105 results about "Short path algorithm" patented technology

The invention provides a knowledge base and business system collaboration method under an AI platform, and belongs to the technical field of AI platform digital data processing.The method includes the steps that triple semantic analysis is conducted on query by constructing a multi-level semantic vector representation module, a parallel data retrieval engine is started, vector retrieval, graph reasoning and real-time data pulling are executed at the same time, and the query efficiency is improved; establishing a dynamic confidence evaluation mechanism to evaluate the quality of the data source, executing a weight distribution algorithm based on reinforcement learning, dynamically calculating the weight of the data source according to a query type by adopting a graph convolutional network intelligent routing decision model, and implementing multi-source data fusion and consistency verification to solve data conflicts through a weighted voting mechanism. An intelligent result sorting and filtering system is established, a multi-dimensional evaluation strategy is adopted to output high-quality answers, a continuous learning and feedback optimization loop is constructed, system performance is continuously optimized through active learning and a graph shortest path algorithm, and the technical problem that knowledge base data and a service system cannot effectively and uniformly make decisions is solved.

The invention discloses a construction emergency early warning method and system, and the method comprises the following steps: collecting the three-dimensional coordinates of a constructor, combining a sliding time window with a wavelet packet energy entropy and other indexes, and generating a multi-scale movement disorder index through principal component analysis and fusion; continuously unstable persons are recognized according to the disorder index, after the trajectory of the persons is segmented, a weighted graph is constructed in combination with hidden Markov and building information model environment parameters, and the cognitive mismatch degree is calculated; mapping the cognitive mismatch degree to a space grid, calculating a local Moran index, fusing a density gradient and a mechanical operation sequence resonance result, and constructing a propagation weight matrix; constructing a heterogeneous graph based on weight matrix guidance, calculating risk influence propagation potential energy, combining historical disorder sequence analysis and relative entropy, and coupling to obtain a group-level instability pre-judgment value; and outputting a comprehensive critical level for the pre-judgment value over-limit individuals through motion trend prediction, spatial intersection and shortest path algorithms. The safety during building construction operation is improved.

The invention discloses a low earth orbit satellite network digital twin drive switching optimization method and system, and relates to the technical field of inter-satellite communication, and the method comprises the steps: building a digital twin system which is synchronously evolved with a physical LEO satellite network; predicting the link quality between each candidate satellite and the user terminal in a future time window based on a digital twin system; dividing a time window into a plurality of continuous time slices, constructing a directed weighted dynamic graph model which takes a satellite-time slice as a node and takes link comprehensive utility cost as an edge weight, and searching an optimal path in the directed weighted dynamic graph model by utilizing a shortest path algorithm so as to determine an optimal switching opportunity and a target satellite sequence; the optimal switching strategy is issued to a user terminal to be executed, and a link quality prediction result is corrected in real time through a feedback mechanism of the digital twin system to form closed-loop optimization; the method can effectively meet differentiated service quality requirements in a multi-service scene, and is suitable for a high-dynamic LEO satellite communication system.

The invention discloses a multi-source field-level blood relationship tracking method and system. The method comprises the following steps: extracting features from a multi-source heterogeneous system, matching templates, triggering a corresponding acquisition strategy, and outputting an original blood relationship log; reading an original blood relationship log to generate an abstract syntax tree, extracting a source / target field set to output a field-level mapping relation, further writing the field-level mapping relation into a graph database to form a blood relationship edge, writing metadata into a relational database, establishing a two-level index, and outputting a blood relationship graph capable of being quickly positioned; and taking the blood relationship map as input, returning a target path with the maximum sum of confidence coefficients by adopting a weighted shortest path algorithm, outputting a link-level traceability result, and displaying the link-level traceability result. According to the method, complete tracking of the field-level blood relationship is realized, the query response time is shortened to a millisecond level, rapid access to multiple types of data sources is supported, and the problems of insufficient blood relationship analysis precision, low query efficiency and weak multi-source adaptability in the prior art are solved.

