8results about How to "Fast traverse" patented technology

The invention discloses a commercial subject risk assessment method and system based on machine learning, and belongs to the technical field of knowledge maps. Basic features of an enterprise are obtained, a knowledge graph is constructed, and risk features are identified through graph mining; carrying out qualitative analysis and quantitative analysis on the enterprise to obtain a feature tag description; constructing a sample set, setting a misjudgment cost and a class weight based on the sample set, performing parameter tuning and verification set feedback, adjusting a decision threshold, performing binning on each feature, and obtaining a final risk score; and threshold selection and probability calibration are carried out to obtain risk grade division and decision suggestions of the enterprise, and risk label interpretation and large model auxiliary interpretation are carried out. The problems that manual collection and analysis of supervision policy documents consumes time and labor, careless omissions easily occur, and final risk judgment is prone to misalignment, misjudgment and frequent missed judgment are solved. According to the method, key rules can be accurately extracted, and hidden risk conduction links and potential risk points can be mined.

The invention relates to a terrain rendering method and device, computer equipment, a readable storage medium and a program product. To-be-processed terrain data is partitioned by adopting a quadtree algorithm to obtain multiple pieces of multi-level terrain block data so as to realize quick traversal of terrain blocks; and determining to-be-rendered terrain block data from the multiple pieces of multi-level terrain block data based on a preset display condition, if the distance between the to-be-rendered terrain block data and the target is smaller than or equal to a preset distance threshold value, constructing a rendering grid according to the to-be-rendered terrain block data, and according to the position relationship between the rendering grid and the target pressure plane, rendering the target pressure plane according to the rendering grid. And determining a target vertex height of the rendered grid, and performing rendering processing according to the target vertex height of the rendered grid to obtain a rendered terrain. According to the method, the flattening processing mode is determined through the preset distance threshold value, and finally the processed data is rendered, so that real-time efficient flattening rendering of mass topographic data can be supported, and the flattening edge has no sawteeth and can be accurately matched with a model.

The invention relates to the field of computer document conversion and provides a method for converting an XML Schema document into an SCORM document in order to solve the problems that an existing XML conversion method is large in manual interaction amount and algorithm calculation amount and often not ideal in division result, and the method comprises the steps that 1, a temporary directory and subdirectories of the temporary directory under an SCORM data packet directory are emptied; 2, clearing a directory where the XML data packet is located and a subdirectory of the XML data packet after the XML data packet is decompressed; step 3, decompressing the XML data packet; step 4, obtaining a plurality of data source packets after the source data packet is decompressed, and storing the data source packets into Listt; the method comprises the following steps of: carrying out extraction and purification on Pu < {EN0} > Modulet; middle; 5, traversing the source data packet in the List to obtain a current source data packet; 6, analyzing the xml file in the source data packet, extracting data from the XML file, and constructing a data structure; constructing directory structure information according to an analysis result; and step 7, packaging the data packet, and publishing the data packet as an SCORM data packet. According to the method, a plurality of xml files are analyzed by using an open source framework VTD-XML, and rapid analysis, traversal and the like are also provided.

This application discloses a method for designing high thermal conductivity aluminum-silicon alloys based on machine learning models, relating to the field of metallurgical materials technology. The method includes: constructing an original dataset of aluminum-silicon alloys containing alloy composition, process parameters, and thermal conductivity properties; preprocessing and feature filtering the dataset to obtain key features affecting thermal conductivity; training several machine learning models based on these key features and using the coefficient of determination as a preliminary screening indicator; further screening using model performance indicators; constructing a final thermal conductivity prediction model through model fusion technology; finally, predicting the thermal conductivity of the virtual alloy composition, selecting high thermal conductivity alloy formulations based on the prediction results, and conducting experimental verification. This application solves the problems of traditional alloy design relying on trial and error, long development cycles, and insufficient prediction accuracy, achieving efficient and accurate prediction of the thermal conductivity of aluminum-silicon alloys, and providing an effective means for the intelligent design and development of high-performance thermally conductive materials.

The invention discloses a scheduling naming adaptive configuration method and system based on a design model. The method comprises the steps that information in a physical loop description model and information in a logic loop description model are analyzed and extracted; generating a signal corresponding relation in the physical loop description model and the logic loop description model by utilizing the extracted information; updating the logic loop description model to the latest version by utilizing the extracted information and the signal corresponding relation; comparing the logic loop description model of the latest version with an original logic loop description model, and generating a logic loop description model description updating report; descriptions of intervals, devices and signals in automation systems and equipment are automatically updated according to the description update report. According to the method, interval description, device description and signal description can be quickly changed, adaptive configuration of scheduling naming is carried out, the workload of manually modifying the scheduling naming of an automatic system and equipment is reduced, and the efficiency of engineering configuration is improved.

A multi-agent context sharing method, system, and medium are disclosed, comprising: parsing the context content output by a first agent to generate corresponding metadata; associating the context content with the corresponding metadata and storing it in a distributed cache; establishing a topic set indexed by a session identifier in the distributed cache and adding the topic identifiers to the topic set; responding to a task to be executed by a second agent, obtaining the topic set corresponding to the current session identifier, reading the topic descriptions corresponding to each topic identifier in the topic set, and generating a list of topic descriptions; inputting the task to be executed and the corresponding list of topic descriptions into a large language model, receiving the topic identifier set returned by the large language model as the target topic identifiers semantically related to the task to be executed; and reading the corresponding context content from the distributed cache according to the target topic identifiers, associating the context content with the task to be executed, and inputting it into the second agent.

The present application discloses a business data processing method, device, equipment and storage medium, the method comprising: obtaining business data from an original server; storing data in the business data that meets business conditions in a new server according to a combination of business attribute hash and data component hash; obtaining the stored data from the new server by a multi-shard concurrent traversal method; and sending the stored data to a user account corresponding to the stored data when the acquired stored data meets the sending requirements. The business data can be hashed and stored by a hash combination routing method to avoid hash collisions of the data, and the stored data can be traversed by a multi-shard concurrent traversal method to quickly traverse data with the same business attributes, thereby improving traversal performance.

The application discloses a network element detection method of IPv6 network space, comprising the following steps: obtaining a list of network elements to be detected, the list of network elements to be detected recording a plurality of first network elements to be detected; performing detection on each first network element to obtain a second network element directly connected with the first network element; judging whether the second network element is an anonymous network element, if yes, using a preset probe program to find an IPv6 global unicast address of the anonymous network element based on a seed node in a preset seed set to determine network element information of the anonymous network element; repeatedly performing detection until the detection of each first network element in the list of network elements to be detected is completed; and forming a network topology of the IPv6 network space based on the network element information of each second network element. The method disclosed by the application can quickly traverse all network element devices in a sparse IPv6 network space, and quickly form a network element use condition under the IPv6 network space according to the formed table.