21results about How to "Avoid invalid calculations" patented technology

The application relates to a traditional Chinese medicine constitution identification method based on Al tongue surface image analysis, and the method comprises the following steps: collecting tongue surface information and inquiry information of a user, and identifying and obtaining tongue surface joint features; collecting time sequence data of the user, calculating time sequence mutual information, combining constitution theory knowledge constraints, grading determining the correlation level and weight of the tongue surface joint features and each constitution, and constructing a dynamic weight mapping relationship; performing weighted accumulation calculation on the tongue surface joint features combined with the inquiry information to obtain original scores of each constitution; constructing a constitution correlation knowledge base, quantifying conflict values between each constitution based on a light AI constitution correlation classification model, eliminating conflict constitutions through Bayesian probability fusion, obtaining calibrated constitution scores, and performing constitution determination. The application realizes objective constitution quantification under multi-dimensional feature fusion, constructs a weight mapping system graded according to the correlation closeness, significantly improves the accuracy of constitution identification, and effectively avoids invalid calculation and repeated elimination in constitution identification.

This invention discloses a knowledge-enhanced multi-agent decision-making method for welding deformation control in ship assembly subgroups. The method includes: constructing a welding process knowledge graph using a large language model based on welding process data; building a multi-agent collaborative framework for ship assembly subgroups; a process planning agent generating a process plan including welding sequence and welding parameter combinations; a deformation simulation agent performing welding deformation simulation calculations and outputting deformation prediction results; and a central coordinating agent triggering multi-agent collaborative iterative optimization based on the comparison of deformation prediction results with tolerance constraints, outputting the optimal welding process plan that meets deformation control requirements. This invention, by constructing a welding process knowledge graph, structurally represents the welding deformation mechanism, process parameter rules, and historical cases, and achieves knowledge-driven process decision-making based on a multi-agent collaborative mechanism, effectively solving the problems of lagging welding deformation control and reliance on experience in process parameter selection in traditional methods.

The application discloses a design method and system of a two-dimensional material loaded metal monatomic catalyst, comprising the following steps: firstly, generating a substrate structure by using a random strategy, a space group and graph theory; then, removing and optimizing the substrate structure according to atomic environment and lattice constant comparison; then, confirming a stable substrate structure by using a density functional perturbation theory method and ab initio molecular dynamics calculation; then, loading a monatomic transition metal on the substrate to obtain a monatomic catalyst model, and constructing a catalyst attribute database by using first principle calculation; finally, designing a monatomic catalyst by machine learning and database interpretation analysis. The application can quickly obtain a target two-dimensional material loaded metal monatomic catalyst by combining high-throughput screening method, first principle calculation and machine learning.

The present application relates to the technical field of medical film, and particularly relates to a medical film quality detection system based on multi-parameter fusion, which comprises an acquisition module, a discrete determination module, an identification module, a risk determination module, an adjustment module and an early warning module. The present application takes a dynamic discrete coefficient as a trigger condition, analyzes the contribution of each process parameter to the current thickness fluctuation to identify the primary root cause, forms a quantitative process risk index by comprehensively considering the out-of-control degree of the root cause parameter and the thickness deviation, and according to the process risk index, an adjustment instruction with clear direction and strength suggestion can be sent, and the adjustment efficiency is evaluated after adjustment, early warning is given when the control loop fails or the problem escalates, and the problems of lagging quality defect discovery and blind and lagging process adjustment caused by the failure to quickly and accurately locate the process abnormal root cause in the complex multi-process coupling production process are effectively solved.

This disclosure provides a method, apparatus, device, medium, and product for matching geographic sites. The method involves dividing the geographic site based on its location information to obtain a grid index; determining a candidate grid range around the site to be matched based on the grid index; the candidate grid range includes candidate matching sites corresponding to the site to be matched; determining the geographic location difference between each candidate matching site and the site to be matched, and determining candidate matching sites that meet geographic distance conditions based on the geographic location difference to obtain a target matching site; determining the spherical distance between the target matching site and the site to be matched to obtain a target geographic distance; and identifying the target matching site corresponding to the target geographic distance that is less than a preset spherical distance threshold as a successfully matched site of the site to be matched.

The invention relates to the technical field of image processing, and discloses an operation scene real-time dynamic reconstruction method and system based on three-dimensional Gaussian sputtering. The method comprises the following steps: extracting spatial-temporal characteristics of a soft tissue deformation Gaussian subset through a HexPlane spatial-temporal encoder; fusing the decoded feature vectors to generate a soft tissue deformation parameter set; a deformation field Jacobian matrix of Gaussian elements in the soft tissue deformation Gaussian subset is calculated, a local volume strain rate is obtained through determinant operation, when the strain rate exceeds a preset threshold value, self-adaptive densification operation is executed, and new Gaussian elements inherit parent Gaussian element deformation parameters and are updated to a corresponding set; and combining the updated parameters to carry out probabilistic boundary allocation and transmissivity perception rendering to obtain a reconstruction result. The accuracy, the physical authenticity and the stability of real-time dynamic reconstruction of the operation scene are improved.

