122results about How to "Strong engineering practicability" patented technology

The invention relates to an underwater acoustic target recognition system and method based on multi-modal depth feature fusion, and belongs to the field of underwater acoustic target recognition. The method comprises the following steps: firstly, performing preprocessing on an obtained underwater acoustic target original audio and associated metadata, and constructing a multi-modal data set; and then the constructed multi-modal sample is input into an identification model, the model extracts deep representation of each modal through a multi-branch feature coding network, depth alignment and complementary aggregation of different modal features are realized by using a cross-modal cross attention mechanism guided by potential query, and a target identification result is output based on a decision network of mixed experts. According to the method, experimental verification is carried out on two disclosed underwater acoustic data sets, the experimental result verifies the effectiveness of the multi-modal deep fusion and hybrid expert adaptive decision strategy adopted by the method, and through mining the complementary advantages of acoustic features and semantic priori, the multi-modal deep fusion and hybrid expert adaptive decision strategy is obtained. And the robustness and generalization ability of the underwater acoustic target recognition system in the strong-noise and multi-working-condition environment are remarkably improved.

The invention relates to a heat supply prediction method and system based on spatial-temporal feature fusion deep learning, and the method comprises the following steps: S1, carrying out the collection and fusion of multi-source heterogeneous data, and constructing an integrated data set; s2, preprocessing the data; s3, constructing a graph structure model of the heat supply system, and constructing a weighted undirected graph; s4, constructing and executing forward calculation of the space-time double-flow deep network; s5, designing a composite loss function including mean square error loss and physical constraint loss, and performing joint optimization training on the space-time double-flow deep network; and S6, performing multi-step heat supply load prediction by using the trained model, outputting a heat supply load curve of each heat exchange station in a specified time period in the future, and integrating a prediction result with a heat supply scheduling system. The method has the advantages that the prediction precision is improved compared with that of a traditional machine learning model by capturing the spatial-temporal characteristics at the same time, and the advantages are more remarkable in extreme weather.

The invention relates to the technical field of building structure engineering, in particular to a simplified elastic analysis and design method for an integrated model of a partition wall structure, and provides a simplified elastic analysis and design method based on a physical mechanism and data driving. And instead, a practical design tool which can be directly used for engineering design, is seamlessly connected with the current specification and has definite physical significance is formed based on intelligent calibration of a large-refinement nonlinear analysis result. According to the method, quantitative correlation between elasticity and nonlinear performance is established, theoretical preciseness is guaranteed, and the method has extremely high engineering practicability and serves as preposition and supplement of refined nonlinear analysis to form a complete technical system from rapid scheme design to accurate performance verification.

The invention discloses an unbalance compensation method and system for an energy storage converter, and belongs to the field of power electronics and electric energy quality treatment. The system comprises a power instruction analysis module, a current reference generation module, a negative sequence current control loop module, a zero sequence control loop module, a positive sequence control loop module, a pulse width modulation module, a first conversion module and a second conversion module, the current reference generation module is respectively connected with the negative sequence current control loop module and the positive sequence control loop module; the third end and the fourth end of the negative sequence current control loop module are connected with the pulse width modulation module through the second conversion module; the third end and the fourth end of the zero sequence control loop module and the third end and the fourth end of the positive sequence control loop module are connected with the pulse width modulation module through the first conversion module. According to the method, the energy storage and compensation functions of the PCS can be seamlessly integrated under a unified control framework, so that the control system is greatly simplified, and the performance is remarkably improved.

The invention discloses a multi-layer semantic perception, distillation and semi-supervised cooperative training target detection method, and the method specifically comprises the following steps: constructing a data set: extracting a first part of images from image data, marking the first part of images to construct a supervised target detection data set, and taking the remaining images as an unmarked image data set, the data volume of the unlabeled image data set is greater than that of the supervised target detection data set; teacher model optimization: performing supervision training on the teacher model on the supervised target detection data set; constructing a teacher model, and executing self-distillation training on the teacher model; pseudo labels are generated for the unlabeled images through a teacher model, and adaptive screening is carried out based on confidence distribution; mapping a pseudo label to a strong enhanced sample through enhanced geometric transformation, carrying out semi-supervised training by using the strong enhanced sample and the pseudo label, and introducing a feature layer distillation constraint at the same time; optimizing a student model; and outputting the target detection model obtained through training.

