14 results about "Decision graph" patented technology

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 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.

This application relates to the field of quantum computing technology, and in particular to a method, apparatus, and electronic device for compressed storage of quantum logic gates, comprising: creating a decision graph and using the root node of the decision graph as the current node; dividing the matrix into four sub-matrices with the same number of rows and columns, creating a child node corresponding to each sub-matrix, and associating the pointer of the current node with each child node; when a sub-matrix satisfies a preset termination condition, using the child node corresponding to the sub-matrix as a leaf node and storing the leaf node as a scalar value of the corresponding sub-matrix; recursively decomposing the quantum gate matrix and shared sub-matrices by creating a decision tree, decomposing complex matrix operations into smaller sub-problems, reducing redundant computations; and using the decision graph to explore the sparsity and regularity of the quantum gate matrix, efficiently representing the quantum gate matrix and state vector, thereby achieving compressed storage of matrices in quantum circuits and avoiding redundant computations.

The application discloses a multi-focus fusion DOF three-dimensional reconstruction method based on a Siamese network. The method collects multi-focus plane images of an object to be measured, generates a standardized multi-focus plane image sequence in combination with a calibration parameter set containing a focal plane depth, a threshold parameter group and a weight parameter, inputs adjacent images into a weight sharing Siamese network, extracts a focus feature map in a unified feature space through CNN, FPN and DCN, calculates a focus confidence map according to the focus feature map, and constructs a focus decision map in combination with a focus response difference; pixel-level fusion is completed relying on the decision map and the confidence map, a pixel-level focus index matrix is updated through recursive comparison, index abnormal jumps are corrected by using depth continuity constraints and regional correction weights, an optimized focus index matrix is obtained, depth data and preliminary reconstruction results are generated based on the optimized focus index matrix, abnormal areas are corrected in a reverse tracing manner, and finally, the DOF three-dimensional reconstruction results are output. The method can reduce misjudgment, suppress depth jumps, and improve continuity and accuracy.

The application discloses a fault repair method and device, equipment, a storage medium and a program product, and relates to the technical field of software operation and maintenance. The method comprises the following steps: determining a plurality of first candidate paths matched with a current fault event from a decision graph, wherein the decision graph is a knowledge graph obtained by fusing an influence propagation graph and an expert knowledge graph, and the influence propagation graph is a knowledge graph generated according to pre-collected historical multi-modal data; determining a comprehensive confidence of each first candidate path according to a path confidence, a path causal weight and a safety coefficient of the first candidate path; determining a first target path corresponding to the highest comprehensive confidence; and if the comprehensive confidence of the first target path is greater than or equal to a first comprehensive confidence threshold, performing a first target treatment action represented by a treatment action node of the first target path. The method improves the fault repair efficiency and the fault repair accuracy.

A program according to one embodiment of the present disclosure causes a computer to execute: a first input procedure for inputting a first nonterminal node and a second nonterminal node on a zero-suppressed binary decision diagram; a second input procedure for inputting at least designation of a first function representing a condition to be satisfied by a set pair of a set included in a set group represented by the first nonterminal node and a set included in a set group represented by the second nonterminal node; and a calculation procedure for executing a set group calculation of the set group represented by the first nonterminal node and the set group represented by the second nonterminal node, on the basis of the first nonterminal node, the second nonterminal node, the first function, and a template of an algorithm for achieving the set group calculation.

The application relates to an AI voice follow-up intelligent generation method and system for chronic disease management, and relates to the technical field of intelligent voice follow-up, and comprises the following steps: acquiring user voice response data, performing voice recognition and term standardization to obtain standardized text; performing natural language understanding on the standardized text, extracting key information to generate a structured follow-up record; calculating the comprehensive compliance score of a user based on the structured follow-up record; taking a preset directed decision graph as the basis, taking the comprehensive compliance score and information coverage state as inputs, dynamically adjusting a questionnaire node, and generating an adaptive questionnaire path; and performing the next round of voice follow-up interaction according to the adaptive questionnaire path. The application solves the technical problem that a traditional chronic disease follow-up voice system adopts a fixed interaction process, cannot flexibly adjust the questioning emphasis and communication mode according to actual patient feedback, leads to rigid follow-up, incomplete information, and difficulty in supporting long-term personalized management.

The application discloses a multi-focus image fusion method based on interactive mask decoupling and frequency adaptive Transform, comprising the following steps: acquiring two source images; extracting preliminary features through a multi-scale feature extraction module; inputting a cascaded frequency adaptive Transform encoder to perform self-attention calculation in the frequency domain to obtain encoding features; inputting the bottleneck layer aggregation into a decoder, and enhancing clear areas according to the mask map updated stage by stage through an interactive mask decoupling attention module to output a decision map; and outputting a full-focus image according to the decision map fusion. The application migrates the self-attention calculation to the frequency domain to reduce the complexity, and decouples the multi-head attention into foreground, background and global path through a dynamic mask to realize accurate separation and enhancement of the focus area, effectively suppress the boundary artifacts, and significantly improve the detail preservation ability and overall visual quality of the fused image.

