85 results about "Decision graph" patented technology

The invention discloses an agent inference system based on multiple maps, and relates to the technical field of artificial intelligence, and the system comprises the steps: based on industry report, academic literature and business manual multi-source data, extracting entity-relationship-attribute, and constructing a knowledge map; dynamically capturing cooperation, report and task allocation relationships among entities, and constructing a production relationship graph; constructing a decision graph based on a field expert heuristic rule; based on the thinking engineering theory, human thinking modes and emotional states are analyzed, and a thinking map is constructed; integrating a knowledge graph, a production relation graph, a decision graph and a thinking graph, performing entity and mode alignment, mapping multi-source nodes and edges into the same vector space, introducing conflict resolution, and constructing a unified multi-mode heterogeneous knowledge graph; and guiding a large language model to generate a reasoning direction through path cue word injection, querying a constraint reasoning boundary, outputting an optimal reasoning result, and realizing agent reasoning of multiple maps. The method has the beneficial effect that the reasoning accuracy is improved.

The invention discloses a data processing method and device of a data center network, equipment, a medium and a product, and relates to the technical field of data processing, and the method comprises the steps: obtaining network topology information and a data forwarding table rule corresponding to each equipment subnet in the data center network; performing parallel coding on each piece of network topology information and each data forwarding table rule based on a network parallel binary decision diagram to obtain a data forwarding path structure between subnets on each piece of equipment, the network parallel binary decision diagram being generated based on a lockless index and hierarchical cache; based on the path connectivity corresponding to the data forwarding path structure, constructing a data forwarding graph corresponding to the subnet on each device; and verifying the data reachability between the subnets on each device according to the data forwarding graph, and generating a data reachability verification result. According to the technical scheme, the concurrency limitation is overcome, high concurrency can be achieved, and the data plane verification efficiency of the data center network is improved.

The invention discloses an intelligent fire-fighting hidden danger identification method based on multi-modal fusion, and the method comprises the steps: collecting multi-source heterogeneous data in a building environment, and carrying out the unified processing of the data, and obtaining standardized multi-modal original input data; event anchor point detection is carried out on the multi-modal input, key events are extracted, and a corresponding multi-modal event sequence is generated; constructing an event graph containing time and causal edges, and outputting an alignment event stream by using a space-time coupling causal alignment module; importing BIM and air duct structure information to establish a spatial topological graph, and fusing event streams to generate spatial constraint features; constructing a self-evolution semantic decision map based on the fusion features, and dynamically adjusting node weights and edge connection relationships; and carrying out hidden danger identification and grade division on the real-time data by using the decision map, and outputting an early warning signal and positioning information. According to the method, high-precision identification and intelligent early warning of fire-fighting hidden dangers are realized through space-time causal alignment, spatial topology fusion and self-evolution semantic decision of multi-modal data.

The invention discloses a bearing part intelligent detection and management system based on machine vision, and relates to the technical field of bearing manufacturing and detection. The method is used for solving the problems of bearing surface foreign matter recognition and pollution source tracking optimization. The system comprises a phase order correction and reconstruction module which generates a regularization weight factor through a high-frequency phase gradient, dynamically inhibits an order jump error of a raceway steep region, and outputs a high-precision three-dimensional shape and a gradient field; the coupling analysis module synchronously calculates local curvature entropy and polarization scattering intensity to realize foreign matter type identification and accurate positioning; the stress mapping decision module maps the foreign matter coordinates to a Hertz contact stress field, calculates a service life attenuation value in combination with a stress amplification coefficient, and generates a sorting priority decision map; and the pollution source reverse optimization module is used for dynamically adjusting dust removal equipment parameters based on foreign matter coordinate space clustering and assembly equipment position association. According to the system, closed-loop intelligent management of foreign matter detection and pollution source control is realized, and the bearing product quality and the production efficiency are improved.

