137 results about "Metacomputing" patented technology

The invention, which relates to the technical field of mine geology and urban safety, discloses a refined collaborative prediction method and system for subsidence of a global goaf, comprising the steps of establishing a hierarchical storage system, and correcting a working face calculation boundary; extracting the maximum influence radius of all the working faces and four-dimensional coordinates of the mining boundary of each working face, and calculating to obtain a global prediction range to generate a global surface prediction grid; point set insertion and Delaunay triangulation are adopted to obtain an effective triangular unit, a local influence domain range of the effective triangular unit is calculated, and an influenced sub-grid is screened from the global surface prediction grid; and calculating a predicted point movement deformation value based on a parallel computing architecture, accumulating the predicted point movement deformation value to a global result array through a coordinate index mechanism, synthesizing a deformation component in a specific direction, generating a visual result, and performing statistical analysis. According to the method, the problems of poor adaptability and low efficiency of a traditional scheme are effectively solved, and the prediction precision and efficiency are remarkably improved.

The invention relates to the technical field of rolling mill automatic control, in particular to a special rolling mill controller without a PLC framework and an integrated control system, and aims to solve the problems that in rolling of a rolling mill, the sampling rate difference of pressure and thickness sensors and material plastic deformation accumulation cause the time sequence dislocation of a rolling force peak value and a thickness valley value, the collaborative utilization of data by a thickness control algorithm is influenced, and the cost is reduced. In order to solve the problems that rolling force, thickness data and roller pulse signals are collected through a special controller, and a rolling length observation benchmark is converted; the dynamic phase compensation unit calculates a plastic deformation cumulant, after triggering compensation, a basic phase difference is established based on a sampling rate difference, a compensation coefficient is dynamically increased, a compensation data segment is generated through linear interpolation, and a time sequence is forcibly aligned; and the integrated control unit inputs the alignment data into a thickness control algorithm, the rolling force serves as feedforward, the thickness data serves as feedback, a precise roller gap adjusting instruction is generated, and the material thickness rolling precision is improved.

A method may include: receiving a prompt and generated text from the LLM; computing an original token probability distribution for each token in the prompt and in the generated text; receiving a token position probability distribution for each token position in the generated text from the LLM; identifying keywords in the prompt; perturbing embedding vectors for the keywords used by the LLM by adding noise to the embedding vectors; computing a perturbed probability distribution for the perturbed embedding vectors by providing the perturbed embedding vectors as an input to a neural network used by the LLM, wherein the neural network returns a perturbed token probability distribution; evaluating a divergence between the original token probability distribution and the perturbed token probability distribution; identifying semantically meaningful tokens in the generated text; calculating a mean of divergences for the semantically meaningful tokens; and classifying the LLM based on the mean of divergences.

The invention relates to a real-time path planning method and system based on conflict resolution, equipment and a medium. The method comprises the following steps: preprocessing original observation data to obtain an evidence unit of each sensor; calculating a total conflict amount and a sensor pair contribution matrix based on an evidence unit, updating the credibility of each sensor and selecting a fusion operator to obtain fusion evidence and a conflict degree after fusion; a short-term time sequence is generated according to the fusion evidence and the conflict degree after fusion, the expected occupation probability and the expected conflict trend of each grid unit are predicted, and a time sequence conflict map is obtained; according to the time sequence conflict map, conflict-level adjacent grid unit aggregation fuzziness and area-level conflict characteristics are carried out; and inputting the fusion evidence, the conflict fluctuation degree, the expected stable time and the region-level conflict feature as cost and constraint into a real-time local path planner to obtain a control decision. By adopting the method, the problem of path decision oscillation caused by multi-source sensor conflicts can be relieved.