The application discloses a kind of based on knowledge graph's rubber surface defect real-time detection system and method.The system includes defect fingerprint extraction module, defect dynamics modeling module, hierarchical decision graph module, adaptive strategy optimization module, defect field analysis module and intelligent compensation control module.Through multiscale feature extraction, construct defect fingerprint and pedigree network, based on physical and chemical principles, predict defect evolution, use four-layer knowledge structure to realize multi-hop graph reasoning, use Bayesian optimization and meta-learning to dynamically adjust detection strategy, model rubber surface as continuous field for anomaly positioning, and generate hierarchical compensation strategy according to impact score.The application realizes the integration of detection, prediction, reasoning and control, and improves detection accuracy and efficiency.

This application discloses a method, apparatus, and electronic device for training a decision graph generation model, applied in the field of artificial intelligence. The method includes: training an initial decision graph generation model based on general data from a non-operational domain to obtain an intermediate decision graph generation model, wherein the general data includes multiple non-operational problems and corresponding general decision graphs; training the intermediate decision graph generation model based on first operation and maintenance data from the operation and maintenance domain to obtain a first decision graph generation model, wherein the first operation and maintenance data includes a first operation and maintenance problem and a corresponding first operation and maintenance decision graph; and performing reinforcement learning on the first decision graph generation model based on second operation and maintenance data from the operation and maintenance domain to obtain a second decision graph generation model, wherein the second operation and maintenance data includes a second operation and maintenance problem and a corresponding second operation and maintenance decision graph. The second decision graph generation model is used to generate operation and maintenance decision graphs, which can solve the problem of poor adaptability of the method for determining operation and maintenance decision graphs and improve the adaptability of generating operation and maintenance decision graphs.

This invention discloses an intelligent assessment and repair decision-making method for drainage pipeline defects based on big data, specifically involving the field of assessment and decision-making. The method includes: constructing a five-dimensional framework; collecting various types of data such as pipe segment attributes and defect status; forming a spatiotemporally aligned data set through preprocessing, quality control, and standardization; designing a knowledge graph ontology framework based on this set; extracting entity instances and relationships to form an initial graph; and outputting high-dimensional feature vectors of pipe segments via a graph neural network; quantifying and determining defect levels; predicting the spatiotemporal evolution trend of defects through a model that integrates physical laws and data-driven approaches; quantifying risks in multiple dimensions and calculating the total risk; constructing four types of functional intelligent agents; achieving collaborative decision-making through multi-objective optimization and reinforcement learning; and generating a dynamic decision graph hierarchically prioritized. This invention achieves intelligent and precise defect assessment and maintenance decision-making, improves operation and maintenance efficiency and scientific rigor, and adapts to the dynamic changes in the pipeline network.

1. Name of the product in this design: Graphical User Interface for Claims Data Analysis and Decision-Making System for Electronic Devices. 2. Purpose of this design: An electronic device. 3. The key design feature of this product is its graphical user interface. 4. The image or photograph that best illustrates the design's key features: the front view. 5. Uses of the graphical user interface: It is used to integrate full claims data into PC programs to generate visual reports and guide product pricing, resource allocation and other decisions through predictive models. 6. Human-computer interaction method of graphical user interface: The main view is the display page of the claims data analysis and decision-making system. Clicking the "Query" button at the top of the main view will take you to the interface change status diagram.

This invention discloses a method and system for secure information transmission in multi-terminal online paperless meetings, relating to the field of data transmission technology. The method includes: S1, the server divides the meeting document into encrypted fragments according to agenda items and pre-distributes them to each tablet terminal. The encrypted fragments are protected based on a chaotic system and threshold cryptography; S2, each tablet terminal constructs a rendering decision graph based on the rendering instruction stream and extracts a rendering fingerprint. The nodes of the rendering decision graph represent document elements within the viewport, and the edge weights represent the temporal correlation strength of the rendering instructions; S3, each tablet terminal calculates the similarity of its own rendering fingerprint with that of other tablet terminals and executes a consensus protocol based on the rendering fingerprint similarity; S4, a health index is generated based on the execution result, and the health index feeds back the evolution parameters of the modulated chaotic system; S5, during the execution of an agenda item, each tablet terminal collects encrypted fragments that meet a threshold number to reconstruct the key and decrypt the local document. When the agenda item ends, the reconstructed key and fragments are deleted.

The application discloses a multi-focus image fusion method and system based on structural similarity and region segmentation, and the method comprises the following steps: performing weighted processing on multi-focus source images based on a fusion strategy of visual saliency detection, performing enhancement processing on pre-fusion images through a multi-scale detail enhancement strategy of logarithmic energy difference, and obtaining detail-enhanced pre-fusion images; performing segmentation processing on the detail-enhanced pre-fusion images based on a structural similarity index, and obtaining a region segmentation decision graph; and performing fusion processing on the region segmentation decision graph according to a pixel selection rule, and obtaining a final fusion image. The system comprises a pre-fusion module, an enhancement module, a segmentation module and a fusion module. Through the application, pixels with different focusing properties can be accurately distinguished and integrated to generate a full-focus image. The application can be widely applied to the field of image fusion technology.