatial-temporal feature tensor through tensor decomposition fusion, training a depth probability prediction model adopting a variational auto-encoder structure, and adjusting prediction probability distribution in combination with environmental data. According to the method, the prediction precision is improved, a complex space-time dependency relationship can be captured, and reliable uncertainty quantization is provided.

A method may include obtaining, from a camera device, thermal image data for a steam area of a plant facility. The steam area may include a steam trap for a steam network. The method may further include obtaining plant steam data regarding the steam trap. The method may further include determining pixel data regarding the steam trap using the thermal image data and an image segmentation process. The method further includes determining various temperature values across the steam trap using the pixel data. The method may further include determining predicted steam trap data using the temperature values, the plant steam data, and a machine-learning model. The method may further include transmitting a command that adjusts one or more parameters of the steam network based on the predicted steam trap data.

The invention belongs to the technical field of robot navigation and path planning, and particularly discloses and provides a dynamic navigation planning method and system for a service robot, which overcomes the limitation of single-dimensional analysis in a complex dynamic scene by constructing a dynamic social thermodynamic diagram and deducing group dynamic intention data. The perception precision of the environment structure and the people stream situation is improved; a linkage mechanism among a dynamic social thermodynamic diagram, individual behavior characteristics and path planning is established, and a social cost function is generated to optimize a navigation path according to the traffic efficiency and social etiquette of group future dynamic vectorization evaluation; the actual influence of the navigation behavior of the robot on the environment is monitored in real time, and a planning strategy is adjusted in combination with feedback data, so that the adaptability of the navigation decision and the continuous improvement of the environment acceptance degree are realized.

A system for vendor deduplication. The system creates embeddings of entity names and creates an initial entity graph comprising entities whose embeddings are related. The initial entity graph includes nodes representing the entity names linked together by edge weights indicating their similarity. The system adjusts the edge weights between the entity names according to transactional data related to the entities to create a final entity graph and merges the entity names as a common entity based on the adjusted edge weights in the final entity graph.

The invention relates to the technical field of road engineering detection, in particular to a road disease recognition method and system based on electromagnetic waves and photographic imaging, and the method comprises the steps: firstly obtaining electromagnetic wave detection data and photographic imaging data of a road region, then synchronously detecting the distribution position and thickness of a road thin water film, generating a rasterized water film feature map, and finally obtaining a road disease recognition result. Then, according to the water film characteristic pattern, dynamically correcting bimodal data interference, adjusting a reflected wave amplitude value and a time domain delay parameter for electromagnetic wave detection data, compensating a gray difference and an edge gradient value for photographic imaging data by applying a local reflection suppression algorithm, and finally, fusing the corrected data and associating the state of the water film characteristic pattern to eliminate coupling misjudgment. The system comprises a data acquisition unit, a water film detection unit, a double-domain correction unit and a fusion decision unit, the problem of insufficient identification precision caused by a thin water film is solved, the road disease identification precision is improved, and a reliable basis is provided for road maintenance.

The invention relates to the technical field of power plant equipment maintenance, in particular to an industrial internet power plant equipment predictive maintenance system based on digital twinning. The system comprises an equipment data acquisition unit, a digital twinning construction unit, a state prediction unit, a maintenance strategy generation unit and a dynamic adjustment unit. The equipment data acquisition unit acquires multi-equipment real-time operation data, and a multi-dimensional data set is formed through time alignment and space registration; the digital twin construction unit performs sparse reconstruction on the data set to obtain target data and abnormal indication data; the state prediction unit generates a health state prediction result containing the remaining service life and the fault occurrence probability in combination with the target data, the historical maintenance records and the operation parameters; a maintenance strategy generation unit generates a scheme containing a maintenance priority and a time window; the dynamic adjustment unit adjusts the scheme according to the abnormal indication data. The system realizes comprehensive monitoring, accurate prediction and dynamic maintenance of equipment.

The invention discloses a traditional Chinese medicine grinding control system, which relates to the technical field of traditional Chinese medicine grinding control and comprises a medicinal material characteristic sensing module, an intelligent calculation analysis module, a dynamic execution adjustment module, a multi-mode optimization control module and a system coordination updating module. The medicinal material characteristic sensing module collects physical and texture characteristic data of medicinal materials; the intelligent calculation and analysis module fuses the medicinal material processing knowledge base and historical grinding process data to generate initial grinding control parameters; the dynamic execution adjustment module adjusts the operation parameters of the grinding mechanism in combination with the real-time grinding state data; the multi-modal optimization control module monitors the deviation between actual quality parameters and target quality parameters of powder, and a self-adaptive decision algorithm is used for optimizing regulation and control parameters of a grinding area; the system coordination updating module collects whole-process data and performance index evaluation and generates a system optimization instruction, and the instruction corresponding module adjusts the rotating speed and pressure parameters of a grinding area of the vertical grinding machine. According to the system, intelligent and precise control over medicinal material grinding is achieved, and the stability and consistency of the grinding quality are improved.