The invention relates to the technical field of intelligent scheduling, and particularly discloses an intelligent scheduling decision control method and system for a distributed car washing robot, and the method comprises the steps: constructing a weighted graph model which comprises a vehicle position, obstacle distribution and path reachability, and dynamically adjusting the weight of an edge according to the path length, energy consumption and time; optimizing the graph structure by adopting an improved minimum spanning tree algorithm, and calculating a path efficiency index in combination with fuzzy logic and a neural network technology; on the basis of the optimized subgraph, applying a shortest path algorithm to obtain a local optimal path, and introducing a dynamic adaptation coefficient to evaluate the response capability of the path to environment change; fusing the path efficiency index and the dynamic adaptation coefficient into a comprehensive scheduling feature vector, inputting the comprehensive scheduling feature vector into a trained deep learning scheduling model, and predicting an optimal scheduling strategy in combination with a task priority and a robot resource state; and dynamically adjusting the moving path and the operation density of the robot according to a scheduling result, and realizing self-adaptive evolution and cooperative control of the system.

The invention discloses an irregular ship scheduling method and system considering uncertain harbor time, and a medium, and belongs to the technical field of shipping management. The method comprises the following steps: collecting ship, cargo, port and interference event data; generating an initial scheduling scheme by adopting a greedy strategy; generating multiple groups of random interference scenes based on Monte Carlo simulation; a two-stage stochastic programming model is constructed, in the first stage, income maximization serves as a target, and an initial plan is generated through damage and repair operator iterative optimization by means of a self-adaptive large neighborhood search algorithm; in the second stage, aiming at each interference scene, a recovery network is constructed for the influenced goods, and an optimal recovery strategy and adjustment cost are solved by utilizing a shortest path algorithm; and finally, outputting a scheduling scheme including a ship path, a navigational speed and a multi-scene recovery strategy through iterative optimization. According to the method, the earnings and the operation efficiency of the shipping companies are improved, the adjustment cost caused by uncertainty is reduced to the greatest extent, the benefits of the shipping companies and cargo owners can be balanced in a complex scheduling problem, and the service quality is improved.

The invention discloses a carbon dioxide seepage dominant channel judgment and permeation enhancement effect evaluation method and system, and the method comprises the following steps: obtaining three-dimensional image data through the three-dimensional CT scanning of a rock sample before and after a CO2 mineralization storage experiment reaction, extracting a crack network as a topological structure center line skeleton, calculating the topological indexes of a network structure, and calculating the permeability enhancement effect of the network structure; a fracture network topological structure model constructed based on a graph theory is coupled with a discrete fracture network model for CO2 flow simulation, an equivalent permeability tensor is obtained, an improved Dijkstra shortest path algorithm is adopted, spatial distribution of CO2 seepage dominant channels is obtained, dominant channel characteristics before and after transformation are compared with the equivalent permeability tensor, the seepage enhancement effect is quantitatively evaluated, and the CO2 seepage enhancement effect is obtained. And changing injection conditions to perform multi-group simulation under different working conditions, calculating the seepage enhancement effect and the mineralization reaction rate under different injection conditions, establishing a quantitative evaluation model of the mineralization sealing permeation enhancement effect, and realizing sealing effect prediction and seepage enhancement effect evaluation.

The invention discloses an electric power Internet of Things service scheduling method and device based on an SDN and an NFV, and a medium, and belongs to the field of virtual networks, and the method comprises the steps: receiving an electric power Internet of Things service request issued by a cloud network cooperative management platform through an SDN controller, and matching a corresponding VNF combination for the electric power Internet of Things service request; based on the control domain network topology structure, performing first path planning for the VNF combination through a weighted shortest path algorithm to obtain a first deployment path; constructing an optimization objective function of the first deployment path based on the dynamically adjusted time delay weight factor and load weight factor, and performing global optimization on the first deployment path based on the optimization objective function to obtain a second deployment path; and generating a deployment instruction based on the second deployment path, and issuing the deployment instruction to each corresponding physical node through the NFVO to perform VNF instance deployment so as to complete power Internet of Things service scheduling. Therefore, by implementing the method and the system, accurate scheduling of various services of the power internet of things can be completed according to the time delay requirement.

