8results about How to "Avoid invalid calculations" patented technology

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.

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.

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 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 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.

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.