The invention relates to the field of power quality monitoring of a power system, in particular to a comprehensive power quality monitoring method and system based on an intelligent fusion terminal, and the method comprises the steps: obtaining and preprocessing power quality data of the intelligent fusion terminal, dividing electrical partitions, determining dominant harmonic components, and calculating the electrical distance between terminals in the same partition. And based on density peak clustering, combining feature difference and electrical distance weight fusion to obtain a similarity distance, determining an adaptive cutoff distance by using a low-density region adjustment factor, and drawing a decision diagram to identify a clustering center. Screening clustering results, analyzing electric energy quality characteristic dominance, identifying a mixed cluster and re-clustering, and positioning a disturbance source by using an attenuation law in combination with a significant clustering result and an electrical distance. According to the method, the accuracy of disturbance source positioning is improved through adaptive clustering and mixed cluster analysis, and the operation condition of the power grid and multiple disturbance sources can be accurately identified through the adaptive truncation distance and the adjustment factor of the low-density region.

The invention provides a method and a system for constructing a multi-agent collaborative decision graph for traffic control. The method comprises the following steps: generating a dynamic multi-dimensional traffic decision map through multi-source traffic, traffic resources and multi-source data of traffic events of a road network system, establishing a model, predicting and evaluating a simulation result and an optimization decision result of the road network system, iterating the map, and generating a strategy according to user vehicle priority association nodes in combination with the map. Generating feedback data for a decision instruction of a traffic environment, inputting the feedback data into a map for optimization and updating, simulating, deducing and selecting an optimal scheme according to a vehicle travel urgency degree, and generating an instruction execution scheme; therefore, active deployment, collaborative optimization and adaptive evolution of traffic control are realized, and the operation efficiency and safe operation capability of a road network system are improved.

The invention discloses a vehicle fault diagnosis method, device and equipment, a medium and a product. The method comprises the following steps: acquiring real-time vehicle diagnosis data, and extracting a diagnosis vector of the vehicle diagnosis data through a pre-trained language model; determining fault association knowledge according to the diagnosis vector and a fault vector database; constructing a fault diagnosis decision diagram according to the fault knowledge graph, the maintenance manual and the historical work order; based on a graph neural network model, extracting a fault reasoning sub-graph from the fault diagnosis decision graph according to the diagnosis vector; converting a node relationship in the fault reasoning sub-graph into a natural language reasoning chain; according to the vehicle diagnosis data, the fault association knowledge and the natural language reasoning chain, constructing prompt words; and generating a fault diagnosis result based on a large language model and the cue word. According to the embodiment of the invention, a more efficient and accurate solution can be provided for remote vehicle fault diagnosis.

This application relates to the field of quantum computing technology, and in particular to a method and apparatus for accelerating quantum circuit simulation based on decision graphs. The method includes: acquiring a decision graph corresponding to the matrices of several ordered quantum logic gates in a quantum circuit to be simulated; calculating the simulation computation cost corresponding to the matrices based on the decision graph; performing a phased fusion optimization process on the matrices of the several quantum logic gates according to the simulation computation cost to generate one or more fused equivalent quantum logic gate matrices; and performing quantum circuit simulation computation using the fused equivalent quantum logic gate matrices. This application uses gate fusion to reduce the number of matrices that need to be loaded into memory, thus reducing memory access latency. Gate fusion also reduces the number of MVM operations; for example, after fusion of k quantum logic gates, only m MVM operations are required, where m < k, significantly improving the speed of quantum circuit simulation.

The invention relates to the technical field of power monitoring, and discloses a power module operation state monitoring method and system, and the method comprises the steps: carrying out the multi-frequency calibration of a high-frequency electrical signal of a power module, and obtaining a standardized multi-dimensional electrical signal; decomposing the standardized multi-dimensional electrical signal into a limited bandwidth modal component, and performing Hilbert transform to obtain a high-dimensional state feature vector; performing local linear embedding dimension reduction on the high-dimensional state feature vector to obtain a low-dimensional reference coordinate; acquiring a low-dimensional monitoring coordinate of the current high-dimensional state feature vector; constructing a decision diagram of the low-dimensional reference coordinates, and performing clustering center-to-center spacing analysis on boundary points in the decision diagram to obtain a dynamic adaptive threshold value; state deviation degree analysis is carried out on the power module, difference comparison is carried out on an analyzed state abnormity index and a dynamic self-adaptive threshold value, and a state abnormity early warning signal of the power module is generated; according to the invention, the efficiency of monitoring the running state of the power module can be improved.