The invention relates to a bridge degradation identification and maintenance decision support method and system based on a knowledge graph, belongs to the technical field of traffic infrastructure intelligent operation and maintenance and engineering information processing, and solves the defects of weak data fusion capability, opaque causal modeling and non-traceable decision support in the prior art. The method comprises the following steps: acquiring and preprocessing multi-source heterogeneous data to generate a standardized data set; semantic alignment is carried out, and candidate entities and relations are extracted; constructing a knowledge graph body and loading the knowledge graph body into a knowledge graph; a self-adaptive quantile threshold value is adopted to binarize the factor intensity and the disease severity sequence, and a smooth point mutual information and a Spearman correlation coefficient are fused to learn a causal weight; complementing the influence relation of factors on the bridge through graph reasoning and calculating the weight; and finally, calculating a bridge degradation risk score, and outputting a high-confidence influence path based on a shortest path algorithm. According to the method, multi-source data fusion and degradation causal chain explicit modeling are realized, and a scientific basis is provided for a bridge maintenance decision.

The invention discloses an urban comprehensive park space-time network construction method and system based on crowd trajectory data. The method comprises the following steps: firstly, collecting, cleaning and dividing crowd trajectory data in a comprehensive park range; secondly, scenic spots in the comprehensive park are clustered, the number of optimal clusters is determined through clustering analysis, and all the clusters serve as all functional activity districts; then building a trajectory model through space projection and a shortest path algorithm, recovering a user moving trajectory path according to the crowd trajectory data, generating path node sequence data according to the timestamp of each trajectory point, and finally, taking the centroid of each functional activity area as each node of the space-time network, and combining each time period to obtain the user moving trajectory path. And constructing an undirected space-time network and a directed transfer network. The method has the advantages of efficient data processing, high modeling precision and perfect privacy protection, dynamic monitoring and space optimization analysis of the park people flow can be realized, and reliable data support and decision basis are provided for urban comprehensive park planning management.

The invention provides a construction method for load decomposition and transmission of a special-shaped beam curved template, and belongs to the technical field of building construction.The load change of each node of the curved template is monitored in real time by establishing a load jump identification matrix, and a supporting system abutting stability matrix is constructed to evaluate the bearing capacity of each abutting point; a graph theory shortest path algorithm is utilized to optimize a load transmission path and form a fluctuation evaluation vector, a prestressed reinforcement tension stability control matrix is constructed to realize symmetrical batch tension, and support system parameters and a tension program are adjusted in real time through a load transmission dynamic balance equation set. And a load transmission effect evaluation vector is established to perform continuity and controllability evaluation on an overall transmission path, and when the transmission efficiency is lower than a set value, the load distribution and path optimization program is executed again, so that the technical problem of instability of a support system caused by uncontrollability of the load transmission path in the construction process of the special-shaped beam curved template is solved.

The invention relates to the technical field of big data, and particularly discloses a natural language and semantic mapping-based business data model automatic construction method, which comprises the following steps of: performing structured analysis on a natural language demand input by business personnel, and extracting a dimension entity, a measurement index and a user intention; performing semantic matching on the business terms and the metadata fields by using a Sentence-BERT sentence vector model to generate a field mapping list; constructing a data consanguinity map based on a historical SQL, and reasoning an optimal multi-table association path through a shortest path algorithm by taking a center table as a root node; automatically generating a target wide table structure definition and a complete SQL (Structured Query Language) code by combining a template engine; and performing grammar and logic consistency verification on the output statement. According to the method, full-automatic, high-precision and interpretable end-to-end modeling from natural language requirements to executable wide tables can be realized, the data modeling efficiency and accuracy are remarkably improved, and the participation threshold of business personnel is reduced.