The invention relates to the technical field of marine environment numerical simulation, in particular to a near-shore typhoon wave refined simulation method based on terrain adaptive grids and parameter dynamic correction, and the method comprises the steps: obtaining basic data and simulation parameters of a target sea area, constructing a computational domain and an initial grid, and constructing a target sea area; the initial grid is an unstructured grid fused with multiple physical constraint factors; performing optimization processing on the initial grid based on a numerical stability criterion to obtain a final calculation grid meeting a calculation convergence requirement; establishing a bidirectional coupling model, and applying the final computational grid to the bidirectional coupling model; carrying out localization iteration calibration on key physical parameters of the bidirectional coupling model to obtain an optimal parameter set; and carrying out typhoon wave process simulation calculation and constructing a typhoon wave feature database by utilizing the final calculation grid and the optimal parameter set, and realizing high-precision simulation and prediction of the typhoon wave process by constructing an adaptive optimization grid, a bidirectional coupling model and a parameter localization calibration mechanism.

This invention relates to the fields of injection molding quality control and artificial intelligence, specifically to a method and system for predicting warpage defects in injection molded products based on a physical information neural network. The method includes: acquiring the basic parameters of the injection molded product and a physical information neural network; collecting measured data and randomly selecting physical sampling points; substituting the measured data and physical sampling points into the network using a double loss function training method; the measured data includes the basic parameters and corresponding measured warpage displacement values; the physical sampling points output corresponding predicted temperature fields, predicted internal stress fields, and predicted warpage displacement fields through an output layer; inputting the basic parameters of the product to be predicted into the trained network, and outputting the warpage defect prediction results. This invention balances data-driven accuracy with the reliability of physical mechanisms, solving the technical problems of pure data-driven models relying on a large number of defect samples and the low efficiency of traditional physical simulation.

This invention belongs to the field of data prediction technology, and provides a method and system for predicting solidification cracks in alloy welding. The method includes: acquiring the thermophysical parameters, scanning speed, and horizontal and vertical distances from the solidification point to the welding point of the alloy to be tested; calculating the theoretical angle between the scanning speed direction and the normal to the fusion line based on the horizontal and vertical distances from the solidification point to the welding point; establishing a continuous growth limiting factor calculation model based on the thermophysical parameters, scanning speed, and theoretical angle, and determining the derivative expression model between the solid-liquid interface temperature and the square root of the solid fraction; establishing a crack sensitivity index calculation model based on the continuous growth limiting factor calculation model and the derivative expression model; converting the crack sensitivity index calculation model into a data curve, and obtaining the welding solidification crack prediction result based on the data change characteristics of the target segment in the data curve. This scheme has a simple calculation process, strong engineering applicability, and improves the accuracy of solidification crack prediction.

The invention discloses a building engineering CAD drawing intelligent identification method and system, a terminal and a medium, and the method comprises the steps: determining a drawing frame identification range, building an original data set, and carrying out the processing based on the original data set, and obtaining a training data set, the training data set comprises a plurality of pictures marked with a drawing frame range and a drawing frame type; training a yolov8 model based on the training data set to obtain a picture frame range and type identification model; reasoning the CAD drawing based on the drawing frame range and type identification model to obtain a drawing frame range and type reasoning result, performing coordinate mapping processing on the drawing frame range and type reasoning result, and recording the result into a drawing identification JSON file. According to the method, the reasonable boundary range and the drawing frame type of the effective design content can be identified from the CAD drawing, so that a subsequent application layer can conveniently develop an automatic drawing frame application algorithm based on the boundary range.

The application provides a deep geothermal resource prediction method based on mechanism-space-distribution fusion, comprising: constructing a multi-dimensional heterogeneous fusion feature system cooperated by a mechanism driven layer, a space perception layer and a data distribution layer, explicitly injecting radioactive heat potential, heat-mass transfer coupling factor, multi-scale space singularity index and unsupervised anomaly score; adopting a recursive feature elimination algorithm to dynamically screen core geochemical fingerprints; fusing gradient boosting tree, random forest and extreme random tree to construct a ternary consensus integrated prediction module, and outputting joint prediction probability through soft voting; based on recall rate anchoring strategy, optimizing asymmetric decision boundary to generate geothermal potential prediction map. The prediction result of the application is highly consistent with the fault structure zone, effectively solves the problems of mechanism loss, high false alarm rate and small sample overfitting, and provides an intelligent technical solution with high precision, low false alarm and interpretability for deep concealed geothermal field exploration.