A minimal unsatisfiable set detection apparatus, which detects a minimal set from a set of observed events that are determined to be inconsistent with a knowledge base, includes a decision graph acquisition unit 31 that acquires a decision graph that outputs a boolean value of an observed event from the knowledge base, an observed event acquisition unit 32 that acquires a plurality of observed events determined to be inconsistent with the knowledge base, a minimal set covering derivation unit 33 that obtains a minimal set covering by converting a plurality of observed events, which are acquired by the observed event acquisition unit 32, into a minimal set covering problem using the decision graph, and an output unit 34 that outputs a calculation result by the minimal set covering derivation unit 33.

The application relates to the technical field of data mining, and discloses an intelligent mining system for research data, which comprises a heterogeneous data acquisition module, a semantic association analysis module, a decision graph generation module, a time sequence feature correction module and a knowledge distillation optimization module. The heterogeneous data acquisition module captures data features and constructs a multi-layer topology through a multi-source data perception node and a dynamic dimension fusion network; the semantic association analysis module analyzes semantic association by using a concept topology modeling unit, a knowledge vector clustering unit and a multi-modal switching link; the decision graph generation module generates a core decision benchmark framework based on a strategy optimization node and a rule reasoning engine; the time sequence feature correction module performs time sequence correction and noise compensation on semantic association; and the knowledge distillation optimization module detects deviation through an entity relationship evaluation network and feeds back an optimized decision framework. The system realizes intelligent acquisition of multi-source data, dynamic analysis of semantics and adaptive generation of a decision graph, and improves the precision and efficiency of research data mining.

The embodiment of the invention discloses a substation operation and maintenance method and device based on multiple agents, equipment and a medium. A specific embodiment of the method comprises the steps of obtaining a real-time operation data set and an intelligent agent coordination graph in response to determining that the volume of a transformer substation is higher than a target volume; performing graph division on the agent coordination graph to obtain at least one agent set; for each agent group set, executing a generation step: for each agent group, generating group decision information; displaying the group decision information set on a decision page; generating an agent decision diagram; executing agent screening of the coordination agent set to obtain a coordination agent subset and agent decision information; generating operation and maintenance information; and according to the operation and maintenance information, controlling the main agent to indicate each coordination agent so as to carry out equipment operation and maintenance processing on the target substation. According to the embodiment, under the condition of reducing agent computing resources, accurate generation of the operation and maintenance information corresponding to the transformer substation can be achieved, and normal operation of the transformer substation is guaranteed.

1. Name of the product in this design: Graphical User Interface for Railway Packing and Assembling Decision-Making of Electronic Equipment. 2. Purpose of this design: An electronic device. 3. The key design features of this product are its graphical user interface content. 4. The image or photograph that best illustrates the design's key features: the front view. 5. The design for which protection is sought includes color. 6. Purpose of the graphical user interface: By predicting the future location and empty / load status of all online ladles in real time, based on the blast furnace distribution plan, and aiming to improve the ladle turnover rate, while considering the principle of safe tapping of iron in the blast furnace, it recommends reasonable ladle matching schemes for the iron tapping batches that are currently being tapped and the iron tapping batches that will be tapped in the future. It also allows users to view the locomotive's most recent tasks to be performed through detailed routing, thereby achieving rapid turnover of ladles. 7. Human-computer interaction method of graphical user interface: In the main view, click the "Detailed Route" button in the lower right corner to enter the interface change state diagram.

The invention discloses a multi-point collaborative conference large-screen interaction management system, and relates to the technical field of network communication. The system comprises a shared content objectification analysis module for analyzing the shared content into an interactive content object tree; the user interaction intention pre-judgment module is used for monitoring user intention and generating an initial decision node serving as a discussion starting point; the parallel topic session management module is used for creating a parallel disseminating session with automatically inherited context; the decision-making process association generation module is used for displaying logic association of the topics by constructing a decision diagram; and the conference state machine control module is used for managing focusing, diverging and converging conference process states. According to the method, the core interaction, discussion branch and decision-making process of the conference are subjected to comprehensive structured, traceable and visual management, so that the collaborative efficiency and decision-making quality of complex issues are remarkably improved.

