7results about How to "Highly systematic" patented technology

The application discloses an automatic driving scene generation method and device and a vehicle, and relates to the technical field of automatic driving scene generation, and in particular to a method for generating a scene by using a world model, a long-tail safe scene, risk attribution analysis, counterfactual reasoning, and multi-objective comprehensive scoring and iterative re-determination screening.

This application provides a geological disaster safety risk assessment method based on rainfall, landslides, and transmission tower deformation, relating to the field of geological disaster prediction. The method includes: collecting multi-source data in the slope area where the transmission tower is located; constructing a rainfall-induced soil moisture content response model and dynamically correcting the soil shear strength parameters; calculating the landslide stability safety factor based on the corrected soil shear strength parameters; constructing a comprehensive deformation index for the transmission tower; obtaining a rainfall risk index; and combining the landslide stability safety factor and the comprehensive deformation index of the transmission tower to construct a comprehensive risk assessment model, outputting the risk level and early warning signal. This application constructs a dynamically coupled risk assessment model of the three elements of "rainfall-slope-tower," realizing a comprehensive analysis from meteorological disaster to structural response.

This invention provides a method for digital modeling and visualization of plant transpiration processes, comprising: firstly, setting corresponding data acquisition nodes in each plant zone to collect air humidity, transpiration water volume, and root zone soil pressure values, and generating a transpiration monitoring data sequence; then, calculating the transpiration rate and percentage change in transpiration based on the transpiration monitoring data sequence to construct a dynamic parameter set for transpiration; further, constructing a digital model of plant transpiration based on the dynamic parameter set for transpiration, and optimizing the model weight parameters using reinforcement learning to generate a predicted value for transpiration intensity; subsequently, generating a sequence of transpiration image frames based on the predicted value for transpiration intensity to achieve dynamic visualization of the transpiration process; finally, synchronizing the transpiration image frame sequences of different plant zones in time, calculating the difference in transpiration intensity, and generating a comparative visualization demonstration result of the plant transpiration process.

This application provides a method and system for enterprise risk assessment based on a large language model and text quantitative analysis. The method includes: acquiring and parsing the current first annual report text of a target enterprise to obtain several subheadings and corresponding subtexts; dividing the subtexts corresponding to each subheading into corresponding semantic chapters using a preset large language model, thereby generating corresponding first reconstructed texts; extracting corresponding first target texts from the first reconstructed texts according to preset target semantic chapters; performing a difference comparison analysis on the first target text and the second target text using the large language model to obtain several difference texts and corresponding several change trends; calculating several analysis indicators based on the number of each difference text, each change trend, and the average number of words in each chapter, and conducting a risk assessment of the target enterprise based on each analysis indicator to generate a risk assessment result, thereby improving the effectiveness and accuracy of the risk assessment.

This application discloses a learning plan updating method and apparatus based on an AI intelligent agent, relating to the field of educational technology. The method includes: responding to acquiring learning behavior data of a student learning questions based on a learning plan in a peer learning system; determining the question information and note information of the student's target questions based on the learning behavior data; determining the set of implicit knowledge points in the knowledge point set corresponding to the question information and note information based on a first set of knowledge points marked for the target questions; determining the target implicit knowledge point set corresponding to the learning plan from the implicit knowledge point set based on the prerequisite and relevance information between the implicit knowledge point set and the first knowledge point set; and updating the target implicit knowledge point set in the knowledge point learning grid corresponding to the learning plan to update the learning plan to a target learning plan including the target implicit knowledge point set. This application can improve learning efficiency and the systematic nature of knowledge construction.

This invention discloses a carbon-plastic bipolar plate for a zinc-bromine flow battery, its preparation method, and its application, belonging to the field of electrochemical energy storage technology. The method includes: dispersing nitrogen-doped hollow carbon nanotubes and spraying them onto the positive electrode side of a carbon-plastic bipolar plate; after drying, a nitrogen-doped hollow carbon nanotube-modified positive electrode carbon-plastic bipolar plate is obtained; dispersing boron-nitrogen co-doped carbon and spraying it onto the negative electrode side of a pretreated carbon-plastic bipolar plate, after drying again, a boron-nitrogen co-doped carbon-plastic negative electrode carbon-plastic bipolar plate is obtained. On the positive electrode side, the nitrogen-doped hollow carbon nanotubes catalyze the bromine reaction through nitrogen doping, reducing the overpotential; the hollow structure adsorbs bromine species and uses charge action to inhibit bromine permeation, reducing self-discharge. On the negative electrode side, the boron-nitrogen co-doped carbon uses B-N zinc-loving sites to guide uniform and dense zinc deposition, inhibiting dendrite formation; and inhibits hydrogen evolution through charge regulation. Both methods synergistically improve the bromine barrier performance, reaction kinetics, and dendrite suppression ability of the carbon-plastic bipolar plate.

The application discloses a partial discharge diagnosis method based on regional clustering, which firstly extracts pulse repetitive discharge spectrum data and corresponding labels in a partial discharge training set and stores the data as a mapping matrix. Through a primary clustering function, corresponding selected region coordinate matrices are obtained. The selected region coordinate matrices are classified according to the labels, and the result is stored in a clustering data dictionary. The labels and the selected region coordinate matrices in the clustering data dictionary are iterated, and are sent into a secondary clustering function to obtain final diagnosis region coordinate matrices. Whether the collected PRPD spectrum data to be diagnosed is faulty is judged in combination with a discharge frequency threshold, a corresponding fault occurrence probability is calculated, and finally a partial discharge fault diagnosis result containing the fault occurrence probability is generated.