The invention provides a link state sensing dynamic service function chain deployment method in an F6G low earth orbit satellite optical network, and relates to the technical field of low earth orbit satellite optical network service function chain deployment. The method comprises the following steps: acquiring TLE data of space debris according to network topology information and network resource information of an F6G low earth orbit satellite optical network; preprocessing the TLE data of the space debris, and performing clustering processing by using a KMeans clustering algorithm; predicting the risk level of the risk fragment, and calculating the interruption duration of a risk link and a comprehensive risk value of the link; constructing a weighted satellite optical network topological structure based on the link logic distance; obtaining k optimal pre-deployment paths by using a K shortest path algorithm; constructing an optimization problem to carry out flow routing and VNF placement joint optimization; and if the constraint condition is met and no high-risk link causes business interruption, the service deployment is successful. According to the method, the acceptance rate and the resource utilization rate of the whole service of the system are effectively improved, and meanwhile, the average time delay of service deployment is reduced.

This invention discloses a city low-altitude user equilibrium system with generalized cost, comprising: constructing an air-ground cooperative three-dimensional transportation network for users to travel between origin and destination in low-altitude environments; defining a generalized path cost model and constructing an air-ground cooperative three-dimensional transportation network cost model based on the topology of the network; transforming the user equilibrium problem in the air-ground cooperative three-dimensional transportation network into a variational inequality model based on traffic flow within the network; and solving the variational inequality model using a combination of the K-shortest path algorithm and adaptive projection method to calculate the equilibrium flow of the air-ground cooperative three-dimensional transportation network, thereby completing the planning of the city low-altitude travel system. This system accurately characterizes many real-world factors considered by users when traveling in the air-ground cooperative network, providing decision support for urban management departments to effectively construct and fully utilize the performance of the city's three-dimensional transportation network.

This invention discloses a construction emergency early warning method and system. The method includes the following steps: collecting the three-dimensional coordinates of construction workers, using a sliding time window combined with indicators such as wavelet packet energy entropy, and generating a multi-scale motion disorder index through principal component analysis; identifying continuously unstable personnel based on the disorder index, segmenting their trajectories, and constructing a weighted graph by combining Hidden Markov Model and Building Information Model environmental parameters to calculate cognitive mismatch; mapping the cognitive mismatch to a spatial grid, calculating the local Moran index, and fusing density gradient and mechanical operation sequence resonance results to construct a propagation weight matrix; guiding the construction of a heterogeneous graph based on the weight matrix, calculating the risk impact propagation potential energy, and coupling historical disorder sequence analysis and relative entropy to obtain a group-level instability prediction value; for individuals whose prediction values ​​exceed the limit, outputting a comprehensive crisis level through motion trend prediction, spatial intersection, and shortest path algorithms. This invention improves the safety of construction operations.

The application discloses an edge computing network service function chain embedding method based on K shortest path, and aims at a distributed service function chain embedding problem under time delay constraint. In the case of meeting the end-to-end time delay constraint, a service function embedding algorithm based on K shortest path algorithm is designed to minimize the deployment cost. The application firstly proposes a service function embedding problem modeling method based on a weighted layered graph, and converts the service function chain embedding problem into a minimum cost path problem under time delay constraint in the weighted layered graph. Secondly, a service function chain embedding mechanism under time delay constraint is designed based on the weighted layered graph and K-linear measurement aggregation algorithm. Compared with the prior art, the application has better high performance and operability, and has practical significance for complex network applications in edge computing networks.

The application provides an automatic turning method and system, and relates to the technical field of power station maintenance, comprising: obtaining first information and second information, the first information is a sensor deployment scheme, sensor data and corresponding turning effect evaluation index of historical turning operation, and the second information is real-time monitoring data; obtaining third information by quantum annealing processing according to the first information; obtaining fourth information by Kalman filtering processing according to the first information and the second information; obtaining fifth information by dynamic programming processing according to the third information and the fourth information; and obtaining sixth information by fuzzy logic reasoning processing according to the first information and the fifth information. Based on quantum annealing processing and dynamic programming processing, combined with graph construction, random forest algorithm and shortest path algorithm and other technologies, the application realizes intelligent design of the optimal control strategy of the turning operation, can automatically adjust the turning operation according to the real-time monitoring data and the turning effect evaluation index, and improves the turning efficiency and precision.