The application relates to a device performance test method and device, computer equipment and a storage medium. The method is applied to an upper computer, the upper computer is in communication connection with a benchmark communication device and a to-be-tested communication device respectively, the benchmark communication device and the to-be-tested communication device are in communication connection through at least one line, and the method comprises the following steps: acquiring a test strategy for data receiving performance test of the to-be-tested communication device; controlling the benchmark communication device to send message data to the to-be-tested communication device through at least one target line matched with the test strategy; acquiring message receiving conditions of the to-be-tested communication device for receiving the sent message data through the target lines; and determining whether the data receiving performance of the to-be-tested communication device is normal according to different message receiving conditions. The method can effectively detect the data receiving performance of the device.

This invention relates to the fields of tunnel engineering and 3D geological modeling technology, specifically to an intelligent modeling method and system for 3D geological uncertainty in tunnels based on transition probability geostatistics and sparse boreholes. The method includes: S1, integrating multi-source data to construct a 3D geological conceptual model; S2, statistically characterizing a one-dimensional transition probability matrix, calculating and fitting a spatial continuity and 3D anisotropic variability function model; S3, calculating the prior spatial probabilities and transition adjustment factors for various lithologies, obtaining the posterior lithology distribution of nodes through Bayesian intelligent updating, and initially assigning lithology categories to nodes through random sampling; S4, assigning the most probable lithology category to each grid node, calculating the variance of lithology values ​​across all implementations, and measuring model uncertainty; S5, outputting the optimal 3D uncertainty model for the tunnel; and S6, verification and evaluation. This invention can effectively achieve 3D heterogeneous modeling and explicit quantification of uncertainty under strong geological constraints.

This invention belongs to the interdisciplinary field of artificial intelligence and geological resource assessment, specifically relating to a method and system for predicting the energy storage potential of salt caverns based on multi-source geological information. It aims to address the problems of low prediction accuracy and difficulty in balancing breadth and precision in existing technologies due to single-source data, static models, and lack of adaptive capabilities. The method includes: acquiring multi-source data such as seismic, well logging, core, and geostress data; constructing a geological feature fusion vector containing seven core parameters; establishing a high-dimensional nonlinear mapping model driven by a deep neural network; dynamically adjusting the prediction range based on data coverage density and confidence level; and achieving continuous model iteration through online incremental learning. The system integrates data quality assessment, anomaly handling, and distributed computing modules. By adopting the above technical solutions, this application can achieve a significant improvement in prediction accuracy and adaptive intelligent adjustment of the prediction range.

The invention discloses a sparse sensor optimization layout method for battery thermal safety monitoring. The method comprises the following steps: constructing a full-working-condition temperature field data set through high-fidelity simulation data; defining a multi-task loss function fusing the overall reconstruction error, the hotspot monitoring error and the spatial dispersion; and with minimization of the loss function as a target, an optimal sensor distribution point is automatically searched by adopting an optimization algorithm. According to the method, the problems of sensing blind areas and early warning lag existing in empirical layout are solved, high-precision temperature field reconstruction and early thermal safety early warning can be achieved with the minimum number of sensors, the reliability is high, the cost is low, and the method is suitable for thermal management design of various lithium ion battery systems.

This invention discloses an integrated planning method and system for a multi-jurisdictional unmanned aerial vehicle (UAV) service system. The method constructs an overall planning model with the goal of minimizing total cost, and sequentially establishes a front-end UAV allocation model and a back-end battery swapping station allocation model. With the objectives of minimizing average response time and minimizing the total expected queue length, respectively, the total number of UAVs, charging stations, and backup batteries, as well as the jurisdiction-level configuration scheme, are obtained. This invention achieves integrated collaborative planning of front-end transportation and back-end battery swapping, reducing the total system cost and average response time, balancing the operating load of each jurisdiction, effectively avoiding service interruptions due to a lack of available batteries during peak periods, and significantly improving system reliability and engineering practicality.

