47 results about "Link model" patented technology

The invention discloses a photoelectric imaging system multi-component optimization method based on full-link model driving. The method comprises the following steps: determining a parameter value range of to-be-optimized sensor parameters of multiple components in a target photoelectric imaging system; the to-be-optimized sensor parameters comprise focal length, aperture, pixel size and integration time; based on a pre-constructed full-link simulation model of a target photoelectric imaging system and a target genetic algorithm, performing iterative optimization on the parameter value range of the to-be-optimized sensor parameters to obtain target parameter values of the to-be-optimized sensor parameters under aberration-free and stray-free conditions; and determining a target aberration range and a target stray irradiance range of the target photoelectronic imaging system based on the target parameter values of the optimized sensor parameters. According to the method, the synergistic effect and the mutual coupling restriction relation between different component parameters can be integrated in the optimization process, and the performance of the optimized target photoelectric imaging system is improved.

The application discloses a kind of space multiplexing time slot allocation method and system based on underwater acoustic channel conflict matrix, first according to underwater acoustic transmission link model, the link signal receiving success probability in underwater acoustic network is calculated;Second, according to underwater network topology information and link signal receiving success probability, generate channel conflict matrix;Then, construct time slot allocation matrix is used to mark node occupies time slot situation, from time slot conflict situation, time slot occupancy and allocation uniformity angle, to time slot allocation construct multi-objective optimization function;Finally, according to underwater acoustic channel conflict matrix and time slot allocation matrix, through global search, find the optimal solution of time slot allocation.The application comprehensively considers the allocation of underwater channel resources from three aspects of time slot conflict, time slot utilization and time slot allocation uniformity, establishes an effective fitness evaluation mechanism, can make full use of channel resources, and improves underwater acoustic communication performance.

The invention provides a method, device and equipment for modifying BIM link model data and a storage medium, and relates to the technical field of BIM design, and the method is applied to a BIM link scene and comprises the steps that an axis net of a BIM link model is loaded in a current document, when the axis net is in a model state, execution of editing operation on the axis net is forbidden, and in a current view, editing operation on the axis net is forbidden. And in response to a first state switching operation for the axis net in the current view, switching the axis net from a model state to a view state, and when the axis net is in the view state, in response to an editing operation for the axis net, modifying the axis net view data corresponding to the current view in the second data area without changing the axis net model data in the first data area. The invention provides the method. In a BIM model link scene, on the premise of not changing basic data of an axis network in a link document, flexible display and controlled editing of the axis network of the link model in a specific view of the current document are realized.

[Problem] To provide an information processing system and the like capable of optimizing an entire manufacturing line. [Solution] According to one aspect of the present invention, an information processing system is provided, the information processing system comprising a processor configured to execute following steps by reading a program, wherein the processor executes: a model acquisition step to acquire a pre-process model in which a pre-process for generating an intermediate product from a raw material is simulated, and a post-process model in which a post-process for generating a final product from the intermediate product is simulated; a condition acquisition step to acquire a process condition for each of the pre-process model and the post-process model; and an inference step to acquire, as an inference value, at least one of a characteristic value of the intermediate product, a characteristic value of the final product, a state value of a device used in the pre-process, and a state value of a device used in the post-process, by inputting the process conditions into a linked model in which at least the pre-process model and the post-process model are linked.

The invention discloses a special protocol message cross-space semantic association reasoning method and system for an electric power monitoring system, and aims to solve the problems that protocol analysis and system security events are isolated and advanced threats are difficult to associate in existing monitoring. The method comprises the following steps: jointly analyzing a protocol transmission time sequence through Fourier transform, wavelet transform and an intelligent time sequence prediction model, and constructing a fine-grained time characteristic baseline; a sensing agent is deployed on a host, a database, security and protection equipment and other layers, and formatted security events are collected; and designing an intelligent association engine fusing graph representation learning and rule reasoning, carrying out deep semantic association on an abnormal protocol mode and a cross-level security event, and realizing accurate threat alarm based on a business behavior full-link model of reinforcement learning self-optimization. According to the method, intelligent cross-space reasoning from network protocol microscopic abnormity to system macroscopic threat is realized, and the precision, the intelligent level and the adaptive capability of network security situation awareness of the intelligent substation are greatly improved.