The invention relates to a system for determining the compaction of a flowable, solidifiable building material, in particular concrete, during the production of a structural element with the building material, wherein the flowable building material is introduced into a formwork system (10), comprising: at least three sensors (S1, S2, S3) to determine an amplitude (A S1 , A S2 , A S3 ) a vibration introduced into the flowable building material by a vibration unit (VE), wherein the sensors (S1, S2, S3) are arranged on the formwork system (10), at least one computing unit that is set up to perform calculations based on the amplitudes (A) determined by the at least three sensors (S1, S2, S3). S1 , A S2 , A S3) to calculate possible positions (D1, D2, D3) of the vibration unit (VE) relative to the respective sensors (S1, S2, S3) and, based on this, to triangulate the current position of the vibration unit (VE) relative to the formwork system (10), a documentation unit for documenting the dwell time of the vibration unit (VE) in the respective current positions of the vibration unit (VE) relative to the formwork system (10), the computing unit determines a calculated compaction value in the respective current positions based on the respective current positions of the vibration unit (VE) and the documented dwell time in the respective current positions.

The invention discloses a user demand insight positioning method and system based on AI driving, relates to the field of artificial intelligence and big data analysis, and solves the technical problem that it is difficult to accurately recognize user demands and respond to the user demands in real time through dynamic analysis of multi-source text data and construction of a knowledge graph. Comprising the steps that text data are collected, structured data are generated through preprocessing, and a structured data unit is generated; calculating text vocabulary diversity and syntactic complexity indexes, inputting the text vocabulary diversity and syntactic complexity indexes into a pre-training regression model to obtain a dynamic character threshold value, encoding short / long texts by adopting a lightweight graph neural network and a hierarchical Transform, and extracting core demand elements; a dynamic time sequence knowledge graph is constructed, a time sequence edge weight updating algorithm is introduced to adjust node association strength, and cross-domain association is mined; and calculating a user demand intensity evaluation value based on an entropy weight method in combination with the inventory pressure factor and the group influence factor, thereby realizing inventory scheduling and personalized recommendation.

The application discloses a kind of direct identification method of low-order linear system order of different real pole, comprising the following steps: initialization to be measured system to zero state, constant excitation is applied to the input end of to-be-measured system and simultaneously acquires the response output signal of to-be-measured system, calculates sample adjacent different elements, discriminant factor is calculated using sample adjacent different elements, calculate first discriminant element, secondary discriminant element, tertiary discriminant element and its average value and standard deviation, identify, eliminate singular discriminant element and update, the order N of to-be-measured system is analyzed out;The application gives a solution to the key technical pre-problem in the control and operation level for different real pole low-order linear system, and builds a core technical foundation for subsequent realization of safe and controllable, efficient and low-consumption and high-performance stable operation.

The invention discloses a service traffic prediction method and device, a network element, a computer storage medium and a program product. The method comprises the steps of obtaining traffic data of a plurality of applications, dividing application categories to which the applications belong based on the traffic data of each application, and generating a classification list according to a division result; obtaining user information and application use data of the user, dividing user groups to which the user belongs based on the user information and the application use data, and determining a portrait label corresponding to each user group; determining first traffic consumption of the first user in the historical specified time, determining second traffic consumption of a first user group to which the first user belongs in the historical specified time, and determining a first coefficient based on the first traffic consumption and the second traffic consumption; and predicting the service traffic of the first user according to the first coefficient, the classification list and a first portrait label corresponding to a first user group to which the first user belongs, and generating service traffic prediction information.

The application belongs to the technical field of additive manufacturing, and particularly relates to an intelligent 3D printing system, which comprises a rack and a controller, the inside of the rack is provided with a laser printing head and a powder laying mechanism, the powder laying mechanism lays powder, and then the laser printing head melts the powder by laser to complete the action of cladding. The intelligent 3D printing system can utilize forward mapping to output the trained network in seconds or even milliseconds, greatly accelerating the real-time simulation effect of design iteration. Meanwhile, the neural network can replace time-consuming finite element calculation in the optimization process of genetic algorithm, and quickly find the optimal design parameters, thereby achieving the effect of optimization design. On the other hand, the backward mapping is used to quickly and accurately identify the complex material model parameters, which is several times faster than the traditional trial-and-error method, and the input or physical characteristics of the system can be back calculated according to the dynamic response of the structure.