The invention belongs to the technical field of building environment simulation, and relates to a multi-scheme comparison urban landscaping microclimate effect evaluation method, which comprises the following steps of: obtaining an environment basic data set; generating a spatial relation fingerprint parameter group including a wind direction response chain parameter, a water-heat coupling degree parameter and a shadow conflict domain parameter; generating a design scene configuration file; outputting an average radiation temperature index set, a local wind speed distribution diagram and temperature abnormal region mark data with space coordinates; based on the average radiation temperature index set, designing a scene configuration file and a spatial relation fingerprint parameter set, constructing an effect separation model, and generating effect contribution decoupling data; and based on the effect contribution decoupling data and the building layout vector diagram, generating a two-color optimization decision map marked with a green optimization area and a red avoidance area. The problem that local wind speed is too low or heat is gathered due to improper layout is solved.

The application relates to the technical field of protein-related data processing, in particular to a biological information processing system and method applied to synthetic biology. The method comprises the following steps: acquiring real-time proteomics data, performing polymorphic context decoding, and obtaining a protein expression context matrix; analyzing the interaction of behavior characteristics in the protein expression context matrix, and obtaining a multi-scale causal structure graph; performing structure-function transformation rule extraction on the multi-scale causal structure graph, and obtaining a function mapping unit set; evaluating the function mapping unit set, thereby forming a configuration decision graph; simulating the path in the configuration decision graph, performing path adaptability scoring, and obtaining a path adaptability feedback table; and optimizing the path adaptability feedback table, thereby obtaining an optimal expression configuration set. The application helps to improve the accuracy, stability and controllability of protein information in the structural analysis, function identification and regulation path construction process.

The application discloses a kind of multi-focus image fusion method and system based on salient feature difference, which comprises: obtaining multi-focus image;Based on Hessian matrix, feature extraction is carried out on multi-focus image;Based on improved modified Laplacian energy, salient feature extraction is carried out on feature map, and improved modified Laplacian graph is obtained;Significant pixel difference analysis is carried out on improved modified Laplacian graph, and initial decision graph is obtained;Region screening optimization is carried out on initial decision graph, and final decision graph is obtained;According to final decision graph and multi-focus image reconstruction fusion result, fusion image is obtained.The system comprises: image acquisition module, first feature extraction module, salient feature extraction module, difference analysis module, optimization module and fusion module.By using the application, focused area on source image can be accurately distinguished, and high-quality fusion result is provided.The application can be widely applied in the field of image fusion.

The application discloses a kind of based on AI voice interaction's old-age service scheduling method and system, method includes: user voice request and environmental perception data are collected, the joint processing of multi-dialect voice recognition and intention analysis based on deep neural network is carried out to voice request, obtains structured service demand;Environmental perception data are fused multi-sensor data and are handled with the spatiotemporal consistency calibration, obtain enhanced environmental data;Service type features and urgency degree features are extracted from structured service demand and are compensated based on attention mechanism prediction;User activity mode and environmental risk features are extracted from enhanced environmental data;Temporal-spatial graph neural network is used to construct service decision graph, realize demand-environment joint optimization;Finally, multi-granularity task decomposition generates final service task sheet.The present application realizes the accurate identification of the needs of the elderly and the intelligent response of the complex service scenario.

The application discloses a kind of based on multivariate decision graph image fusion method, device, electronic equipment and medium, for solving the problem that the multi-focus image fusion method based on the existing decision graph framework cannot be fused multiple images in single time.The method comprises: obtaining the image to be processed, extracting the feature to be fused from the image to be processed, and determining the multiple images to be fused corresponding to the image to be processed based on the feature to be fused;The multiple images to be fused are preliminarily processed, and the preliminary multivariate decision graph is obtained;The preliminary multivariate decision graph is classified based on the small area decision of the symbol distance field, and the secondary allocation multivariate decision graph is output;The boundary smoothing processing is carried out on the secondary allocation multivariate decision graph, the target multivariate decision graph is obtained, and the multiple images to be fused are weighted fused according to the target multivariate decision graph according to weight, and the target fusion image is obtained.

An information processing apparatus includes a counting unit, a rearrangement unit and an output unit. The counting unit counts, on the basis of a relation between types of quantum gates of plural types used in a quantum circuit and simulation times in a quantum circuit simulator that uses a decision diagram, the numbers of the quantum gates in descending order of the simulation time for each qubit of the quantum circuit targeted. The rearrangement unit determines the quantum gates with lengths of the simulation times at a predetermined rank or higher from the plural types of quantum gates, determines the number of quantum gates for each of the quantum gates determined in a case where there are plural types of the quantum gates determined to be at the predetermined rank or higher, and rearranges an order of the qubits to be provided to the quantum circuit simulator in ascending order of the number determined. The output unit that outputs the rearranged order of the qubits.