The invention provides an interactive control system and method for a power module and an overcharge pile, a storage medium and a computer program product, and the method comprises the steps: obtaining a charging control parameter according to the input time sequence state data of a battery through a charging control parameter prediction model based on deep learning; generating a power instruction according to the charging control parameter and sending the power instruction to the power module; after the power supply module executes the power instruction, an instruction execution result and battery state data are transmitted back to the overcharge pile main control software; and the overcharge pile main control software adjusts the weight of the charging control parameter prediction model according to the received data or regenerates a power instruction based on the latest battery time sequence state data. According to the invention, the charging time can be shortened, the risks of overheating, overcharging and the like can be prevented, different battery states and complex working conditions can be adapted, and the real-time requirement of an overcharging scene on a control instruction and state data can be met.

The invention discloses a vision and laser collaborative assembly positioning method and system, and belongs to the technical field of industrial automation control, and the method comprises the steps: obtaining stereo image data and positioning light spot data, generating multi-source input data, and carrying out the analysis and matching, calculating initial pose estimation, and carrying out the positioning of the three-dimensional image data and the positioning light spot data. Generating a visual positioning result, comparing the visual positioning result with theoretical position data, correcting deviation, generating cooperative positioning data, combining a standard operation process file, generating a visual guiding scheme containing a display instruction and a laser control instruction, synchronously executing the display instruction and the laser control instruction, realizing assembly guiding, and performing assembly. And meanwhile, the assembly process is monitored in real time to generate operation progress data, and the detailed degree of the visual guide scheme is adjusted in combination with historical operation data. According to the method, dynamic compensation and cooperative positioning are carried out by acquiring the three-dimensional image and the laser spot data, and a virtual-real combined guiding scheme is adjusted in real time, so that high-stability self-adaptive assembly process control can be realized.

The invention provides an anti-backflow system, and the system comprises a storage and charging integrated cabin which is used for storing electric energy; the storage and charging integrated cabin comprises a charging pile, an energy storage module, an intermediate relay and a switch which are electrically connected; the control module is configured to obtain static data and dynamic data; determining the output power of the energy storage module and the charging pile based on the static data and the dynamic data; acquiring power supply data; and based on the power supply data, adjusting the power supply condition among the energy storage module, the charging pile and the commercial power, and determining the opening or closing of a first switch node, a second switch node, a third switch node, a fourth switch node, a fifth switch node and an anti-countercurrent contactor, so as to solve the problems that the utilization rate of distributed energy is greatly reduced due to a current anti-countercurrent control scheme; and equipment loss is accelerated, the service life of equipment is shortened, and the operation and maintenance cost is increased.

The invention discloses an out-of-band management method and device based on a solid state disk, and relates to the technical field of solid state disks, and the out-of-band management method comprises the steps: obtaining an original signal from a system management bus channel or a PCIe expansion channel in a solid state disk system; determining an original command corresponding to the original signal; analyzing the original command into a target command, and executing the function of the solid state disk system based on the command type of the target command to obtain an execution result; according to the execution result, a response message adapted to the system management bus channel or the PCIe extension channel is generated, and the response message comprises operation data of the solid state disk; and adjusting the priority of the target command by using the operation data, and through the technical scheme disclosed by the invention, the problems of low efficiency and poor flexibility of out-of-band management in related technologies are solved, and the out-of-band management efficiency and flexibility of the solid state disk are improved.

The invention relates to the field of communication, and discloses an intelligent traffic scheduling optimization method, device and equipment and a storage medium, and the method is used for 5G network intelligent traffic scheduling optimization. The method comprises the following steps: receiving a service request, analyzing the service request to obtain a 5G standard service type, an application scene and a 5G network slice identifier, then obtaining an SLA parameter corresponding to the service request and a candidate link required by service transmission, and converting the SLA parameter into an SLA preference vector; acquiring global data of the candidate link, and predicting by using the network state prediction model to obtain a predicted network state of the candidate link; the SLA preference vector is used as optimization target guidance, the predicted network state is used as a constraint condition, and a global optimization routing strategy is calculated through a multi-target optimization algorithm; and generating a control message packet based on the global optimization routing strategy, issuing the control message packet to the network forwarding equipment, and adjusting parameters of the network state prediction model and the multi-objective optimization algorithm based on the actual performance data after execution.