The invention discloses a method for extracting a chemical reaction path based on a reaction network, and belongs to the technical field of material simulation. According to the method, firstly, the comprehensive weight of the edge is determined through the reaction frequency and the time preference factor, then, a plurality of candidate paths are screened out through the K-shortest path algorithm for follow-up analysis, and then the related paths of the time period interested by researchers are screened out. A bottleneck score and a cumulative transition probability score are determined through a transition state theory, a corresponding score is determined in combination with a time preference factor, and accordingly, paths are scored and key paths are screened out. According to the method, the key path for determining the change of the reaction product can be accurately screened from massive reaction paths, and the problem that a large-scale reaction network is difficult to analyze manually is solved. Through setting of the time preference factor and the time weight, a researcher can focus on analyzing an early-stage or later-stage reaction path according to a demand, and the flexibility and pertinence of path screening are improved.

The application relates to an improved image splicing method, and belongs to the technical field of image processing. The method comprises the following steps: performing field of view correction on an image to be spliced to obtain a calibrated image, performing feature point registration on the calibrated image to obtain an overlapping area, performing gray scale conversion on the overlapping area to obtain a gray scale histogram, adjusting the brightness of an evaluation image according to the gray scale histogram to obtain an equalized image, performing pixel difference mean value calculation on the equalized image to obtain a feature similarity graph, performing downsampling operation on the feature similarity graph to obtain a down-sampled feature graph, performing data processing on the picture, using a shortest path algorithm on the processed picture to obtain a shortest path, performing upsampling operation on the vertex in the shortest path to obtain a shortest path of new graph data, obtaining an optimal stitching line according to the shortest path, using a Laplace fusion algorithm to fuse the images according to the optimal stitching line, and obtaining a splicing result image, so that the efficiency and precision of image splicing are improved.

The invention relates to the technical field of data processing, in particular to a path traffic estimation method, a computer system and a computer readable storage medium. A fusion strategy of a K shortest path algorithm and an A * search algorithm is introduced to screen and complement candidate paths, a candidate path set is generated, and particle weight updating is performed based on three dimensions of travel time consistency, path consistency and detector testability so as to guide the candidate path set to evolve towards a better and more feasible direction; dual prior information of tensor solution and particle reconstruction is introduced, a joint least square problem of path flow estimation is constructed, and a stable solution can be kept under the condition that steering flow or path observation is incomplete. The objective of the invention is to solve the problem of how to realize accurate path flow estimation in a scene covered by a low mobile detector.

The application provides a user operation recommendation method under an AI platform, and belongs to the technical field of large language models.The application acquires multi-dimensional operation data of a user in real time through a distributed data acquisition system, processes page operation records by using a clustering compression algorithm, extracts inquiry content semantic features and historical interaction behavior patterns by using natural language processing and sequence identification algorithms, constructs a user operation intention graph, calculates the correlation strength by using a shortest path algorithm, accurately models the user intention, establishes a multi-modal fusion recommendation model based on a Transformer architecture, constructs an online learning system, calculates the user satisfaction degree by using an intention correlation degree function, dynamically adjusts the model parameters in real time by using a gating weight dynamic adjustment function, and combines offline precalculation and online retrieval optimization to ensure the recommendation accuracy and response speed, thereby solving the technical problem that the user operation recommendation of the AI platform is not accurate enough.