The invention discloses a crane obstacle avoidance function anomaly detection method and system based on time sequence behavior recognition, and relates to the technical field of anomaly detection, and the method comprises the following steps: collecting multi-source state data of a crane in an operation process, and constructing an obstacle avoidance time sequence behavior link model; generating an expected execution event set of the obstacle avoidance action based on the obstacle avoidance time sequence behavior link model; extracting an actual execution event sequence corresponding to the expected execution event set from multi-source state data; and performing time sequence offset trend comparison on the expected execution event set and the actual execution event sequence, and judging whether the event is an obstacle avoidance function abnormal event or not. According to the invention, the time sequence behavior link model between the obstacle avoidance triggering condition and the action response is constructed, and the offset comparison is carried out on the expected execution event and the actual execution event; the problems that in the prior art, obstacle avoidance function abnormity cannot be accurately recognized based on the time dependency relation of the whole trigger-execution process, and the obstacle avoidance performance degradation trend cannot be judged are solved.

The invention belongs to the technical field of artificial intelligence, and relates to an LLM-based business order automatic input method and related equipment thereof, and the method comprises the steps: recognizing a customer business intention through business communication data; if the intention is the expected intention, binding a business entry related service component for the bill entry agent; generating a business input planning scheme; and according to the business entry planning scheme, business sheet entry is automatically carried out. When the method is applied to a financial service communication or negotiation scene, for example, when an insurance communication salesman or a customer service performs service communication with a customer, the big language processing model is utilized to identify the service intention of the customer, when the service intention is an expected intention, the big language processing model is adopted to perform service sheet input planning, and finally, the business sheet input planning is performed. According to the input planning scheme, business order input is automatically carried out, and compared with manual input, the input time can be saved, the business order input efficiency can be improved, manual input errors caused by manual input can be avoided, and the business order input accuracy can be improved.

A finite-time anti-interference control method for a universal pneumatic flexible manipulator includes the following steps: The universal pneumatic flexible manipulator is simplified to a link model using the D-H method, and kinematic analysis is performed to obtain the kinematic analysis model and the position of the end point of the universal pneumatic flexible manipulator; based on the kinematic analysis model of the universal pneumatic flexible manipulator, a dynamic model of the universal pneumatic flexible manipulator is established using the Euler-Lagrange method; the uncertainty of the universal pneumatic flexible manipulator is considered as a disturbance, and a second-order mathematical model of the pneumatic flexible manipulator is established; a finite-time extended state observer is designed to estimate the disturbance, and based on the disturbance estimate, a finite-time backstepping controller is designed to compensate for the influence of the disturbance on the system; to address the model uncertainty, a finite-time control method is designed to compensate for the influence on the position control accuracy of the pneumatic flexible manipulator, exhibiting strong robustness and high control accuracy.

The invention discloses a bulk commodity transportation and sales full-link big data processing method, and particularly relates to the technical field of big data processing. The method comprises the following steps: collecting real-time data of production, transportation, storage and sales nodes, and constructing a heterogeneous data source set; constructing a weight mapping matrix based on the data frequency and the credibility; fusing and constructing a space-time unified full-link model; extracting a dynamic feature sequence of the transportation batch, wherein the dynamic feature sequence comprises transportation time consumption, a path fluctuation deviation coefficient and a congestion abnormal coefficient; generating an event response vector through anomaly detection and fluctuation recognition; a causal backtracking feedforward prediction model is constructed in combination with historical sales data, and a sales prediction result is dynamically adjusted; according to the optimized transportation path, generating a scheduling suggestion set; incremental updating is carried out on the full-link model to realize closed-loop optimization; the method can effectively improve the prediction precision, scheduling efficiency and link stability of bulk commodity transportation and sales.

The application belongs to the technical field of cross-language entity linking, and discloses a cross-language entity linking method, system, medium, equipment and terminal.The cross-language entity linking method comprises the following steps: searching for candidate entities and constructing an entity name index; constructing an entity linking model based on different clues; performing vector embedding and fusion based on attribute-based entity linking; and performing multi-clue entity linking based on co-occurring entities.The application uses three kinds of clues to realize entity linking, the clues are entity attributes, co-occurring entities and context descriptions, and neural network structures such as LSTM, CNN and GCN are combined to perform word embedding representation and network modeling.Compared with traditional entity linking technology, the application has stronger semantic representation ability and the linking method has cross-language capability.Through analyzing different forms of information, the application realizes a multi-clue cross-language entity linking algorithm with three different structures, and completes accurate linking of news text cross-language entities such as persons and institutions and a given knowledge base.