A method, an electronic device, a computer readable medium, and a computer program product are provided. The flow management and control system comprises a request processing unit which is used for periodically obtaining an exception list from a strategy center unit and performing local caching, performing legality check on a received request according to the exception list, and reporting request related information to a computing center unit; the computing center unit is used for receiving the requests reported by the request processing unit, distributing the requests received in a preset time period to the same processing equipment according to a timestamp partitioning algorithm, and aggregating and computing the traffic indexes corresponding to the preset time period in the memory of the processing equipment; and the strategy center unit is used for storing a global exception list, receiving the traffic index exception list reported by the calculation center unit to update the global exception list, and synchronizing the updated exception list to each request processing unit.

The invention provides a cluster system comprising a computing unit and a switching unit and a task processing method and device, and relates to the technical field of computers. The cluster system comprises N computing platforms, and each computing platform comprises a switching unit, a computing unit, a power supply unit, a monitoring management unit and a controller. The computing unit comprises at least one of a PC, a CPU, a GPU and a neural network computing module; the switching unit comprises a first type switching module which is used for connecting a hardware or software interface of a network, is responsible for sending, receiving and processing data, and comprises but is not limited to a gigabit Ethernet interface; the second type of switching module provides support for high-speed serial data transmission, adopts high-speed data interfaces, and comprises but is not limited to a Serdes interface and an LVDS (Low Voltage Differential Signaling) interface; the third type of switching module is a high-bandwidth and low-delay data interface which comprises but is not limited to an MCIO interface and a PCIe interface; and the fourth type of switching module is a high-bandwidth and high-density data transmission interface which comprises but is not limited to a QSFP interface and an OSFP interface.

The application discloses a neuron computing core and system. The computing core comprises a storage module, a computing module, a pulse generation module and a core control module. The computing module is used for performing operation on coarse-grained data, pulse data and weight data previously set in the storage module, and the operation result is sent to the pulse generation module. The pulse generation module is used for sending the operation result to a target address. The computing core can support operation with different precisions without two repeated computing resources, and can reuse the same hardware resources, thereby ensuring high operation efficiency and saving hardware resources. The application can be widely applied in the field of artificial neural network computing technology.

The present invention provides a quantum system error detection device, the device comprising: a control register for receiving information representing a quantum state of a control qubit and outputting an operation result; an auxiliary register for receiving, on a one-to-one basis, information representing a quantum state of a target qubit; a CNOT gate connected to the control register and the auxiliary register; a first detector connected to the control register and configured to measure a quantum state of the control qubit to which the CNOT gate is applied; a second detector connected to the auxiliary register and configured to measure a quantum state of the auxiliary qubit to which the CNOT gate is applied; a probability calculation unit for calculating probabilities of quantum states of the control qubit and the target qubit from measurement results of the first detector and the second detector; and an error rate calculation unit for calculating error rates of quantum state initialization, the CNOT gate, and quantum measurement from the probabilities calculated by the probability calculation unit.

The invention provides an equivalent materialization modeling and efficient simulation method for an additive manufacturing lattice structure, and belongs to the technical field of additive manufacturing and structure simulation. The method comprises the following steps: firstly, designing and preparing a standard test sample consistent with a real sample piece in process according to dot matrix geometric characteristics of the real sample piece, and obtaining equivalent material parameters through mechanical test; secondly, extracting the outer contour of a dot matrix area from the original CAD model, constructing a continuum entity to replace an original dot matrix structure, and fusing the continuum entity with an entity area to form a simplified model; and endowing equivalent material parameters to the entity area, and performing thermal-mechanical coupling finite element calculation in simulation software to obtain stress and deformation distribution in the forming process. According to the method, huge calculation overhead caused by full-dot-matrix fine modeling is avoided, the simulation efficiency is remarkably improved, meanwhile, the prediction precision is guaranteed through experiment-driven equivalent material parameters, the method is suitable for various dot matrix configurations and metal material systems, and efficient and high-fidelity simulation of additive manufacturing complex dot matrix components is achieved.