The embodiment of the invention provides an urban low-altitude wind field prediction method based on deep learning and related equipment, and belongs to the technical field of wind field prediction. The method comprises the following steps: acquiring three-dimensional building contour data and wind speed and direction meteorological data of a city target area; according to the three-dimensional building contour data, three-dimensional cylindrical building geometric feature reading convolution calculation is carried out on a single or multiple predefined urban low-altitude wind field prediction target points within the height range of 0-120 m, and feature vectors of all the prediction target points are obtained; feature vector ranking is adjusted based on wind speed and wind direction meteorological data, the feature vector ranking is input into a trained deep learning wind field prediction model for wind field prediction, and initial wind field data output of a single or multiple prediction target points is obtained; and synthesizing the plurality of initial wind field data outputs to obtain three-dimensional wind field prediction of the urban target area. According to the embodiment of the invention, the urban low-altitude wind field prediction efficiency can be improved.

The invention discloses an intelligent optimization control method and system for a compressed air energy storage power station, and relates to the technical field of power grids, and the method comprises the steps: S1, building a system model corresponding to the compressed air energy storage power station, and collecting data; s2, training a reinforcement learning agent, and learning to obtain an optimal control strategy capable of adapting to the operating environment of the compressed air energy storage power station; s3, using the prediction model to predict the future operation state of the compressed air energy storage power station, and optimizing the control sequence; and S4, executing real-time control operation, adjusting a control strategy according to feedback data, and performing dynamic optimization control. According to the method, reinforcement learning and model prediction control are organically combined, a reinforcement learning agent is introduced, a control strategy is continuously learned and optimized, and adaptive adjustment is quickly made according to factors in multiple aspects such as the current generation power, the power load, the energy storage state and the environment in the face of real-time fluctuation of the new energy generation power.

The invention provides a vehicle-gauge-level dynamic equalization SerDes system and a working method, and belongs to the technical field of high-speed serial communication, and the method is characterized in that the system comprises an environment feedback module which collects temperature, cable impedance and common-mode noise data in real time; the dynamic equalizer is used for adjusting parameters of the pre-emphasis, the continuous time linear equalizer and the decision feedback equalizer based on the data acquired by the environment feedback module; the link health monitoring unit is used for counting the bit error rate through a hardware counter and triggering a self-repairing process; and the repair controller is used for executing a self-repair process which comprises redundant channel switching, transmission rate degradation and link retraining operation. According to the invention, the hardware-level environment adaptive equalization and millisecond-level self-healing capability of the SerDes link can be realized, and meanwhile, the redundancy design cost is reduced.

The invention relates to a vehicle control method and device, electronic equipment and a vehicle. The method comprises the steps of obtaining road data and real-time meteorological data in a current driving path of a target vehicle; judging whether a road in front of the target vehicle is a crosswind area or not based on the road data and the real-time meteorological data; when it is judged that the road in front of the target vehicle is the crosswind area, influence intensity data of the crosswind area is determined; when it is detected that the target vehicle is about to enter the crosswind area, vehicle parameters of the target vehicle are adjusted according to the influence intensity data; when it is detected that the target vehicle enters the crosswind area, vehicle state data of the target vehicle influenced by crosswind in the crosswind area are obtained, and vehicle parameters of the target vehicle are adjusted according to the vehicle state data. According to the embodiment of the invention, the method achieves the precise judgment of the crosswind region, carries out the vehicle parameter adjustment under the condition that the vehicle does not enter the crosswind region, and avoids the control delay of the vehicle.

The invention relates to a mask generation method and device, computer equipment, a readable storage medium and a program product. The method comprises the following steps: after obtaining first matrix data, loading the first matrix data to a first memory in response to a target access instruction to adjust a data arrangement mode of the first matrix data to obtain second matrix data; determining a multiplication result matrix of the second matrix data, and statically distributing the multiplication result matrix to a second memory corresponding to the corresponding calculation thread; and determining a mask register according to the thread identifier and the mask boundary of the calculation thread. In the process of loading the first matrix data to the first memory, the complex high-dimensional tensor first matrix data is adjusted into a regularly linearly arranged two-dimensional matrix, so that optimization and recombination of data layout are realized, a large number of access instructions across calculation units are prevented from being generated during data access in the mask calculation process, and the data access efficiency is improved. The utilization efficiency of the memory broadband is improved, and the overall calculation performance of the chip is improved.