The application discloses a kind of sewage system schematic diagram generation method, equipment and medium, it is related to electric digital data processing technical field.The method comprises the following steps: identifying the sewage pipeline corresponding to sewage system in three-dimensional model, and determining the pipeline type corresponding to sewage pipeline according to the topological relation of sewage pipeline;Wherein, pipeline type includes vertical pipe main pipe, horizontal pipe main pipe and instrument branch pipe;Read the elevation information in the link model of three-dimensional model, and based on the base point selected by user, according to elevation information, generate elevation line and the elevation name corresponding to each elevation line;From the first elevation line as drawing starting point, generate the pipeline graph line corresponding to each pipeline type;At the preset position of pipeline graph line, generate the end device legend connected with pipeline graph line, and carry out pipe diameter annotation and vertical pipe numbering annotation to pipeline graph line, obtain the schematic diagram corresponding to sewage system.

The invention discloses a hot rolling data material tracking anomaly analysis method and system based on link modeling. The method comprises the steps that a cross-system timestamp link model is constructed, and nodes of all working procedures of hot rolling production are modeled as graph structure nodes; performing feature engineering processing on the time sequence data, the process parameters and the MES records of each material collected at each process node to form a unified feature vector; modeling the feature vectors by using a graph neural network model, and outputting an abnormal score of each material at each process node; performing anomaly judgment and aggregation based on the anomaly score and a preset threshold value, and identifying an abnormal material and an abnormal process; providing interpretable output to assist root cause tracing; and model closed-loop optimization and threshold adaptive adjustment are supported. According to the method, the problems of cross-system data islands, material tracking distortion and abnormality positioning difficulty in hot rolling production are solved, and the data consistency verification efficiency, the abnormality detection sensitivity and the root cause analysis capability are improved.

The invention relates to the technical field of industrial upper computers and three-dimensional simulation, in particular to a three-dimensional scene building method based on OpenCasCode, which comprises the following steps of: (1) importing and creating a model, including importing a conventional format model or creating regular models such as a cube, a sphere and the like; (2) setting a three-dimensional model coordinate system, and configuring, positioning and linking the coordinate system to realize accurate linking; (3) model position adjustment is achieved through manual dragging or parameter setting based on an OpenCASCADE manipulator; (4) creating equipment, and configuring equipment types, links and motion relations; (5) simulation verification: dragging a progress bar to confirm motion data; (6) scene storage and reading are carried out, and version compatibility is supported; and auxiliary tools for template multiplexing, path management and capture, measurement and a free coordinate system are also matched. Third-party software is not needed, developers do not need to modify codes when the scene changes and the axis number is not changed, and the method is suitable for various industrial three-dimensional simulation scenes.

The application relates to a kind of test data management and control methods based on service data construction, comprising: establishing service basic data structure model;Establishing service basic test data link model;According to test data number generation service, generate original test data;Based on original test data, set key field identification sensitive information;Non-original test data declaration and declaration audit;Actual test data application control, actual test data is sequentially carried out sensitive information identification, original check and non-original check, and check through test data and check not through test data are determined;Based on service basic test data link model, check not through test data is carried out full-link tracing and destruction.Compared with prior art, the application can actively and accurately identify sensitive test data, and trace and process sensitive test data link to improve the persistence and availability of business test data.

The invention discloses a multi-connecting-rod manipulator trajectory planning method based on spatial three-dimensional coordinates, and relates to the field of automatic control. The method comprises a multi-connecting-rod model conversion module, a linear trajectory planning module and an equipment interlocking module. Bidirectional conversion of a joint angle and a three-dimensional coordinate is realized through multi-connecting-rod model conversion; based on coordinates of a starting point and an end point, adopting seven S-shaped curves to plan global cooperation time, generating a smooth trajectory in combination with PVT interpolation, and dynamically converting jerk to ensure accurate displacement; bidirectional interlocking of the mechanical arm and the station equipment is achieved by presetting a safety area and judging the position in real time. The method does not need to depend on a transverse external shaft, the reachable range of the mechanical arm is expanded, vibration can be effectively restrained, collision accidents are avoided, the method is suitable for precise load transfer in the multi-station clean environment such as EFEM, and the problems that a traditional polar coordinate control method is poor in flexibility and low in safety are solved.