The application discloses an insurance customer service optimization system based on artificial intelligence, and relates to the technical field of intelligent customer service.The system comprises a data acquisition and analysis module, which acquires multi-modal interaction data of customers in real time, extracts the fundamental frequency variation rate and MFCC coefficient of voice voiceprints, calculates emotional polarity values, simultaneously analyzes text semantic content to obtain intention classification labels and emergency degree scores, and detects text missing area coordinates in images and micro-expression action frequencies in video streams; a closed-loop optimization module, which pushes an audit conclusion and a revised visual decision graph to a client, synchronously returns feedback data, dynamically optimizes dynamic weight distribution model parameters and causal knowledge graph clause node connection weights.The application realizes accurate quantification of customer emotions and service emergency degrees through multi-modal data fusion and PPO dynamic weight distribution.

The invention discloses a human-computer interaction task failure evolution path identification method based on a binary decision diagram, and aims to solve the problem that a task failure path in a complex human-computer interaction system is difficult to accurately identify. The method comprises the following steps: constructing a man-machine interaction task event tree and converting the man-machine interaction task event tree into BDD; determining a top event based on the event tree, constructing a fault tree and converting the fault tree into BDD; integrating the event tree BDD and the fault tree BDD to form a unified BDD corresponding to the ET-FT model; and traversing and identifying a failure evolution path based on the integrated BDD. Unified modeling of static logic and dynamic evolution is achieved through BDD, the causal relationship is quantified by combining Shannon decomposition and the ITE method, and the method has the advantages of being accurate in modeling, efficient in analysis and high in expansibility, can be widely applied to the fields of aerospace, medical equipment and the like and provides support for system reliability optimization.

The invention relates to the field of electric digital data processing, in particular to a sputtering film pressure sensor anomaly detection method and system based on a classification model, and the method comprises the steps: obtaining historical output data of a sputtering film pressure sensor, extracting normal working condition data, carrying out the division and slicing, obtaining a plurality of data segments, and carrying out the clustering, calculating a local density and a high-density point distance, drawing a decision diagram, screening a candidate cluster center, determining a redundant threshold through kernel density estimation, removing a redundant cluster center, and forming a normal data cluster. Constructing a classification neural network model based on a normal data cluster, fusing a loss function of misjudgment and missed judgment penalty, adaptively adjusting a penalty coefficient to optimize the performance of the model, inputting real-time data fragments into the model to obtain a classification probability, judging whether the data is abnormal or not, and completing anomaly detection. According to the method, by introducing the clustering and dynamic sliding window technology based on the density peak value, multi-working-condition data fluctuation is effectively captured, and the misjudgment rate and the missed judgment rate are reduced.

The embodiment of the present specification provides a kind of decision graph atlas graph data generation method and device.The method is executed by computer, comprising: reading first graph data from first storage area, wherein it includes the first node corresponding to the event attribute of first type business event.Several rules scripts are read from second storage area, rule script defines several decision rules, each decision rule includes identification field and expression field;Any variable included in the expression field of any decision rule is one of several event attributes or the identification value of the identification field of other decision rules.Through parsing rule script, determine second graph data, wherein it includes: parsing expression field obtains the dependent relationship between decision rule and event attribute and between each decision rule;Second graph data includes the second node corresponding to several rules, and the connection edge generated according to dependent relationship.Further, based on first graph data and second graph data, generate the graph data of decision graph atlas.

This invention provides an optimization device that can solve a given combinatorial optimization problem even if the objective function is a non-differentiable convex function. [Solution] An objective function f is a convex function that is not necessarily differentiable, and a selectable combination C of items X. i For a set of combinations F representing the set ⊆X, there exists a combination C i The probability is p i An optimization device that finds a vector x that represents the inclusion of f(x) and minimizes f(x) within a predetermined tolerance, comprising an input unit that inputs a zero-suppressed binary decision graph (ZDD) in which the objective function and the set of combinations F are represented by a zero-suppressed binary decision graph, and a tolerance ε, and in each iteration the solution x obtained in the previous iteration T From this, the next solution x T+1 The optimization unit finds the vector x such that the error from the optimal value of the objective function is less than or equal to the allowable error. T The solution is updated using the subgradient of the objective function f, and the updated solution is projected onto the feasible region of the objective function using ZDD to obtain the next solution.