This utility model belongs to the field of storage device technology, specifically relating to a device and system for collecting leaked ethylene glycol aqueous solution. It includes a collection tank body, a water inlet, a solenoid valve, a vent, a level gauge, a signal terminal, a drain outlet, a detection port, a controller, and a collection tank base. The water inlet is located on the top left side of the collection tank body via a straight pipe, the signal terminal is installed on the top right side of the collection tank body, and the drain outlet is located at the bottom of the collection tank body via a straight pipe. This utility model, through the coordinated design of the collection tank body, solenoid valve, level gauge, and controller, achieves automatic collection and alarm control of leaked ethylene glycol aqueous solution. When the liquid level reaches the alarm threshold, the controller automatically closes the solenoid valve at the water inlet and sends a signal to prevent the leaked liquid from continuing to spread. Simultaneously, manual collection is achieved through the drain outlet, effectively preventing the slightly toxic ethylene glycol aqueous solution from harming people and the environment, and significantly improving the safety of indoor ski resort air conditioning systems.

This invention discloses a method, apparatus, device, and storage medium for depth extraction of the focus stack weight domain. The method includes: acquiring a multi-focal plane image sequence; calculating focus sharpness pixel-by-pixel and normalizing it along the focal plane to generate an initial weight map; using the original image as a structural reference to perform edge-preserving filtering on the initial weight map to obtain an optimized weight map; constructing a weight-focal plane curve based on the optimized weight map, and sequentially performing three levels of logical judgment: the first level removes textureless regions based on the maximum weight value; the second level removes high-reflectivity false peaks based on waveform flatness; and the third level filters candidate focal plane positions based on peak focus sharpness; and performing sub-pixel fitting on the selected candidate focal plane positions to convert them into physical depth and generate a 3D point cloud. This invention effectively solves problems such as false points on textureless backgrounds, false peaks on highly reflective surfaces, edge breaks in weak textures, and limited depth accuracy through edge-preserving filtering to optimize the weight map, three-level progressive judgment, and sub-pixel fitting.

The application relates to a plane circle center point-based SolidWorks standard part automatic installation method for a parameter-free model, and belongs to the field of computer-aided design and three-dimensional mechanical design automation. The method first selects any part plane and any assembly hole on the part plane through a point selection mode; a sketch is created based on the geometric boundary of the part plane, and the coordinates of the sketch are determined according to the geometric boundary position information of the part plane; all assembly holes with the same hole feature on the part plane are automatically identified according to the extracted selected assembly hole feature, and corresponding sketch coordinates are established; sketch points are established for all sketch coordinates under the part plane; and the sketch-driven part array function is called, after manually assembling a standard part at any sketch point, the standard part assembly is automatically executed at all sketch points. The application can automatically batch install standard parts by using the sketch-driven part array function of an assembly body.

The invention relates to a tight coupling vision inertial odometer method based on a pulse camera brightness change rate, and belongs to the field of computer vision and robot positioning and navigation. The method comprises the steps of 1) VIO system preparation and data preprocessing, 2) visual feature extraction and pulse observation value calculation, 3) IMU pre-integration, and 4) tight coupling optimization model construction and solution. During operation of the system, for each sliding window, the optimization process of a predicted state vector is completed through the steps 2)-4), carrier motion state estimation at the latest moment in the current sliding window is output, then the sliding window is updated, and the steps 2)-4) are cycled, so that the system continuously outputs high-frequency and high-precision real-time motion state estimation. According to the invention, the microsecond brightness differential signal of the pulse camera is converted into continuous physical supervision on the motion state, and the precision and robustness of the system in challenging scenes such as high speed and dynamic illumination are remarkably improved in a tight coupling mode on the premise of not changing the VIO main body architecture.

The invention discloses a height and width limiting device for a newly-built highway of highway engineering. The height and width limiting device comprises supporting legs symmetrically arranged on the two sides of a road surface, an intercepting rod horizontally installed between the top ends of the pair of supporting legs, a displayer right facing the vehicle coming direction, a distribution box integrated with a control component and a base embedded and fixed in a roadbed. Wherein the supporting legs and the intercepting rods are both of telescopic structures, and the bottoms of the supporting legs are in sliding connection with the base; an identification module and an intelligent control module are integrated in the distribution box, the intelligent control module is electrically connected with the supporting legs, a driving part of the intercepting rod and the displayer, and the vertical height of the supporting legs and the transverse width of the intercepting rod can be synchronously adjusted according to vehicle size detection signals. The system has the beneficial effects that full-process intelligent management and control of early warning, active avoidance, urgent danger prevention and remote alarm can be realized, and a rigid collision accident between a vehicle and the device is avoided.