The embodiment of the invention provides a batch job delay estimation method and device, equipment, a medium and a program product, and relates to the field of financial science and technology or other related fields. In response to a detected preset change event, obtaining a link model of a distributed system for executing batch jobs, the link model comprising a plurality of nodes for executing the batch jobs in topological connection, the topological connection between the nodes is used for representing file dependence, job dependence and online service calling dependence when the nodes process batch jobs; determining a target node and a target online service corresponding to the preset change event, and respective service delay time of the target node and the target online service; generating a full-link response delay estimation result of the batch job subjected to the preset change event based on the link model and respective service delay time of the target node and the target online service; the method improves the evaluation efficiency and accuracy.

The invention discloses an electricity utilization safety and supply guarantee linkage scheduling method for key power customers of an urban network, particularly relates to the technical field of supply guarantee scheduling of key customers of the urban network, and aims at solving the problems that in an existing urban power distribution network, a key power customer power supply link is not clear, risks are difficult to quantify in time, supply guarantee constraints are difficult to implement in a linkage mode in the whole scheduling process, and the scheduling cost is low. Therefore, the problems of extensive insurance and supply strategies and high possibility of mis-switching and insurance leakage are solved. Power supply link models which are bound with key power customers one by one are constructed on an urban network scheduling platform, and power supply guarantee link operation states and power utilization behavior characteristics are uniformly collected and fused, so that power utilization safety risk indexes and power supply guarantee pressure indexes are generated and solidified into a power supply guarantee linkage constraint set and scheduling influence factors; therefore, in the whole process of operation mode adjustment, load control and fault processing, the power utilization safety and supply guarantee requirements of the key power customers are considered at the same time, mistaken switching and leakage protection situations are reduced, and the power supply reliability of the key power customers of the urban network is improved.

The invention discloses a killing chain construction method based on a particle swarm algorithm, and belongs to the technical field of cooperative combat systems. The method comprises the following steps: dividing a killing chain construction problem into four links of detection, positioning, interference and strike which are executed in sequence, respectively establishing corresponding task allocation models, and taking maximization of efficiency of each link as a target function; and solving each link model by adopting an improved decimal discrete particle swarm algorithm to obtain an optimal task allocation scheme, and sequentially combining all link schemes to complete the construction of the killing chain. According to the method, the modeling process is simplified, the calculation efficiency is improved, the method is suitable for a large-scale combat scene, an optimization scheme can be quickly generated, and the requirements of actual combat for real-time performance and accuracy are effectively met.

The invention discloses a sensing, decision-making and execution integrated intelligent control method and system for a redundant rope-driven mechanical arm, and relates to the technical field of robot motion planning. The method comprises the following steps: processing an environment point cloud to obtain a three-dimensional environment model; generating a plurality of groups of collision-free expert track sequences based on the three-dimensional environment model and a simplified rigid connecting rod model of the mechanical arm; training a motion control model based on an improved enhancement algorithm by adopting a three-stage learning strategy, wherein the first stage is based on barrier-free and static target environment training, the second stage is based on barrier-free and dynamic target environment training, and the third stage is based on random barrier and dynamic target environment training; a collision-free expert track sequence is introduced into the improved strengthening algorithm to serve as expert experience; and acquiring expert experience corresponding to the real-time pose, the target position and the obstacle category of the mechanical arm, and performing real-time motion control on the mechanical arm by utilizing the trained motion control model. According to the method, collision-free motion planning of the redundant rope-driven mechanical arm in the shielding scene can be achieved.

