6results about How to "Reduce the need for computing resources" patented technology

This invention relates to a physical information neural network-based intelligent performance prediction method and system for automated multi-material fiber placement on complex curved surfaces in aircraft. The invention includes: collecting fiber placement process parameters; performing standardized preprocessing and physical constraint-enhanced sampling to obtain an enhanced training dataset; constructing a high-order nonlinear sparse regression candidate library based on the enhanced training dataset; jointly identifying piecewise smooth physical differential equation systems and their mode switching logic using sparse Bayesian regression and Hidden Markov Models to obtain an embeddable inverse mechanism model; constructing a Physical Information Embedded Generative Adversarial Network (PI-GAN); collaboratively optimizing the generator and discriminator through adversarial training to output surface defect indices and mechanical performance indices; and initiating incremental self-learning when introducing new process scenarios to achieve model self-evolution. This invention achieves end-to-end accurate prediction of multi-dimensional quality indices such as surface defects and mechanical performance.

This invention discloses a method and system for identifying innovative points in academic papers, relating to the field of artificial intelligence technology. The method first processes the paper abstract through a concept path extraction module, including: structured semantic segmentation, concept pair extraction and verification, constraint relation triple generation, hierarchical verification, and path optimization, to construct a complete set of concept paths for the paper. Then, in a rare path discovery module, the popularity index of each concept path in the global path frequency dictionary is calculated and compared with a threshold to identify rare paths as the scientific innovative points of the paper. This invention effectively suppresses the illusion of language models through a knowledge graph constraint mechanism, significantly improving the accuracy of concept path extraction and its coverage of long-tail concepts, achieving accurate and efficient identification of innovative points in academic papers at the path level.

The application discloses a kind of multi-energy distribution network voltage control methods, comprising the following steps, define local voltage control rule;Analysis distributed power output causes voltage fluctuation upper and lower limit;Build global voltage control function;Algorithm is solved to objective function, the local voltage control rule is acquisition control point voltage u, determine whether to satisfy the following constraint, set the reactive power output of voltage compensation device.The multi-energy distribution network voltage control method, considering the uncertainty fluctuation of distributed power supply, improve the accuracy of voltage fluctuation analysis, formulate the localized voltage adjustment rule and global voltage optimization function, realize passive control and active control combination, reduce fluctuation rate, using interval number to express the uncertainty of distributed power supply, less computing resource demand, control reaction speed is fast.

The application discloses a multi-agent material calculation consistency calibration method, belonging to the cross field of material science, artificial intelligence and computational physics. The method adopts a master-slave structure multi-agent system, containing one master agent and at least three slave agents. The master agent is responsible for overall coordination, embedding physical mechanism constraints, consistency calibration and output results. The method steps are: constructing a calculation system, introducing physical mechanism constraints and embedding slave agent calculation models, collecting calculation data, performing bias analysis, adjusting parameters or correcting results through iterative calibration, and finally verifying and outputting the final results. The application introduces physical mechanism constraints, combines bias analysis and iterative calibration, and solves the problems of poor consistency of existing multi-agent material calculation results and easy violation of physical laws. Experiments show that the method reduces the deviation of the calculation results and the experimental measured values to below 3%, improves the calibration efficiency by more than 40%, and improves the calculation accuracy by more than 35% compared with the prior art, thereby improving the accuracy and engineering practicability of high-throughput calculation of material performance.

The present application relates to a kind of vehicle driving path processing method, device, electronic equipment and storage medium, the vehicle driving path processing method, obtain the planning path of the reference line indicating vehicle driving, extract the straight path in planning path, so as to divide the straight path based on preset length, obtain segmented path, the length of segmented path is less than or equal to preset length, adjust the distance between segmented path and the road boundary of vehicle driving road, obtain target planning path, the distance between the reference line indicated by target planning path and road boundary is greater than or equal to preset distance threshold value;Therefore, by dividing the straight path into segmented path, segmented path is handled, solve the problem that the high demand of computing resource and low processing precision exist in the length process of straight path, and the effect of reducing the demand of computing resource and improving processing precision is realized by processing segmented path.

This invention relates to the field of wind energy forecasting technology, and more particularly to a method, system, device, and storage medium for early warning of extreme offshore wind power events based on typhoon forecasting. The method includes acquiring real-time satellite cloud images; identifying and marking regions of typhoons in the satellite cloud images based on their morphological characteristics; obtaining the pixel coordinates of the centroid of these regions and converting them into actual latitude and longitude coordinates to obtain the typhoon's eye coordinates; acquiring infrared satellite cloud images; obtaining the maximum wind speed radius based on the typhoon's eye coordinates; and estimating the current maximum wind speed using a preset wind speed model; calculating the typhoon's short-term trajectory, future maximum wind speed, and maximum wind speed radius using a preset typhoon short-term dynamics integrated prediction model; and predicting the typhoon's impact on a designated location within a future timeframe using a preset typhoon physical model, and calculating the wind speed and direction at that location.