This invention discloses a method and system for fault diagnosis of industrial equipment under complementary label constraints, belonging to the field of industrial intelligent operation and maintenance and fault prediction health management technology. The method includes: collecting and preprocessing equipment vibration signals; constructing a dual-head deep network based on one-dimensional residuals as a complementary label learning model; generating a joint probabilistic loss function using complementary labels based on maximum likelihood estimation, enabling the model to learn fault features from "negative" labels; and achieving high-precision fault classification using the trained model. This invention applies the complementary label learning paradigm in weakly supervised learning to industrial equipment fault diagnosis, achieving a diagnostic accuracy of over 90% on multiple standard bearing datasets such as CWRU and MFPT. This method significantly reduces the data labeling threshold and effectively solves the pain points of scarce fault samples and difficult labeling in industrial scenarios, possessing significant practical application value.

The invention provides a log analysis method and system based on a large language model, and belongs to the technical field of log analys.The method comprises the steps that anti-fact rewriting is conducted on a to-be-analyzed log, and multiple log variants are obtained; log parameters are extracted from the log variants through the large language model to serve as intermediate variables, and the confidence coefficient of each intermediate variable is determined; performing correctness scoring on each intermediate variable based on statistical information of a historical log corpus knowledge base; determining a comprehensive score of each intermediary variable according to the confidence coefficient of the intermediary variable and the correctness score of the intermediary variable; and screening the medium variable with the highest comprehensive score as a log parameter of the log to be analyzed, and generating a log template of the log to be analyzed according to the log parameter of the log to be analyzed. According to the log analysis method, the stable semantic structure of the log can be more emphasized in the log analysis process, and the accuracy and generalization ability of log analysis are improved.

The invention belongs to the technical field of lithium batteries, and particularly relates to a module structure reliability checking method for cell expansion. Comprising the following steps: S101, acquiring cyclic expansion force data of a battery cell group; s102, processing the cyclic expansion force data and extracting characteristic values in sections; s103, establishing a simulation model and calculating an initial state; s104, calculating the stress state of the module in stages; and S105, calculating and checking fatigue damage. According to the method, the expansion force change curve under the real working condition is obtained by implementing the multi-cell cyclic expansion experiment, the maximum expansion force and the minimum expansion force are extracted in a segmented mode based on the curve, and the fatigue damage accumulated value of the structural part under the alternating load is calculated in a segmented mode in combination with the simulation model. Therefore, accurate and efficient checking of the structural reliability of the battery module in the whole life cycle is realized.

The application provides a polymer material life prediction method and system considering bidirectional coupling, and aims to solve the problem that the permeability of the polymer material suddenly increases due to hydrogen-induced damage accumulation under a high-pressure hydrogen environment. The method obtains material parameters and service boundary conditions, converts pressure into surface concentration, alternately performs mechanical and diffusion-damage evolution solving in a finite element increment step, modifies the stiffness by using the damage variable of the last step to calculate the hydrostatic stress of the current step, modifies the effective diffusion coefficient by using the stress and the damage variable of the last step, solves the hydrogen diffusion equation and updates the damage variable of the current step, and constructs a bidirectional positive feedback coupling closed loop. Finally, the residual life is output based on the permeation threshold or the damage critical value. The application is mainly used for life evaluation of polymer materials in high-pressure hydrogen storage and transportation equipment.

The application discloses a farmland point cloud ground separation method and system based on topological persistence analysis, and belongs to the technical field of the cross of precision agriculture and point cloud data processing technology, and comprises the following steps: pre-processing and coordinate alignment of three-dimensional point cloud data of a farmland environment; projecting the three-dimensional point cloud to a two-dimensional plane and performing rasterization processing, and then generating a two-dimensional elevation field; topologically decomposing the two-dimensional elevation field by adopting a step-by-step threshold scanning, extracting connected components in each layer of binary results, and tracing the evolution process of the connected components between adjacent elevation layers; calculating topological persistence features of each connected component; classifying the ground and crops based on the topological persistence features and the spatial features of the connected components; and outputting the classified ground point cloud and crop point cloud. The application solves the technical problems of strong parameter dependence and poor robustness of the existing method, and provides high-quality basic data for precision agriculture application.