The application discloses a kind of based on Revit software's Web end BIM model upgrade method, mainly include the following steps: S101, create a BIM model file in Revit software, obtain.rvt file and form client BIM model initial version;S102, the initial version of the BIM model is converted into web end BIM format, and the initial version of the Web end BIM model is obtained;S103, add link model initial version and integrate into the scene of client BIM model initial version, generate client BIM model upgrade version and the like steps.The application is continuously batched to the history version Web end BIM model three-dimensional scene New construction is added, and when BIM model is rendered in browser, BIM model is also loaded in network according to the order of adding batch, so streaming loading purpose can be reached, rendering effect is smooth, so that all model constructions are loaded once, and the phenomenon of easy to appear jamming is avoided.

The application discloses a kind of steady control system risk assessment method, device, storage medium and computing device, the application constructs communication network model, communication link state model and steady control device model, on the basis of communication network model and communication link state model, construct the logical link model between communication nodes, on the basis of steady control device model and communication network model, construct the association model of steady control device and communication node, based on the association model of steady control device and communication node, logical link model between communication nodes, construct steady control system model, based on steady control system model, comprehensively consider power grid operation mode, primary power grid fault, steady control device failure, communication failure, realize steady control system risk assessment, provide research and development design or operation and maintenance guidance for timely digging steady control system potential serious fault risk.

A control system and method are provided to support federated learning on a digital twin model, where respective set of devices may each perform training on a local model instance. Within each set, the training and model parameters may be distributed across the devices, with the distribution varying between sets. The control system and method may obtain information on the parameter distribution for a source set and a target set of devices, and determine a parameter mapping to link model parameters between the sets. The mapping may define data processing operations, such as splitting or merging model parameters. Upon completion of a training step by a source device, the control system and method may identify target device(s) for the transfer of model parameters and effect the transfer, which may include effecting data processing operations. The above measures may enable efficient transfer of model parameters while supporting federated learning across distributed devices.

The invention relates to a method and system for evaluating recursive DNS service quality based on log analysis, and the method comprises the steps: collecting log data of recursive DNS nodes, extracting and preprocessing recursive query related fields, and forming a structured analysis data set; performing multi-dimensional service quality analysis based on the analysis data set to generate a statistical index; constructing a behavior link model of the recursive query based on the recursive query related field; and positioning the root cause of the abnormal service quality and generating an abnormal report through the cross analysis statistical index and the behavior link model. According to the invention, through full-amount log collection and multi-dimensional analysis, recursive DNS analysis behaviors are fully covered, and the defects of limited coverage range and rough granularity of a traditional dial testing method are overcome; the root cause with abnormal service quality is accurately positioned through behavior link reduction and systematized root cause positioning logic, so that the problem of failure or delay of analysis without traceability in the prior art is solved; and by adopting quantile statistics, the tail delay is accurately captured, and the accuracy and the real-time performance of evaluation are improved.

The embodiment of the invention discloses a core particle resource optimization configuration method and system driven by reinforcement learning and a medium, and the method comprises the steps: constructing a core particle library containing core particle types, the core particle types comprise filter, low-noise amplifier, mixer and variable gain amplifier core particles, and each core particle describes intrinsic characteristic parameters through a multi-dimensional parameter matrix; determining an evaluation index to construct a task probability model according to the performance requirement of the target task; constructing a 7-level radio frequency link model according to selectable core particle types in the core particle library, simplifying the 7-level radio frequency link model into a 5-level radio frequency link model, and constructing a link output signal-to-noise ratio model based on the link model; and determining an optimization objective function by combining the task probability model and the link output signal-to-noise ratio model, and constructing a core particle resource optimization configuration model by considering the task working frequency and the core particle library resource constraint. And defining a state space, an action space and a reward function, and determining an optimal core particle configuration combination of the model based on the elements so as to realize optimal configuration of core particle resources.

The application provides a cross-platform lightweight model rotation target recognition system deployed by a full-link model, which comprises a lightweight child model and a complex teacher model neural network constructed by uniform distribution regression, a rotation task alignment distribution mechanism constructed to optimize a supervision training process, and a task-oriented decoupling knowledge distillation framework constructed to perform deep compression on the lightweight model; the lightweight child model is converted from a training format model to a platform-independent intermediate representation by using ONNX, a cross-platform precision alignment framework is constructed to align the model weight and the intermediate activation of the intermediate representation and a to-be-applied framework; fixed-point compression of the lightweight model is completed by using model quantization, part of floating-point calculation is converted to fixed-point calculation, multiple inference platforms are uniformly integrated into a visual real-time inference system by using container technology, and three steps of full-link deployment of the cross-platform lightweight model rotation target recognition system are completed. The application can reduce the number of neural network parameters and the calculation resource consumption.