The present disclosure provides an extended video memory-based model training method, a model inference method, an apparatus, a device, a medium and a product, relating to the technical field of storage devices. The extended video memory-based model training method comprises: sending a first DSM instruction to an SSD controller, and performing multiple rounds of iterative training by a GPU. Each round of iterative training comprises multiple processing stages. The processing stages comprise: the SSD controller loading data units before calculation corresponding to hierarchical identifiers to the GPU, and the GPU calculating calculation units based on the data units. The first DSM instruction marks the priority of the calculation units. The GPU unloads the calculation units to the SSD. The SSD controller unloads the calculation units of high priority to SLC and unloads the calculation units of low priority to QLC. Through the technical solution of the present disclosure, the access delay of high-sensitive data is reduced without increasing the hardware cost, and the invalid erasing and writing of SLC is reduced to prolong the service life of the SSD.

Methods, error correction circuits, and circuit modules using error correction circuits are provided for performing co-bit calculations for error correction by means of circuit complexity reduction. Methods and related devices for co-bit computations for error correction by means of circuit complexity reduction are provided. The method comprises: in an error correction circuit using a predetermined error correction code, configuring a first group of XOR operational circuits in a plurality of XOR operational circuits corresponding to a predetermined codeword length, rather than all XOR operational circuits in the plurality of XOR operational circuits, so as to reduce the circuit complexity of the error correction circuit and improve the error correction efficiency of the error correction circuit. Wherein the first set of XOR operational circuits may be a set of optimized XOR operational circuits implemented based on co-located bit coverage reduction; and performing the co-bit calculation using the first set of XOR operational circuits for error correction corresponding to a shorter codeword length, where a smaller XOR operand and a shorter critical path length can be achieved.

The application discloses a kind of piecewise direct identification method of low-order linear system order containing complex pole, comprising the following steps: the system to be measured is initialized to zero state and prepares a constant input excitation and an output quantity acquisition system, the constant input excitation is applied to the system to be measured and the output sample is collected and saved, the sample adjacent difference element is calculated, the order base element is calculated, the singular order base element and the corresponding sample adjacent difference element are identified and removed, and the total number of effective sample adjacent difference elements and the total number of effective samples are updated, the identification coefficient and the identification accuracy are calculated, and the order of the system to be measured is analyzed;The application gives a solution to the key technical pre-problem in the control and operation level for the low-order linear system containing complex pole, which lays a solid foundation for the core technology for the subsequent realization of safe and controllable, efficient and low-consumption, and high-performance stable operation.

The invention relates to the technical field of mechanical design, in particular to a mechanical structure global intelligent design system based on topological evolution optimization. Comprising a global parametric modeling module configured to construct an initial population of a mechanical structure by using an explicit geometric description method based on a preset design domain, a mechanical boundary condition and a manufacturing process constraint, each individual in the initial population being uniquely represented by a group of geometric parameter vectors, according to the method, a closed-loop feedback mechanism of a physical perception agent model and active learning evolution is constructed, so that the inherent contradiction of huge time consumption of traditional evolution optimization calculation and insufficient physical precision of a pure data driving model is effectively overcome; according to the system, the deep neural network is used for replacing high-frequency finite element calculation, the global search efficiency of a complex mechanical structure is improved by two orders of magnitude, meanwhile, real-time error calibration is carried out on an agent model through online high-fidelity verification, and it is ensured that the mechanical property prediction error of an optimal solution is lower than a preset threshold value.

A failure location estimation device according to the present invention has a rule learning control unit that defines a rule that indicates the relationship between alarms that characterize failures at a network and failure locations and a failure location estimation function unit that estimates failure locations using an alarm set that has been generated at the network and the rule. When the rule is defined, the rule learning control unit extracts a plurality of rule candidates, the failure location estimation function unit estimates failure locations using all of the plurality of rule candidates and calculates evaluation values for correct locations and evaluation values for incorrect locations, and the rule learning control unit calculates scores that include the evaluation values for correct locations and the evaluation values for incorrect locations calculated by the failure location estimation function unit and numbers of incorrect locations as parameters and uses the rule candidate that has the highest score to define the rule to be used for estimation of failure locations by the failure location estimation function unit.

