13results about How to "Implement features" patented technology

This application discloses a method and apparatus for constructing a multi-scale adaptive gating MambaPlus network, belonging to the field of artificial intelligence and machine learning technology. The method includes: initializing the network configuration and constructing the basic structure; preprocessing the input data to generate a standard dataset; mapping the input data to the hidden space via an input mapping layer, and extracting backbone features from the Mamba backbone; constructing at least two parallel scale branches in the hidden space to obtain a multi-scale feature set; inputting the backbone features and multi-scale features into an adaptive gating module, dynamically allocating weights and adaptively fusing them through a hierarchical gating mechanism to generate fused features; further enhancing the features through cross-scale attention and feedforward enhancement, and then superimposing the residuals to generate the final discriminative features; finally, completing category prediction and model training evaluation. This application, while retaining the advantages of Mamba's long-range dependency modeling, addresses the problems of insufficient utilization of multi-scale information, poor adaptive feature fusion, and low robustness in complex scenarios.

The application discloses a smart community police management system and method based on Internet of Things security, and belongs to the technical field of smart communities, and solves the problem that existing system data processing cannot utilize edge computing nodes for low-delay real-time analysis, and cannot meet timely early warning requirements, the method comprising preprocessing of multi-source heterogeneous community monitoring information, analysis and processing of the community monitoring information based on edge computing, and generation of a risk propagation path in combination with front-end analysis results and heterogeneity characteristics; in the application, analysis and processing of the community monitoring information based on edge computing avoids the delay of centralized processing, can quickly trigger early warning in the early stage of a risk event, thereby gaining golden disposal time for risk event disposal, and a risk analysis model realizes a leap from single-node anomaly detection to composite risk quantification through multi-dimensional feature fusion and dynamic space-time reasoning, and realizes multi-dimensional feature fusion and dynamic reasoning capability of the risk event.

The invention provides a wind turbine generator model fault ride-through structured modeling method, which comprises the following steps: (1) selecting a wind turbine generator, carrying out high-low ride-through test on the wind turbine generator, and analyzing transient response characteristics of different wind turbine generators; (2) obtaining fault ride-through response characteristics of the wind turbine generator; (3) detecting the grid-connected point voltage of the wind turbine generator, and judging and selecting a high-low crossing mode; (4) dividing the whole process of the fault period of the wind turbine generator, and carrying out fault switching logic setting; (5) constructing a control instruction of the wind turbine generator; (6) constructing an active and reactive power control instruction during the fault period; (7) performing parameter identification on the physical parameters of the wind turbine generator and the parameters of the stator and rotor controller to obtain a complete model; and (8) comparing the obtained model with a manufacturer packaging model, and checking the consistency of the model and the manufacturer packaging model. According to the method, on the basis of a large number of actual wind turbine generator set actual measurement curves and fault time segment modeling, fitting and response characteristic analysis of response characteristics of different actual wind turbine generator sets can be achieved.

The application relates to the technical field of intelligent water monitoring, and discloses a flow measurement data verification method based on abnormal water use analysis, which comprises the following steps: deploying an intelligent sensor network comprising a flow meter, a pressure gauge and a thermometer, collecting multi-source data of abnormal water flow state and performing phase-amplitude decoupling processing to generate a feature matrix containing flow state correlation information; establishing a multi-layer probability field model, converting error components into measurement error probability clouds, constructing an error back propagation path and designing cascade compensation parameters; correcting the probability clouds by using a gradient optimization algorithm, combining deep learning technology to enhance the probability convergence field and determining a standard flow value; tracking and analyzing the error propagation link and the attenuation coefficient spectrum to establish an error convergence boundary and output a flow correction result; and finally combining environmental state detection to construct an abnormal verification feature spectrum, completing comprehensive verification of the flow measurement data, effectively improving the detection accuracy of the abnormal water flow state, and improving the accuracy and reliability of flow measurement.

The present application relates to the technical field of virtual clothing recommendation, and specifically discloses a virtual clothing fitting recommendation method and system based on artificial intelligence, which establishes a cross-domain feature decoupling and alignment mechanism by fusing commodity standard images and user real-shot images, realizes the extraction and unified representation of the essential visual attributes of clothing, and fundamentally solves the problem of inconsistent clothing appearance caused by differences in shooting conditions. By constructing an environment-independent feature model and a domain-invariant feature space, the system can accurately measure the visual similarity of clothing in images from different sources, significantly improving the reliability and user trust of the recommendation results. The system realizes precise matching of the recommendation results and high-fidelity presentation of the virtual fitting effect, can accurately capture the fitting effect of clothing and individual form before the user makes a purchase decision, and realizes early identification and visual satisfaction of personalized needs.

This application discloses a damage detection method, electronic device, storage medium, and computer program product, relating to the field of nondestructive testing technology. The method includes: scanning a composite material to be tested using a terahertz time-domain spectroscopy system to obtain the original time-domain echo signal of the composite material, wherein the composite material to be tested is a glass fiber reinforced polymer composite material; preprocessing the original time-domain echo signal to obtain target image data; extracting features from the target image data to obtain damage features; predicting the geometric offset of the damage features; and locating the damage target in the composite material to be tested based on the geometric offset and the damage features. This application solves the technical problem of poor detection effect in existing nondestructive testing technologies.