The invention relates to the technical field of analogue simulation, in particular to a plate shape control parameter optimization method based on digital twinning, which comprises the following steps of: constructing a material microscopic performance digital twinning body, calculating the offset of a physical neutral layer through virtual straightening rehearsal, deducing a non-uniform differential curvature target, carrying out reverse iteration, and outputting a global optimal parameter of a straightening machine. And the fracture mechanical model is used for driving the digital twin to perform virtual simulation of shear crack propagation, burr and edge collapse data are calculated, and the angle and surface prestress parameters of a shear knife are adjusted. And the production line laser point cloud and the visual image are fused to construct geometric morphology digital twin bodies, a defect topology fingerprint is generated, the two digital twin bodies are coupled by running a moving target spot interception algorithm, and the optimal transverse track and the local rolling reduction of the stress release roller are planned. According to the method, through multi-physics field virtual simulation and closed loop verification, collaborative optimization of global straightening, dynamic shearing and local repairing in high-strength steel plate production is achieved.

The invention relates to an electric power document analysis and generation method and device based on a large language model and a medium, and the method calls the large language model to execute the following steps to perform document analysis and generation: obtaining a to-be-processed electric power document, and performing structured analysis and feature extraction to obtain first structured data; screening an optimal template which is most matched with the power document from a template library on the basis of the first structured data; and reading second structured data corresponding to the optimal template, verifying the second structured data, adjusting chapter titles according to the first structured data and synchronously updating writing cue words after verification is passed, outputting a document adjustment result, performing format standardization, and generating a final templated power document. Compared with the prior art, the method has the advantages of high power document template generation efficiency, high matching precision, self-adaptive adjustment capability and the like.

The invention discloses a firmness safety assessment method and system for a power transmission line iron tower based on computer assistance, and belongs to the technical field of computer-aided engineering, and the method comprises the steps: forming a multi-source data set through fusing sensor, environment and historical maintenance data, and generating preprocessing data after time sequence alignment and filtering processing; and adjusting finite element mechanical parameters based on the data, constructing a dynamic parameterized finite element structure, and performing simulation to obtain physical index data. A preliminary risk index is generated by combining a historical fault library and risk rule matching, then an environment severity degree index is introduced, a comprehensive state index is obtained through calculation, hierarchical feature extraction and multi-scale fusion analysis are carried out, and finally risk early warning information is output. According to the technical scheme, the dynamic parameterization finite element structure is constructed and checked, and comprehensive evaluation and prediction are carried out in combination with data-driven risk matching, so that comprehensive and prospective evaluation and early warning of the firmness safety state of the power transmission line iron tower can be realized.

The invention relates to the technical field of bridge engineering, in particular to a bridge creep deformation prediction and control method, which comprises the following steps: establishing a bridge structure finite element model; determining key section positions of the upper and lower edges of the bridge structure, and installing stress test elements at the key section positions; monitoring and recording the stress change of the upper and lower edges of the key section position in real time in the construction process; parameters in the finite element model are adjusted according to actually measured stress data, so that the error between the stress difference between the upper edge and the lower edge of the finite element model and an actually measured value is controlled within 1.0 MPa; generating a prediction result by using the corrected finite element model, wherein the prediction result comprises the creep deformation amount and the creep deformation direction of the bridge structure in the later period; and reserving a fastener adjustment space according to a prediction result. The scheme is used for solving the defect that in the prior art, the later creep deformation of a large-span beam arch bridge is difficult to accurately predict, and high-precision prediction of the later creep deformation of a bridge structure and dynamic parameter optimization and adjustment in the construction stage are achieved.

The invention discloses a wharf dismantling and backfilling settlement control construction method based on real-time monitoring, and belongs to the technical field of wharf engineering construction and settlement control. Existing wharf dismantling and backfilling construction lacks a systematic settlement control process and does not depend on real-time monitoring to realize dynamic feedback, so that the construction quality and the settlement control effect are poor. According to the method, partition division, threshold value determination and monitoring point position setting are prepared before construction, partition and segmented dismantling, layered backfill compaction, settlement dynamic adjustment and circulating construction are conducted, settlement and horizontal displacement data are collected through real-time monitoring in the whole process and transmitted to a data processing end, and construction parameters are adjusted and areas exceeding the threshold value are processed according to the data. The method is mainly used for accurately controlling settlement in wharf dismantling and backfilling construction, guaranteeing construction quality and safety of surrounding buildings and underground pipelines, and improving construction orderliness and safety.