The present invention provides an information processing device that can generate 3D model data of a formwork molded object with a cut shape, in which a cut shape of an appropriate volume is added to the formwork molded object, which has a target shape. [Solution] The information processing device of the present disclosure includes an acquisition unit, a first generation unit, a calculation unit, a second generation unit, and a third generation unit. The acquisition unit acquires 3D model data of a formwork molded object and manufacturing information of a material extrusion method. The first generation unit generates 3D model data of a predicted molded object that is expected to be materialized by a material extrusion method based on the 3D model data of the formwork molded object. The calculation unit calculates information on the amount of change in the shape of the predicted molded object from the shape of the formwork molded object. The second generation unit calculates cutting shape information so that the volume of the cutting shape does not exceed a predetermined value. The third generation unit generates 3D model data of a formwork molded object with a cutting shape based on the 3D model data of the formwork molded object and the cutting shape information.

The application relates to the technical field of intelligent manufacturing, in particular to a numerical control machine tool production efficiency statistical system, which comprises a data acquisition and correlation unit, which is used for acquiring and correlating multi-dimensional state data from a numerical control machine tool; a switching feature vectorization unit, which is used for receiving the multi-dimensional state data acquired by the data acquisition and correlation unit; a transient parameter prediction unit, which is used for predicting an initial efficiency drop amplitude and a feature recovery time based on a switching feature vector constructed by the switching feature vectorization unit; a transient loss quantification unit, which is used for calculating a transient efficiency loss according to the initial efficiency drop amplitude and the feature recovery time predicted by the transient parameter prediction unit; and a scheduling sequence optimization unit, which is used for taking the transient efficiency loss calculated by the transient loss quantification unit as a decision basis to solve an optimal task execution sequence. The application can improve the actual output efficiency of the numerical control machine tool and the overall equipment utilization rate in the dynamic production scene of small batches and multiple varieties.

The invention relates to an operation switching method and device, a terminal, an MME network element, a computer readable storage medium and a computer program product. The method is used for a terminal, and comprises: receiving target operation indication information, the target operation indication information being sent to the terminal by an on-satellite mobility management (MME) network element, or being sent to the terminal by an on-satellite base station; the target operation indication information can be used for indicating a target operation to be switched by the terminal; and according to the target operation indication information, executing a process of switching from a store-and-forward operation or a normal operation to a target operation. By adopting the method, flexible switching between the store-and-forward mode and the normal mode can be realized.

This invention relates to the field of bridge structural health monitoring systems based on the Industrial Internet, specifically disclosing a bridge structural health monitoring system based on the Industrial Internet. The system includes a bridge structural sensor network, a micro-meteorological sensing unit, a computational fluid dynamics simulation engine, a physical information neural network proxy model, a real-time boundary correction unit, and a structural health assessment center. By fusing micro-meteorological data with high-fidelity wind field simulation, a wind pressure-structural response mapping model with physical consistency is constructed, and real-time boundary correction is used to achieve closed-loop synchronization between the digital twin and the physical entity. The structural health assessment center identifies anomalies based on the expected response and measured deviations, and reduces false alarms by combining an adaptive threshold mechanism. Furthermore, the model has the ability to extrapolate and predict wind-induced vibrations, enabling early risk warnings. This invention can achieve high-precision damage identification and proactive safety warnings, improving the proactive safety assurance and intelligent operation and maintenance level of bridges in complex wind environments.

The invention discloses a finite element fatigue damage calculation information encryption system for a rotary folding deployable system, and particularly relates to the field of end-cloud cooperative calculation and structural security information encryption processing, and the finite element calculation initialization operation is executed in an edge node of the rotary folding deployable system; and recording the formed response difference matrix delta R, calling a mapping function to calculate a mapping key phi (delta R), and registering the phi (delta R) as an encryption control parameter of the current calculation period. Disturbance mapping, virtual calculation space and a layered encryption transmission mechanism are introduced under an end-cloud collaborative architecture, so that encryption solution and credible verification are completed in a finite element fatigue damage calculation process on the premise of not exposing real node coordinates and geometric topology, and therefore, safe sharing of structural calculation information and side channel anti-inference are realized.