The application discloses a full-mouth tooth crown automatic segmentation method based on gum line identification and region growth, relates to the field of dental digital restoration, and comprises the following steps: pre-processing a tooth model obtained by mouth scanning to obtain an initial mesh model; identifying a gum line based on the initial mesh model to obtain gum line region mesh nodes; segmenting a gum and a tooth crown region based on the gum line region mesh nodes to obtain a tooth crown region mesh model; and segmenting the tooth crown region mesh model to obtain mesh models of individual tooth crowns. The application provides the full-mouth tooth crown automatic segmentation method based on the gum line identification and the region growth, so as to solve the problems of inaccurate gum line identification, poor region growth segmentation effect and poor full-mouth adaptability in the prior art, realize accurate extraction and feature reservation of the full-mouth tooth crown, and provide reliable support for automation and standardization of digital oral restoration.

The present application relates to the technical field of multi-task learning, and provides a multi-task model fine-tuning method and device, electronic equipment and storage medium, the method comprising: generating modulation coefficients of each task by using the encoding features of each task, and modulating the corresponding hidden layer features by using the modulation coefficients of each task to obtain modulation features of each task; calculating routing weights of each task based on the modulation features of each task, and determining the corresponding target expert module from multiple routing expert modules of the multi-task model according to the routing weights of each task; aggregating the output of the shared expert module in the multi-task model and the output of the target expert module of each task to obtain the prediction results of each task, and fine-tuning the parameters of the multi-task model based on the prediction results of each task. The present application introduces an explicit task semantic guidance and feature modulation mechanism, thereby effectively solving the problem of expert allocation error caused by the lack of macro task perception of the router in the traditional method.

The application discloses an intelligent temperature control method and system for an injection molding machine, which collects temperature values of a melt conveying section, a solid melting section and a solid conveying section of a material bucket of the injection molding machine, sets temperature target values of the three sections, predicts actual control values of the temperatures of the sections and a temperature target value of the whole material bucket of the injection molding machine and a temperature prediction value of the whole material bucket of the injection molding machine according to the temperature target values of the sections and temperature values collected by all the three thermocouples, outputs ideal control amounts of the temperatures of the sections of the material bucket of the injection molding machine and a temperature control amount of the whole material bucket of the injection molding machine after a temperature controller, and obtains temperature control amounts of the sections by fusing the two, acquires real-time compensation control amounts of the temperatures of the sections, and realizes decoupling compensation control on the temperature of the material bucket of the injection molding machine by combining the temperature control amounts of the sections and the real-time compensation control amounts of the temperatures. Compared with the prior art, the application can improve the accuracy, rapidity, robustness and comprehensiveness of temperature regulation of the injection molding machine.

The application discloses a system for realizing InSAR deformation time series analysis and fault creep event detection, and relates to the technical field of geophysical monitoring.The system comprises a comprehensive monitoring platform, and the comprehensive monitoring platform is in communication connection with the following modules: a time series noise filtering module, which is used for extracting a creep deformation signal related to a fault sliding mechanism from original InSAR deformation data of a target detection area by adopting a space-time adaptive filtering algorithm in combination with wavelet transform and independent component analysis, filtering out the interference of seasonal hydrology, thermal expansion and non-tectonic noise, and obtaining a filtered time series component sequence.The application can effectively separate and inhibit seasonal hydrology, thermal elastic deformation and other non-tectonic noise by adopting the combination of wavelet transform and independent component analysis, retain time series components highly related to fault creep activities, and significantly improve the extraction precision of tectonic signals in InSAR deformation data.

This invention relates to an AI-powered smart home security control system, belonging to the field of smart home security control. It utilizes an environmental perception module to collect multi-dimensional sensor data and generate an environmental state vector; a behavior modeling module to integrate historical user command data to construct a joint environment-behavior feature space; a self-evolving learning module to use an incremental autoencoder combined with time-aware location embedding to perform online learning and trend prediction of real-time behavior flows; a path modeling module to perform online statistical analysis of network path chains to generate dynamic path templates; and a risk prediction and control module to calculate a weighted risk index based on the degree of behavior deviation, path deviation, and environmental anomaly. Based on the risk index, a tiered security control strategy is executed, and the behavior model dynamically evolves through a model self-updating trigger. This invention achieves a shift from static matching to dynamic evolution, from post-event identification to pre-event prediction, improving anomaly detection accuracy and enhancing the intelligence and adaptability of smart home security control.

This invention provides a multi-source collaborative emergency power supply scheduling optimization method for coal mines based on supercapacitors, belonging to the field of coal mine safe power supply technology. The method includes acquiring real-time operating parameters of the power supply system to construct a node state feature matrix, decomposing and extracting dynamic features to construct a node priority system, generating power supply path scores and performing global optimization, determining equipment switching strategies and synchronous switching methods, and establishing a supercapacitor transitional power supply mechanism. This invention achieves rapid and reliable switching of coal mine power supply systems, ensures power supply continuity, and improves emergency response capabilities.