The application provides a method for evaluating interface bonding strength of plant fiber reinforced plastic, and belongs to the technical field of bio-based composite materials. In the application, the Dijkstra shortest path algorithm is used to calculate the path cost from the center position of a sample to each candidate emission point and select the candidate emission point with the minimum path cost as an optimized emission point. The optimal emission direction angle and optimal emission frequency are determined by performing fine search on the optimized emission point position according to the transmission signal propagation time and frequency attenuation value. Finally, the optimal parameters are used for ultrasonic transmission testing on all test points to establish an ultrasonic characteristic response matrix and input an interface quality evaluation model to output an interface bonding strength prediction value. The technical problem of insufficient detection accuracy caused by the difficulty in self-adaptive optimization of ultrasonic detection parameters during the evaluation of the interface bonding strength of plant fiber reinforced plastic is solved.

The invention discloses a partition-based airborne quantum network efficient entanglement resource distribution method, apparatus and device. The method comprises the steps of determining a long-distance multi-hop entanglement path of an airborne communication platform based on an improved shortest path algorithm; according to a long-distance multi-hop entanglement path, relay nodes between a source node and a destination node are divided into a plurality of first-class regions, each first-class region comprises a preset number of intermediate nodes, if the number of remaining nodes after path division is less than the preset number, the first-class regions are independently divided into a second-class region so as to establish multi-hop entanglement connection, sequential entanglement swap operation is adopted between adjacent sub-regions of a long-distance multi-hop entanglement path, and the sequential entanglement swap means that after entanglement swap is completed in a current sub-region, entanglement swap starts to be executed in a next sub-region so as to establish an entanglement link between a source node and a destination node. The invention provides an entanglement distribution scheme applicable to an airborne communication platform so as to improve network performance.

The invention relates to a power distribution overhead line lightning stroke fault unmanned aerial vehicle routing inspection route planning method, which comprises the following steps of: acquiring historical tripping line section data, power grid state data, lightning stroke area data and regional weather condition data, constructing a lightning stroke tripping degree evaluation system, and dividing lines into four types of extremely easy lightning stroke tripping, relatively easy lightning stroke tripping, general lightning stroke tripping and difficult lightning stroke tripping; routing inspection route pre-planning is carried out on lines with general and above tripping degrees, and original data acquisition and line investigation are completed; in a fault point circling evidence obtaining stage, a part point layering strategy is adopted, and a shortest path algorithm and an electronic fence technology are combined to generate a safe optimal route. According to the method, the problems of low fault searching accuracy, high missed identification rate and low efficiency of traditional manual line patrol are solved, the safety and path optimization of unmanned aerial vehicle patrol are improved, rapid positioning of lightning stroke faults is realized, and efficient technical support is provided for distribution network line lightning stroke fault disposal.

The application provides a power grid fault traveling wave positioning method based on a fusion optimization algorithm, comprising: establishing a dynamic virtual fault framework model of a power grid, randomly generating a plurality of virtual fault particles containing position coordinates, and constructing an initial virtual fault particle cluster; using a shortest path algorithm to calculate the topological path length of each virtual fault particle in the virtual fault particle cluster to all measurement points in the power grid, and then calculating a virtual fault space-time feature vector; setting the traveling wave arrival time when a real fault occurs as a target clustering centroid in a feature space, and calculating a feature matching fitness; constructing a non-convex optimization problem with the optimal feature matching fitness as a target, solving the problem using a fusion optimization algorithm, and thus obtaining a fault positioning result and a traveling wave velocity, so as to realize traveling wave positioning. The application can solve the problems of local optimum, slow convergence speed and high calculation cost in the prior art.

The invention relates to an emergency logistics transportation network time reliability assessment method and system, and belongs to the technical field of emergency logistics. The invention provides an efficient evaluation scheme based on state space decomposition and a Dijkstra shortest path algorithm in order to solve the technical problems that a traditional network communication reliability index cannot meet the timeliness requirement of emergency logistics and an existing algorithm is too high in calculation complexity. The technical scheme comprises the steps of determining network basic data; calculating and determining a state edge set; searching a feasible path in the determined working edge set; if not, searching in a larger edge set to judge the property of the state set; decomposing the uncertain state set based on the feasible path edge set and identifying feasible subsets; and recursively processing each subset. According to the method, the service level of the emergency logistics network under the rescue time constraint can be accurately evaluated, the calculation efficiency of a large-scale network is remarkably improved through algorithm optimization, and a scientific basis is provided for optimization management of the emergency logistics network.