The invention provides a task visualization method and device based on port automation, a field bridge and a system. The method comprises the steps that task node data of a plurality of task execution subsystems are obtained, the task node data are data meeting preset node field requirements, and the task node data comprise task identification, current node information and father node identification of the current node information; according to a node relation in the task node data, a tree-shaped link model is constructed, and the tree-shaped link model is used for reflecting the execution process of the tasks of the task execution subsystems in real time; the task execution process is visually displayed according to the tree-shaped link model, task visualization processing of port automation is completed, the effect of visualizing task link nodes in real time is achieved, and the fault response efficiency of a port automation system is improved.

The invention relates to a software and hardware integrated distributed tracking method and system for an information system operation and maintenance scene. The method comprises the steps that hardware state performance data and software operation logs are collected, and software and hardware time sequence data in a unified format are generated through standardization processing; screening a strong association object as a soft and hard node through an association degree quantification model, and generating software and hardware coupling data; constructing a full-link model comprising hardware nodes and software nodes according to the software and hardware coupling data, mapping a user request into the full-link model, determining a request path according to a data flow direction between the nodes, and calculating the total path delay of the request path; calculating the system load according to the hardware utilization rate, the software concurrent request number and the network packet loss rate, and dynamically adjusting the hardware data acquisition frequency and the software data sampling rate in combination with the load and the total path delay. By adopting the method, the resource overhead can be controlled while the monitoring precision of the key link is guaranteed, and the intelligent operation and maintenance requirements of a complex information system are met.

This invention discloses a method, apparatus, and system for analyzing the correlation between user retrieval, travel, consumption, and destination attention links, belonging to the field of consumer behavior prediction. The method includes: structuring and preprocessing legally and compliantly collected user data; identifying cognitive dwell nodes in the structured and preprocessed data to construct an attention link model module; constructing a cognitive behavior evolution prediction and path interpretability model module based on the attention link model module; and finally, dividing the attention link model module and the cognitive behavior evolution prediction and path interpretability model module into independent modules, integrating them through a unified data interface and communication protocol. During cross-scenario deployment and model migration, adjustments are made according to the requirements of new scenarios. This invention enables efficient deployment and rapid migration across different application scenarios, effectively improving the overall system's engineering adaptability, scalability, and commercialization efficiency.

The invention provides a knowledge fusion method, device and equipment, relates to the technical field of knowledge maps, and aims to improve the quality of knowledge map construction. The method comprises the following steps: respectively coding a target entity to be stored in a knowledge base and each entity in the knowledge base to obtain respective first feature representation of each entity; processing the respective first feature representation of each entity through an entity link model to obtain respective second feature representation of each entity; according to the respective second feature representation of each entity, linking the target entity to one entity in the knowledge base, performing entity clustering on each entity in the knowledge base after entity linking, and fusing the relationship corresponding to each entity in the knowledge base after entity linking and entity clustering to obtain a fused entity; the knowledge base after entity linking, entity clustering and relation fusion is obtained, and each entity and each relation in the knowledge base are used for constructing the knowledge graph.

The invention discloses a multi-mine integrated energy system double-layer game optimization method based on a flexible link. The method comprises the following steps: S1, constructing a flexible link model; s2, forming a mine comprehensive energy system on the basis of the flexible link model; s3, establishing a single-mining-area double-layer game model with an aggregation service provider as an upper layer and an energy supplier and a user as a lower layer; s4, selecting a production mine and an infrastructure mine which are close to each other in geographic position, and constructing a multi-mine-area collaborative low-carbon economic optimization dispatching model; and S5, according to the multi-mine-area collaborative low-carbon economic optimization scheduling model, constructing an objective function and constraint conditions of mine upper-layer income maximization and lower-layer energy consumption cost minimization, and determining an optimal economic low-carbon scheduling scheme of the multi-mine integrated energy system. According to the method, the limitation that a traditional scheduling method cannot meet the requirements of multiple benefit subjects can be overcome, and the multi-mining-area new energy and associated energy consumption capacity and the flexible resource utilization efficiency are improved.