This application relates to a method, apparatus, computer equipment, and medium for sensing the congestion status of quay cranes at port terminals. The method includes: detecting whether sensing conditions for quay crane congestion status are met; the sensing conditions are that the quay crane congestion route change function is enabled and the vehicle has trailer information; when the sensing conditions are met, determining the nearest left-turn and right-turn segments to the vehicle; detecting collision risk areas in the left-turn and right-turn segments, denoted as a first risk area and a second risk area; detecting whether quay cranes exist in the first and second risk areas; when quay cranes exist in both the first and second risk areas, constructing a route change request message. This application can sense the quay crane congestion status in the terminal environment in real time, accurately identify the quay crane congestion risk in turning segments, and promptly initiate route change requests, improving driving safety and route planning flexibility.

The invention discloses a vertical parking path planning method, which decouples complete path planning into two continuous stages of coarse alignment and fine parking, and predefines a path configuration formed by splicing basic geometric curves according to a fixed sequence for each stage. A discretized finite parameter set is established for key geometric parameters in the configuration, and a traditional continuous path search problem is converted into a traversal and verification problem of a finite parameter combination. The method specifically comprises the steps of traversing parameter combinations, generating candidate paths in batches in a reverse calculation mode, and performing rapid collision detection and screening on the candidate paths. Through the technical means of structural decoupling-parameter pool traversal, the computing power redundancy of a traditional random sampling algorithm in an open scene is fundamentally avoided, and the solving difficulty of complex numerical optimization is also avoided, so that the order of magnitude improvement of the computing efficiency is realized on the premise of ensuring the geometric feasibility and safety of the trajectory, and the method has the advantages of being high in practicability and easy to popularize. And the requirement of a vehicle-mounted system on millisecond-level real-time planning of a vertical parking track can be met.

This invention relates to the field of energy consumption monitoring technology for injection molding equipment, and discloses a method for early warning of abnormal energy consumption in injection molding machines. During continuous production, injection cycle and power sampling objects are established, segmented according to process phase, and a piecewise linear power function is formed. Phase boundaries are determined based on process event signals. Through equal-length discretization, amplitude normalization, curvature energy calculation, and phase energy ratio analysis, a fixed benchmark for removing extreme values ​​is established. Anomaly markers are generated by combining the curvature mutation multiple with the synchronous energy consumption increment, and the abnormal phase, warning level, and warning result are output. This solves the problems of difficulty in locating specific process actions in whole-machine energy consumption monitoring, difficulty in comparing data from different cycles and phases, and the susceptibility to misjudgment based on a single threshold, improving the interpretability of abnormal energy consumption analysis and the targeted nature of maintenance.

The application relates to the technical field of traffic network topology optimization and graph sequence technology, and particularly relates to a traffic network optimization method based on a graph sequence problem of a weighted graph, which comprises the following steps: S1: acquiring a network topology structure and a degree sequence of a target traffic network and a preset weighted graph type; S2: selecting a corresponding weighted graph solving algorithm based on the preset weighted graph type; S3: judging whether the degree sequence of the target traffic network is a graph sequence based on the weighted graph solving algorithm; if yes, executing step S4; S4: generating a weighted graph of a corresponding type based on the selected weighted graph solving algorithm and the degree sequence of the target traffic network; and S5: optimizing the network topology structure of the target traffic network based on the weighted graph of the target traffic network, and generating an optimized traffic network. The application can improve the accuracy and reliability of traffic network topology optimization.

The application relates to the field of fluid pressure control, in particular to a pneumatic actuator flow self-adaptive regulation control method and system. The method comprises the following steps: constructing a health sample; fitting a relationship curve between total air inlet flow of the health sample and corresponding displacement setting value, self-adaptively dividing a plurality of displacement setting value intervals, and assigning a clustering label to each interval; clustering and obtaining a plurality of clustering clusters and corresponding cluster centers; matching a clustering label interval of a real-time running sample according to a displacement setting value of the real-time running sample, and calculating a flow leakage index; dynamically calculating a self-adaptive convergence threshold value according to the flow leakage index, and constructing a performance index model fusing action execution time length and displacement deviation to generate a corresponding performance index; and performing control parameter iterative optimization taking the performance index as an evaluation standard. The application has the effect of self-adaptively regulating flow control parameters according to the actual flow leakage degree of the pneumatic actuator.