The invention provides an assessment interview method and device for enterprise employees and a storage medium, and the method comprises the steps: determining an initial problem in a preset assessment interview problem library based on the post type and historical performance data of the enterprise employees; questioning by using the initial question so as to receive answer information of the enterprise employees; determining the semantic integrity of the answer information; if the semantic integrity is smaller than a preset integrity threshold value, generating a question-chasing question of the initial question according to a semantic element type missing in the answer information; asking questions by utilizing the question-asking questions to receive supplementary answer information of the enterprise employees; and according to the answer information, supplementing the answer information, and determining an assessment interview evaluation result of the enterprise employees. According to the method and the device, the questioning content can be adjusted according to the post types and the historical performance data of the enterprise employees, and the questioning can be selectively performed according to the answer information of the enterprise employees, so that the questioning of the assessment interviews is more accurate and deep, and the accuracy of the result obtained by the assessment interviews is improved.

The invention discloses a robot joint positioning method and device and a storage medium, and belongs to the field of robot control. The method comprises the steps of performing article recognition on environment image data to obtain article data, and inputting the article data into a robot motion learning model in combination with joint pose data to perform coordinate transformation calculation to obtain relative position data of an article and a joint; according to the relative position data and robot executable motion data obtained by a joint power parameter table of the robot, adjusting a joint power adjusting coefficient of the robot to generate a robot joint control parameter, and performing dynamic smooth calibration on the joint control parameter to obtain a variable structure control signal; acquiring an impedance control signal according to the object contact force data and the variable structure control signal; carrying out weight merging on the impedance control signal and the variable structure control signal to obtain a joint driving signal; and the joint driving signal is sent to the robot, so that the robot executes corresponding operation according to the joint driving signal.

The embodiment of the invention provides a method, a device and equipment for determining a data flow of a system on a carrier rocket. The method comprises the following steps: acquiring operation data and working condition data of the carrier rocket; determining a task stage of the carrier rocket according to the operation data and the working condition data; according to the task stage, determining a data stream of a system on the carrier rocket, the data stream comprising at least one of transmission path planning, bandwidth allocation and priority adjustment; acquiring communication state data of the carrier rocket; according to the communication state data, adjusting a data flow of a system on the carrier rocket to obtain a target data flow; and outputting the target data stream. According to the embodiment of the invention, bandwidth requirements of different stages can be matched in real time, bandwidth waste or insufficiency caused by fixed allocation is avoided, and the problem of poor dynamic change adaptability of the task stage is solved.

The application discloses a control method of an electronic device and the electronic device, and the method comprises the following steps: monitoring target feature data of a target application of the electronic device in a running process; in response to the target feature data satisfying a target trigger condition, controlling the electronic device to adjust from acquiring frame data of an application interface of the target application at a current frame frequency to acquiring the frame data at a target frame frequency, the target frame frequency being greater than or less than the current frame frequency; and inputting the frame data acquired at the target frame frequency into a target processing model to generate a target file.

A system for generating a projection structure using a graphical user interface, wherein the system comprises: a display device configured to display a graphical user interface (GUI); a computing device comprising a memory; and a processor, wherein the memory contains instructions configuring the processor to: receive a plurality of datasets, wherein each dataset comprises a plurality of parameters; generate a first projection structure as a function of the datasets; display the first projection structure through the GUI; receive natural language query data corresponding to the first projection structure using a chatbot interface; generate response data as a function of the query data; map, as a function of a look-up table, each categorization to a database entry index; obtain response data from the database; adjust the parameters as a function of the response data; generate a second projection structure; and display it in the GUI.

The embodiment of the invention provides a dynamic running environment rendering method and system applied to virtual reality, and belongs to the technical field of virtual reality, and the method comprises the steps: firstly obtaining real-time running state data (including motion amplitude and motion frequency data) of a user and a preset virtual reality running environment parameter set (including weather and time related parameters); adjusting a preset parameter based on the user data to generate an environmental parameter linkage rule; adapting scene element attributes (including visual presentation and physical simulation attributes) according to an environmental parameter linkage rule; rendering the adapted attributes in real time to generate a dynamic picture; and obtaining user interaction feedback data to adjust the linkage rule so as to update a subsequent picture. The environment can be dynamically rendered according to the running state of the user, the sense of reality and interactivity are enhanced, and the user experience is improved.