12results about How to "Evaluation science" patented technology

The invention discloses a method and system for detecting the internal quality of a polyethylene pipeline hot-melt welding joint, and belongs to the technical field of pipeline quality detection.The method comprises the following steps that before a tensile test is carried out, ultrasonic quality detection is carried out on a casual inspection joint of a polyethylene pipeline set to be detected; dynamically determining an initial tensile rate based on the material grade and the material attribute parameter of the to-be-tested polyethylene pipeline group, and executing a first tensile test at the initial tensile rate; iteratively and dynamically adjusting the tensile rate of the tensile test of the next casual inspection joint based on the tensile test result of the previous casual inspection joint until the tensile test of each casual inspection joint is completed; dynamically executing fracture quality detection based on the fracture position and the fracture characteristic parameter of each spot check joint to obtain a fracture quality detection result of each first joint; and executing internal quality comprehensive detection based on the ultrasonic quality detection result, the fracture quality detection result and the tensile test result of each first joint.

The application discloses a traffic network key facility location method based on reinforcement learning and cascade kinetics, and belongs to the technical field of intelligent traffic network, and solves the problem that the traditional method is not accurate in identifying key nodes and is easy to fall into local optimization. The method comprises the following steps: a weighted complex network is constructed based on a road network, intersections are taken as nodes, road sections are taken as edges, multi-dimensional characteristics such as traffic capacity, location and risk are fused, and the entropy weight method is used to objectively distribute node weights; a cascade kinetics model based on an improved coupled map lattice is established to simulate the dynamic propagation and amplification process of disturbance in the network; a residual network is taken as a state, node removal is taken as an action, and network efficiency loss is taken as a reward, a reinforcement learning model is trained, and a node failure strategy that makes the whole network efficiency decrease the most is learned end to end; and key node sets are selected in sequence according to Q values, and the key node sets are taken as facility preferential deployment positions. The application realizes precise location of global optimization, and significantly improves road network resilience.

This invention discloses a multi-scenario competitive analysis method for AI-powered intelligent marketing, belonging to the field of competitive analysis technology. The method includes: S1, collecting multi-source data from the entire AI-powered intelligent marketing process and preprocessing it to obtain a structured feature matrix X; S2, dividing the multiple scenarios of AI-powered intelligent marketing into 5 core scenarios and key indicators; S3, combining real-time scenario popularity and indicator importance, proposing a scenario-indicator dynamic weight calculation method to generate a scenario-indicator dynamic weight matrix W; S4, using a Transformer model, inputting the feature matrix X and the dynamic weight matrix W, and outputting three tasks; S5, based on the advantage scores output by the competitive advantage assessment task, constructing an advantage heatmap, and generating differentiated strategies. The multi-scenario competitive analysis method for AI-powered intelligent marketing provided by this invention achieves accurate adaptation to multiple scenarios, better supporting enterprise marketing decisions.

The application provides a method, system, device and medium for screening a region suitable for low-altitude logistics layout, relates to the fields of low-altitude economy and geographic information, and comprises the following steps: acquiring navigation electronic map data, DEM elevation data and administrative division data, calculating the average altitude of each township based on the DEM elevation data and the administrative division data of the whole country to generate a preliminary screening region; calculating the elevation characteristics and slope characteristics of each road in the preliminary screening region by using the DEM elevation data to form a road elevation-slope characteristic data set; calculating the road bypassing coefficient, the number of sharp bends and the convenient accessibility index in the preliminary screening region based on the road elevation-slope characteristic data set and the navigation electronic map data, and constructing a road traffic obstacle index set; and evaluating the road traffic obstacle index set by using the analytic hierarchy process, and screening a region suitable for low-altitude logistics layout according to the evaluation result.

This application relates to the field of soil and water conservation carbon sequestration technology, providing a method and apparatus for calculating carbon sequestration based on temporary measures. The method includes: obtaining soil erosion and soil organic carbon content in the production and construction project area; determining protective effectiveness parameters according to the type of temporary measures for the production and construction project; and determining the carbon sequestration amount of the temporary measures for the production and construction project based on soil erosion, soil organic carbon content, and protective effectiveness parameters. This application proposes a carbon sequestration calculation scheme for temporary protective measures during the construction period of production and construction projects, which can more comprehensively and scientifically assess the carbon sequestration benefits of production and construction projects. Furthermore, it can dynamically determine the corresponding protective effectiveness parameters according to different types of temporary measures, which fully considers the physical differences in sand reduction and erosion prevention mechanisms of various temporary measures, making this method universally applicable to temporary protection systems under various complex construction scenarios.

The present application relates to the technical field of coal mine roadway supporting, and provides a repeated impact test evaluation method for surrounding rock control effect of coal mine spraying supporting material, which comprises the following steps: determining a data characteristic vector according to repeated impact test data of surrounding rock of the spraying supporting material and surrounding rock of the non-spraying supporting material, inputting the data characteristic vector into a repeated impact test evaluation model, outputting a repeated impact test control effect probability distribution vector from the repeated impact test evaluation model, and determining a repeated impact test control effect grade according to the repeated impact test control effect probability distribution vector, so that scientific evaluation of long-term mechanical properties and protection effect of the surrounding rock of the spraying supporting material under the action of repeated dynamic and static combined load can be realized, the performance evolution law of the spraying material under the condition of cyclic impact can be accurately revealed, and reliable experimental basis and technical support can be provided for impact-resistant supporting design of deep high-impact risk roadway.