The present application belongs to the technical field of knowledge compilation and network reliability analysis, and particularly relates to a network reliability intelligent computing method and system for a logical decision graph, comprising: modeling a network system as a triple data structure composed of a network topology graph, a terminal node set and an edge availability probability set; determining a topology order of network nodes and network edges based on the triple data structure; constructing a full binary tree vtree with leaf nodes corresponding to network edges one by one according to the topology order; and compiling the network topology graph into a zero-suppression statement logical decision graph using the vtree, wherein the zero-suppression statement logical decision graph is used to represent a set of valid subgraphs that satisfy terminal node connectivity; and recursively calculating a reliability value of the network system based on the zero-suppression statement logical decision graph.

The application relates to the technical field of space planning, and discloses a land space planning multi-source data fusion processing method and system. The method comprises the following steps: performing format analysis and semantic labeling on multi-source land space data to obtain standard land space data of land planning; performing hierarchical feature extraction on the standard land space data to obtain spatial features and attribute features of the land planning; performing adaptive feature fusion on the spatial features and the attribute features to obtain a multi-semantics fusion feature map of the land planning; constructing a spatial constraint rule library of the land planning based on use control rules and ecological protection red lines of the land planning; eliminating conflict patches in the multi-semantics fusion feature map based on the spatial constraint rule library, and performing semantic enhancement on the multi-semantics fusion feature map after elimination to obtain an optimized fusion result; and performing visual rendering on the optimized fusion result to obtain an auxiliary decision graph. The application can improve the efficiency of data fusion processing in land space.

This invention relates to the field of knowledge graph technology, and discloses a task processing method, apparatus, computer equipment, storage medium, and program product. The task processing method includes: receiving a task and its corresponding environmental situation information; querying a reasoning graph and a static knowledge graph based on the task to obtain behavior tree element information; wherein, the behavior tree element information includes multiple first nodes used to process the task, the relationships between the multiple first nodes, and the execution logic; constructing a behavior tree in a dynamic decision graph based on the behavior tree element information; filtering the multiple first nodes in the behavior tree based on the environmental situation information to obtain a target behavior tree containing multiple second nodes; and controlling the operation of the multiple second nodes in the target behavior tree to process the task. This invention combines a reasoning graph, a dynamic decision graph, and a static knowledge graph to complete knowledge reasoning and processing of complex tasks, expanding the reasoning scope and improving reasoning efficiency.

The invention belongs to the technical field of combination of knowledge compilation and network reliability analysis, and particularly relates to an intelligent calculation method and system for network reliability of a logic decision diagram.The method comprises the steps that a network system is modeled into a triple data structure composed of a network topological graph, a terminal node set and an edge available probability set; determining a topological sequence of network nodes and network edges based on the triple data structure; constructing a full binary tree vtree in which leaf nodes are in one-to-one correspondence with network edges according to the topological sequence; the vtree is utilized to compile a network topological graph into a zero suppression statement logic decision diagram, and the zero suppression statement logic decision diagram is used for representing all effective sub-graph sets meeting the terminal node connectivity; and recursively calculating the reliability value of the network system based on the zero suppression statement logic decision diagram.

The invention relates to the technical field of game acceleration strategies, and discloses a game acceleration strategy compiling and unified runtime method which comprises the following steps: S1, defining an acceleration strategy based on an intention-driven acceleration strategy language ID-ASL: compiling a strategy file independent of a service code by using a declarative domain-specific language ID-ASL; s2, compiling and optimizing the ID-ASL strategy file on the basis of a world model; step S3, executing the runtime decision diagram at the client: integrating the compiled runtime decision diagram into a client general SDK (Software Development Kit); and S4, calling the underlying service through the unified adapter layer. According to the method and the device, the business intention and the bottom-layer service provider SDK are decoupled, a developer does not need to repeatedly write adaptive codes, learn heterogeneous API specifications or carry out independent testing for each service provider, repeated investment of chimney type integration is avoided, manpower and time cost is greatly reduced, and version iteration efficiency is improved.