The invention discloses a three-dimensional cable arrangement implementation method and system based on a Bentley platform, and the method comprises the steps: building a topological relation containing nodes and edges based on a cable trench center line, a cable trench frame and equipment arrangement information in a BIM model; connecting the intersection points of the cable trenches in the topological relation, so that the connected cable trenches are communicated with each other in the topological relation; searching a starting node and a termination node of each group of cables in the topological relation, and calculating a plane shortest path of each group of cables by using a shortest path algorithm; each node through which the shortest path of the cable plane passes is obtained, cable trench racks corresponding to the corresponding nodes are found in sequence, and the arrangement position of each cable on each cable trench rack through which the cable passes is calculated; and generating a three-dimensional cable entity according to the arrangement position of each cable on each cable trench frame through which the cable passes. According to the method, the three-dimensional arrangement of the cables can be automatically realized under the condition that a user does not need to draw the trend path line of each group of cables.

This invention discloses a route planning method, apparatus, device, and storage medium for avoiding traffic congestion. Based on the number of vehicles passing and the time of each vehicle's passage collected by each road surface sensor on each road segment, a weighted length for each road segment is determined. Based on the weighted length of the road segments enclosing each sub-region, a weighted area for each sub-region is determined. A first weighted graph is constructed using each sub-region as a node, where the weight of each node in the first weighted graph is the weighted area of ​​the sub-region corresponding to that node. The Dijkstra single-source shortest path algorithm is used to select a set of target sub-regions from all nodes in the first weighted graph. A second weighted graph is constructed using each road segment as a node, where the weight of each node in the second weighted graph is the weighted length of the road segment corresponding to that node. The Dijkstra single-source shortest path algorithm is used to select a set of target road segments from nodes located in the target sub-regions in the second weighted graph. This invention can predict road segments that may experience congestion.

The present application relates to a bridge degradation identification and maintenance decision support method and system based on a knowledge graph, belonging to the technical field of intelligent operation and maintenance of transportation infrastructure and engineering information processing, and solving the defects of weak data fusion capability, opaque causal modeling and non-traceable decision support of the prior art. The method comprises: acquiring and preprocessing multi-source heterogeneous data to generate a standardized data set; performing semantic alignment to extract candidate entities and relationships; constructing a knowledge graph ontology and loading it as a knowledge graph; using an adaptive quantile threshold to binarize the factor intensity and disease severity sequence, and fusing a one-point smoothing mutual information and a Spearman correlation coefficient to learn the causal weight; completing the bridge factor influence relationship and calculating the weight through graph reasoning; and finally calculating the bridge degradation risk score and outputting the high-confidence influence path based on the shortest path algorithm. The present application realizes multi-source data fusion and explicit modeling of the degradation causal chain, and provides a scientific basis for bridge maintenance decision-making.

The invention discloses a DC looped network-based power distribution network fault isolation method and system and a medium, and the method comprises the steps: constructing a power distribution network mathematical model based on a power distribution network topological structure, and enabling the power distribution network mathematical model to comprise element nodes and a connection relation between the element nodes, the element nodes comprise a circuit breaker node, a bus node, a line node and a distributed power supply node; generating a distance matrix based on the mathematical model of the power distribution network, wherein the distance matrix comprises the shortest path between the nodes; if a fault occurs, identifying a fault point based on the distance matrix; and based on the fault point and the distance matrix, tripping according to a path increasing sequence from the fault point. By constructing the mathematical model and the distance matrix of the power distribution network, the complex topology of the power distribution network is converted into a data structure capable of being quantitatively analyzed, the fault point can be quickly and accurately identified by using the shortest path algorithm, the fault positioning time is shortened, and the fault processing efficiency is improved.