The invention provides a method, device and equipment for screening diatomic catalysts for nitrogen reduction reaction, and relates to the technical field of catalysts.The method comprises the steps that multiple candidate diatomic catalysts for nitrogen reduction reaction are obtained, and all the candidate diatomic catalysts are divided into multiple training catalysts and multiple catalysts to be screened; inputting all the to-be-screened catalysts into the catalyst screening model to obtain a catalyst screening result output by the catalyst screening model; the catalyst screening model is obtained by training based on all the training catalysts and the key feature descriptors. According to the technical scheme, the catalyst screening model is obtained through training according to the key feature descriptors related to the reaction activity and the training catalyst, the catalyst with the excellent catalytic activity can be efficiently screened out, a large amount of invalid calculation in high-throughput calculation is avoided, waste of calculation resources and consumption of research time are reduced, and the calculation efficiency is improved. Therefore, the screening efficiency of the catalyst can be effectively improved.

The invention provides a gear parameter determination method and device, equipment, a storage medium and a program product, and relates to the technical field of electric drive speed reducers. The method comprises the steps that the design requirement of the electric drive speed reducer is obtained, and the design requirement comprises the transmission ratio, the minimum tooth number limitation and a plurality of engineering constraint conditions; generating a plurality of feasible tooth number combinations of the high-speed gear pair and the low-speed gear pair according to the transmission ratio and the minimum tooth number limit; based on the multiple feasible tooth number combinations and at least one part of engineering constraint conditions, a preliminary feasible scheme is determined, and the preliminary feasible scheme comprises the feasible tooth number combinations, the center distance range and the tooth width range; based on the preliminary feasible scheme, obtaining one or more groups of optimal solutions of macroscopic parameters of the high-speed gear pair and the low-speed gear pair through a multi-objective optimization model under the condition that all engineering constraint conditions are met; and determining a target gear parameter scheme according to the one or more groups of optimal solutions. The method can improve the gear parameter optimization efficiency of the electric drive speed reducer.

The invention discloses an automatic home layout method and device and a storage medium, and relates to the technical field of artificial intelligence, and the method comprises the steps: obtaining the house type structure information of a target space and the commodity information of candidate home commodities, and then determining an effective layout region of each candidate home commodity, screening out a feasible home commodity set from the candidate home commodities based on the effective layout area; based on a preset sorting strategy, sorting the commodities in the feasible household commodity set to obtain a sorting result; determining a to-be-arranged target commodity combination from the feasible household commodity set according to a sorting result; and performing layout optimization on the to-be-arranged target commodity combination by taking the layout region set as a search space, and outputting a layout scheme meeting a preset cost threshold value. According to the method and the device, the problems of low generation efficiency and slow response speed of the automatic home layout scheme in the prior art are solved, and the technical effect of remarkably improving the scheme generation speed on the premise of ensuring the layout rationality is realized.

The invention discloses a binocular stereoscopic vision underwater concrete three-dimensional reconstruction method based on a two-dimensional image domain, and belongs to the technical field of binocular stereoscopic vision underwater concrete three-dimensional reconstruction, and the method comprises the steps: obtaining an underwater video sequence, extracting a key frame, and constructing a two-dimensional time sequence motion model; based on the two-dimensional time sequence motion model, two-dimensional motion-texture joint denoising is adopted, and an optimized noise mask image is generated; based on the optimized noise mask image, establishing a disparity map by adopting a mask-guided stereo matching method, and constructing a three-dimensional point cloud according to the disparity map; and performing statistical filtering and voxel rasterization time sequence frequency screening on the three-dimensional point cloud to generate a pure underwater concrete three-dimensional point cloud. The method achieves the core target of'time sequence denoising + detail reservation ', has the advantages of being low in calculation cost, good in real-time performance and suitable for rapid reconstruction of massive underwater video data, solves the problem of resource waste caused by invalid calculation, and remarkably improves the real-time performance of the algorithm.

The application discloses a two-dimensional layout algorithm selection method and system based on machine learning, and the method comprises the following steps: constructing and training XGBoost model and full connection neural network model, and establishing a two-dimensional layout algorithm library; acquiring real-time layout data, extracting features and calculating characteristic values, inputting the XGBoost model to obtain the selection probability of each algorithm, and screening out the candidate algorithm sequence exceeding the preset probability threshold; sorting the candidate algorithm according to whether the time factor needs to be considered, calling the solution in sequence, determining the final algorithm if successful, and trying the subsequent algorithm in sequence if failed; if all the algorithms fail, inputting the characteristic values into the full connection neural network to generate the first n optimal algorithms, and constituting a new sequence to solve again. The application solves the problems that in the two-dimensional layout algorithm selection method depending on artificial experience or trial-and-error method, the artificial experience may lead to subjective bias, thereby affecting the accuracy and optimality of algorithm selection; and the trial-and-error method is easy to introduce a large amount of invalid calculation, thereby leading to the problem of low algorithm selection efficiency.