The present application relates to the technical field of building structure engineering, in particular to a simplified elastic analysis and design method for integrated model of partition wall structure, which proposes a set of simplified elastic analysis and design method based on physical mechanism and data driving. The method is not a simple application of traditional empirical coefficient, but an intelligent calibration based on a large number of refined nonlinear analysis results, forming a practical design tool which can be directly used for engineering design, seamlessly connected with the existing specification and has clear physical meaning. The quantitative correlation between elastic and nonlinear performance is established, which not only guarantees the theoretical rigor, but also has strong engineering practicability. As a preposition and supplement of refined nonlinear analysis, the method forms a complete technical system from rapid scheme design to accurate performance verification.

The application discloses a kind of unknown relay transceiver auxiliary-based TDOA passive positioning method and system, can realize real passive positioning, existing relay auxiliary positioning method is dependent on own continuous emission signal to obtain two-way TOA observation, it is difficult to apply to passive or non-cooperative target positioning scene;The application is based on the TDOA observation quantity of target itself radiated signal and is positioned, without actively emitting signal, applicable to passive target and high concealment requirement application scene.By constructing two complementary TDOA observation models, the joint positioning of relay and target can be realized at a single observation moment, effectively reducing the dependence on the continuity of observation data, and improving the system robustness in complex environments;By semi-definite relaxation technique, a global initial solution is obtained, and then a weighted least squares is used for fine error correction.Under the condition of moderate observation noise, the positioning accuracy of the proposed algorithm can approach the Cramer-Rao lower bound, which is better than the existing positioning method without joint correction.

The invention discloses a multilayer multi-pass welding path optimization method based on physical information fusion, and relates to the technical field of advanced manufacturing welding. According to the method, three-dimensional welding path planning is dimensionally reduced into a two-dimensional control point optimization problem through control point parametric modeling, a penalty function fusing gravity, thermal power, fluid dynamics and other multi-physical field effects is constructed, and a particle swarm optimization algorithm introducing a sequence constraint module and improving a speed updating formula is adopted for solving. And Monte Carlo simulation and a robustness enhancement mechanism fed back by a sensor are integrated. The technical defects that a traditional method neglects multi-physics field coupling, is prone to falling into local optimum, lacks robustness and is complex in calculation are overcome, multi-layer and multi-pass welding path planning with global optimization, high physical consistency and high engineering practicability is achieved, welding efficiency, forming precision and structural performance are remarkably improved, and the method is suitable for robot online welding scenes.

The application discloses a kind of service concrete penetration type anti-freezing protective material and preparation method thereof, belong to concrete protection technical field.The composition of the protective material is: organic silicon modified penetration enhancement component 30~60 parts, nano-crystalline component 10~30 parts, microbial self-repairing component 5~20 parts, composite silane coupling agent 2~8 parts, penetration accelerator 1~5 parts, stabilizer 0.5~3 parts, defoaming agent 0.1~1 part, water 10~50 parts.The application constructs "hydrophobic barrier-crystallization densification-microbial self-repairing" triple synergistic protection system, solves the technical bottleneck that existing concrete protective material penetration depth is shallow, long-acting protection stability is poor, has no active crack repair capacity, construction is complicated, and on-site adaptability is poor.The application preparation process is simple, product performance is stable, cost-effective, can long-acting improve the frost resistance of concrete structure in severe cold area.

The invention discloses an optimal path dynamic planning method for a crawler-type unmanned vehicle field environment, and the method comprises the steps: 1, cost calculation: discretizing the environment where an unmanned vehicle is located into a grid map comprising a plurality of grids, and taking the central point of each grid as a path planning node; the method comprises the following steps: firstly, executing a dynamic grid granularity self-adaptive operation driven by a slip risk, and then calculating the moving cost from a current node to any subsequent node; step 2, calculating and updating the cost value of the current node based on the movement cost and the cost value of the subsequent node, and determining an optimal subsequent node K, the cost value being based on the estimated cost value calculated by the subsequent node; step 3, a turning limit checking step: after the optimal subsequent node K is determined, checking and setting a limit mark for judging whether the current node S turns or not; step 4, starting from the starting node, sequentially checking the turning limit mark of each node s; and performing a path reconstruction step until the target node is reached.