This invention discloses a method and apparatus for constructing an event prediction model for a multi-infrastructure system. The method involves collecting basic data from each infrastructure component within the system; simulating the basic data of each infrastructure component to obtain operational data; coupling the spatiotemporal graph networks constructed from the infrastructure components to establish a spatiotemporal graph network model; and performing transfer training on the spatiotemporal graph network model based on the operational data and real-time monitoring data to obtain the event prediction model. The event prediction model constructed using this method can scientifically and accurately assess and predict the response and evolution of the multi-infrastructure system during events, and assist in the response and handling of urban disaster events.

The application discloses a kind of to beat leaf redrying finished product sheet tobacco comprehensive quality characterization method, comprising:1 collection the leaf redrying quality index of the nth processing batch,2 to leaf redrying quality index sequence is pretreated,3 using KMO test and Bartlett sphericity test respectively to the applicability of standardized data verification,4 calculate the correlation coefficient matrix of all processing batch leaf redrying quality index,5 calculate the eigenvalue and unit eigenvector of correlation coefficient matrix,6 calculate cumulative variance contribution rate, determine the number of principal components and calculate principal component score,7 calculate the nth processing batch to beat leaf redrying sheet tobacco finished product comprehensive quality score.The application can quantitatively, objectively, accurately characterize the comprehensive quality of beat leaf redrying finished product sheet tobacco, so as to solve the deficiency that traditional evaluation index is single and relatively rough.

The embodiment of the invention provides a method and system for evaluating the influence degree of a target substance on gastric mucosa, and belongs to the technical field of bionic evaluation. The method comprises the following steps: determining a corresponding stomach environment in a bionic stomach to obtain a stomach model; wherein culture cells of gastric mucosa epithelial cells are added into the bionic stomach; after the target substance is placed in the bionic stomach, the stomach model is driven to start digestive movement based on the movement parameters; and after a predetermined period, collecting digestion result information in the stomach model, performing assignment of each evaluation index based on the digestion result information, and determining an evaluation result of the influence degree of the target substance on the gastric mucosa based on each evaluation index after assignment. According to the scheme, the defect that the action of movement force on cells is neglected in two-dimensional cell culture is overcome, the problems of ethical limitation and hysteresis of traditional animal experiments are solved, a more personalized and accurate evaluation means is provided, and the influence of substances on gastric mucosa can be evaluated more scientifically.

The application provides a bus side knife switch operation risk assessment method and device, and relates to the technical field of electric power engineering. The method comprises the following steps: if the knife switch in the power system is a bus side knife switch, the wiring type of the power system is obtained; then, according to the wiring type, the operation type corresponding to the wiring type is determined; then, according to the wiring type and the operation type, the simulation fault equipment of the power system is determined; finally, according to the simulation fault equipment, the power grid accident risk level of the power system is determined. Through the method, the accuracy of the risk assessment of the bus side knife switch operation can be improved.

The application discloses a chip visual data reasoning capability test method and electronic equipment, and relates to the technical field of chip testing. The method comprises the following steps: processing visual original data sets based on a data arrangement mechanism to obtain visual test data sets, solving the one-sidedness and limitations of single data types and single data formats on the calibration chip capability, and helping to scientifically and comprehensively evaluate the to-be-tested chip; testing the to-be-tested chip according to a preset test model set to obtain an output result set, solving the one-sidedness and limitations of a single test model on the calibration chip capability, and helping to scientifically and comprehensively evaluate the to-be-tested chip; and judging the effectiveness of the output result set according to a monitoring result set, thereby improving the accuracy of the visual test result, and enabling the visual test result to accurately represent the visual data reasoning capability of the to-be-tested chip.

The invention discloses a modeling method for a relationship between man-machine collaborative decision evaluation indexes. The method comprises the following steps: establishing a man-machine collaborative decision model; establishing a man-machine collaborative decision evaluation index system; carrying out a man-machine collaborative decision-making human factor experiment, and obtaining experiment data of each index; calculating the score of each man-machine collaborative decision evaluation index, and carrying out index correlation analysis to obtain a correlation coefficient between every two indexes; selecting strongly correlated man-machine collaborative decision evaluation indexes, and establishing a relation function among the evaluation indexes by using a multiple linear regression analysis method; and evaluating the accuracy of the relation function between the evaluation indexes by calculating an average absolute percentage error between a predicted value and an actual value of the relation function. According to the method, the quantitative relation between the man-machine collaborative decision evaluation indexes is determined, a complete man-machine collaborative decision evaluation index system is established and simplified, the quantitative evaluation problem of man-machine decision is effectively solved, and a quantitative standard is provided for improving the accuracy of man-machine decision.