This invention belongs to the field of large-scale power language models and discloses a method and related apparatus for recommending test cases for large-scale power models. It constructs state data including attack success rate and recommendation latency, utilizes reinforcement learning pre-trained depth-determining models to adaptively select the current knowledge graph exploration depth, dynamically adjusts the knowledge graph propagation range based on historical recommendation results, and employs a relation-aware attention mechanism in recursive propagation to weighted aggregate neighbor tail entities. Entity features under different relations are projected onto the corresponding relation space for semantic matching. A bidirectional interactive aggregator is combined to fuse its own features with neighboring features through addition and multiplication, enhancing feature representation capabilities. A layered aggregation mechanism concatenates features from various depths into a fusion vector and sorts them by inner product to select test cases, enabling the recommendation results to incorporate hierarchical semantic information from multi-hop propagation. This achieves synergistic optimization of recommendation accuracy and response speed, effectively supporting rapid evaluation of the security performance of large-scale power models.

The invention discloses a heterogeneous SAR image high-precision connection point matching method. The method comprises the following steps: extracting object space connection points as region guidance according to object space SAR image data; determining an initial position and a guide area of an image space connection point based on an object-image conversion relation, searching a local optimal connection point, and extracting a supplementary feature point according to an exponential weighted mean ratio of an image texture structure; constructing SAR image feature descriptors according to a gradient statistical histogram and accurately matching the SAR image feature descriptors with image spaces; further eliminating wrong matching points through a similarity threshold value and a random sample consistency algorithm to obtain high-precision connection points; according to the invention, the problems in the prior art that the different-orbit SAR image connection point matching method has obvious defects in coping with the problems of image isomerism and object image conversion position deviation and is difficult to meet the application requirements of high-precision SAR images are solved.

The invention relates to the technical field of fatigue simulation, in particular to a fatigue optimization method based on multi-parameter fusion and related equipment. The method comprises the steps of obtaining fatigue analysis basic data; marking an area meeting a double-threshold standard in the fatigue analysis basic data to obtain a high-danger area; performing regional clustering on the nodes of the high-danger region through a spatial clustering algorithm to obtain geometric features of the high-danger region; calculating according to the fatigue analysis basic data and the geometrical characteristics of the high-danger area to obtain a stress gradient factor, life sensitivity and a force transfer path contribution degree; and determining the selection of a thickness optimization channel and a multi-measure optimization channel according to the product of the stress gradient factor and the life sensitivity and the activation threshold value, determining different fatigue optimization schemes according to different optimization channels, and integrating and outputting the different fatigue optimization schemes. According to the method, the optimization can be accurately activated, the problem of secondary stress concentration is solved, multi-target balance is considered, the efficiency of the optimization period is greatly improved, and the universality is high.

The application discloses a large-range wetland dynamic mapping method combining knowledge guidance and machine learning, comprising the following steps: step one, image acquisition and pretreatment; step two, time sequence training sample preparation and optimization; step three, wetland potential distribution estimation; step four, multi-dimensional space-time feature extraction; step five, machine learning classification; and step six, wetland space-time dynamic characteristic analysis. The application provides a large-range wetland dynamic mapping method combining knowledge guidance and machine learning. Compared with a traditional large-range wetland dynamic monitoring method, the method has the following technical advantages: 1. Training sample dependence is greatly reduced. The traditional machine learning needs to arrange a large number of uniformly distributed training samples in the whole research area, while the method needs to select samples only in the high-probability wetland area by means of wetland potential distribution range constraint sample collection, and the sample amount is reduced by more than 40% compared with similar research, and the classification accuracy can be maintained or even improved.

The embodiment of the invention relates to the technical field of industrial oil and gas well engineering, in particular to a borehole trajectory determining method, device and equipment, and the method comprises the steps that an intermediate point of a to-be-drilled well is initialized; based on the deflecting point data and the target point data of the to-be-drilled well, generating a candidate well track which connects the deflecting point and the target point and passes through the middle point; calculating a trajectory quality index of the candidate borehole trajectory; by taking maximization of the trajectory quality index as a target and taking the condition that the candidate well trajectory and the adjacent well trajectory of the to-be-drilled well meet a preset anti-collision condition as a constraint, generating a new intermediate point of the to-be-drilled well by using a nonlinear optimization algorithm; iteratively executing the steps of generating the candidate borehole trajectory, calculating the trajectory quality index and generating the new intermediate point until an optimization convergence condition is met; and determining the candidate well track meeting the optimization convergence condition as a target well track of the to-be-drilled well.