A synchronization detection device includes: a pseudo-vorticity matrix calculation unit that inputs time evolution information of phases from an oscillator system including a finite number of oscillators and calculates a matrix having elements each of which is a discretized value of a phase difference obtained by two of the oscillators by time evolution; a synchronization graph generation unit that generates a synchronization graph that visualizes two-point synchronization with a graph representation; a partial synchronization set detection unit that detects a plurality of subsets of the oscillators having no common portion and partially synchronized in a set of a finite number of the oscillators in the synchronization graph; and a synchronization index calculation unit that generates an index characterizing partial synchronization of the oscillator system using a calculation result calculated by the pseudo-vorticity matrix calculation unit and a partial synchronization set detected by the partial synchronization set detection unit.

This invention relates to the field of big data technology and discloses an information security alarm system based on big data. The system comprises a data acquisition unit that collects multi-source security data in real time, a processing unit that generates standardized event data, an analysis unit that performs aggregation and statistics, a calculation unit that calculates a preliminary screening value SX, a central unit that analyzes the preliminary screening value SX and marks preliminary abnormal events, a learning unit that marks real abnormal events, an association unit that associates the standardized event data corresponding to the real abnormal events and matches attack patterns, and an early warning unit that displays the data on the platform. This invention standardizes the multi-source heterogeneous security data acquired by the acquisition unit through a processing unit, generating standardized event data in a unified format. This eliminates differences between different data sources in terms of data format, field definitions, and time precision, improving data consistency and usability, and providing unified data for subsequent analysis, calculation, learning, and association units.

The invention relates to the technical field of data processing, in particular to a load sensing optimization system and method, and the system comprises a quantization topology modeling module, a chaotic enhancement pressure generation control module and a causal anti-fact analysis module. The quantization topology modeling module maps micro-service nodes into quantum bits through the annealing algorithm unit and converts the quantum bits into Hamiltonian constraints, the chaos enhanced pressure generation control module receives topological graph recognition target nodes, the chaos sensing unit injects a chaos noise sequence, the instability prediction unit calculates a Lyapunov exponent to mark the chaos state, and the chaos sensing unit senses the chaos state. A hybrid decision engine serializes a quantum bit chain to generate a pressure generation path set, and a reinforcement learning agent optimizes path parameters and synchronizes across nodes through an over-distance parameter adjustment unit. The causal graph engine establishes a causal directed graph to execute anti-fact inquiry, and the vulnerability marking unit calculates quantum de-coherence risk entropy, outputs zero-knowledge proof and feeds back and updates topological constraints. And dynamic micro-service link tracking and cross-regional bottleneck accurate positioning are realized.

One embodiment of the present invention sets forth a technique for processing a query of a life cycle assessment (LCA) database. The technique includes searching one or more hierarchical structures included in the LCA database for data nodes that match a set of parameters that is (i) included in the query and (ii) specifies one or more properties of an entity. The technique also includes upon determining that a data node includes an unknown consumption or an unknown emission, matching a second set of parameters associated with the data node to an entry in a cache and computing one or more environmental impacts based on a functional unit that is (i) included in the entry and (ii) includes a quantity associated with the unknown consumption or the unknown emission. The technique further includes causing the one or more environmental impacts to be outputted in a response to the query.

This invention relates to the field of social security management data processing, and discloses a social security information intelligent analysis system based on dynamic closed-loop control. The system includes: an analysis and prediction unit that calculates risk scores based on feature weights; a subthreshold residual interception unit that captures weak score data below a trigger threshold; a spatiotemporal entropy aggregation unit that calculates the Shannon entropy value of the weak data; an agility bias unit that lowers the trigger threshold based on the low entropy value aggregation state; and an adaptive damping correction unit that uses the difference vector between prediction and feedback to inversely correct the feature weights. This invention calculates the spatiotemporal entropy value of the discarded residual data to sense environmental background pressure, dynamically biases the trigger threshold accordingly, and introduces a damping mechanism correction model in the feedback closed loop to solve the problem of missed weak risk detection caused by a fixed threshold, achieving an adaptive dynamic balance between system sensitivity and false alarm rate.