8results about How to "Improve capture accuracy" patented technology

This invention relates to the field of power distribution system resilience enhancement technology, specifically a method for enhancing the resilience of a mobile hydrogen energy storage power distribution system. This method includes data acquisition and parameter initialization; constructing physical constraints for the power-transportation coupled system based on a multi-microgrid reconfiguration strategy; expanding the original typhoon scenario using an enhancement strategy to generate an expanded sample set including wind and solar power output prediction errors; constructing a fuzzy uncertainty set covering multi-source uncertainties; establishing a sub-Bruker optimal scheduling model with the objective of minimizing the overall system operating cost; and performing dual transformation and linearization on the sub-Bruker optimal scheduling model to obtain the trajectory of the mobile hydrogen energy storage vehicle, charging and discharging commands, and the action sequences of distribution network segment switches and tie switches. This invention effectively solves the problems of high difficulty in multi-grid resource coordination and difficulty in accurately obtaining data distribution characteristics under extreme disasters, significantly improving the economic efficiency of post-disaster system recovery and achieving an effective balance between robustness and economy.

This application provides a software defect prediction method based on a dynamic path adaptive graph convolutional network. The method includes: constructing graph structure data of software modules; inputting the graph structure data into a graph convolutional network to learn the dependencies between modules; adaptively assigning weights to multi-hop paths through a dynamic path weighted convolutional layer and suppressing long path noise interference based on a path length decay coefficient; optimizing the adjacency matrix in real time based on a multi-head attention mechanism, enhancing key dependency edges and pruning redundant connections; embedding dynamic path scoring and an adaptive graph update algorithm into a classification objective function, updating training weights with a balancing strategy, and outputting defect prediction results through the optimized model. This application can effectively solve the performance degradation problems of traditional graph convolutional networks in scenarios with insufficient dependency modeling, noise accumulation, and class imbalance under the static graph assumption.

This application provides a multimodal zoned induction and precise trapping method based on airflow field reconstruction, relating to the field of pest control technology. The method includes constructing a peripheral light-odor composite attraction zone and pre-optimizing the odor concentration using AI; forming a circumferential swirling locking zone using an annular guide hood and monitoring the residence time in real time; increasing the fan speed to form an axial laminar flow trapping zone after target detection and using a trajectory prediction algorithm; periodically and intelligently executing reverse micro-blowing to break up the stacked structure of the sticky traps; dynamically adjusting the light-attracting and airflow modes according to environmental parameters and handling external interference. This application achieves high trapping accuracy and low energy consumption.

This invention discloses a method, apparatus, storage medium, and terminal for capturing facial expressions. The method includes: acquiring a face image to be recognized and extracting a target implicit code from the face image; inputting the face image to be recognized and the target implicit code into a pre-trained facial expression capture model, and outputting facial expression information corresponding to the face image to be recognized; wherein the facial expression information is generated based on facial expression features, and the facial expression features are generated by fusing multiple extracted features. Because this application extracts multiple features and fuses them into new features for model training, it can effectively improve the model's accuracy in capturing facial expression information.

This invention discloses a dynamic start-stop and pressure stabilization control method for water pumps based on operating condition identification, relating to the fields of mechatronics and automation control technology. The method includes the following steps: S1, outputting the predicted arrival time node of the reflected wave; S2, outputting operating condition attribute labels; S3, parsing the operating condition attribute labels; S4, inputting the dynamic fluctuation characteristics and graph topology space into an improved DCRNN model, introducing a bandgap filter based on acoustic impedance constraints and a resonant coupling diffusion mechanism to perform frequency domain filtering suppression and impedance matching coupling; S5, outputting a dynamic start-stop delay reference; S6, outputting the primary water hammer wave; S7, outputting the error compensation coefficient; S8, performing adaptive linkage correction on the dynamic start-stop delay reference and wave amplitude evolution reference. This invention overcomes the limitations of traditional methods, such as static threshold fixation, semantic simplicity, and neglect of spatiotemporal coupling topological constraints, providing an efficient solution for proactive defense against transient flow in fluid pipeline networks.

This invention discloses a method for constructing a vegetation drought index that integrates soil information and multi-source remote sensing data. The method includes: constructing an index dataset of multi-source remote sensing data for a given historical year, including a precipitation condition index dataset, a temperature condition index dataset, a vegetation condition index dataset, a water body index dataset, a temperature-vegetation drought index dataset, and a soil moisture drought index dataset; performing Z-score centering on the index dataset, and classifying pixels with Z-scores greater than a threshold as outliers, thereby removing outliers to obtain a preprocessed dataset; performing principal component analysis on the preprocessed dataset, extracting the first principal component as a comprehensive drought index, and filling the result with outliers from the original image to obtain a regional vegetation comprehensive drought index; and assessing the drought risk of a target area based on the regional vegetation comprehensive drought index. This invention improves the predictive ability and adaptability for drought occurrence.

This paper presents a method and system for correcting and predicting supersonic internal flow fields by integrating topology consistency evaluation and physical constraint latent space mapping, belonging to the interdisciplinary fields of fluid aerodynamics design and artificial intelligence. The method first employs a topology consistency evaluation based on a self-organizing mapping grid to realize the nonlinear coupling evolution of parameter sets and spatial errors under supersonic conditions in a hexagonal topological space. Gaussian smoothing and dot product operations are used to quantify the topology consistency between parameters and spatial errors, automatically selecting core parameters. Next, a physical constraint latent space mapping architecture is constructed, introducing a composite physical loss function to reduce the dimensionality of high-dimensional flow field features and establish a mapping model from core parameters to the latent space. Decoder weights are frozen to ensure the continuity of physical laws and derivatives. Finally, an error-driven correction mechanism is used to statistically analyze residuals and generate an error feedback matrix to complete the implicit core parameters, achieving closed-loop reconstruction and corrective prediction of the surrogate model. This method can significantly improve the physical fidelity of supersonic internal flow field reconstruction and effectively solve the problem of large prediction deviations in the flow field behind the gate.

This invention provides a method for evaluating the uniformity of the flow field in a wind tunnel test section, belonging to the field of wind tunnel construction technology. This invention acquires three-dimensional full-field instantaneous velocity data and wall shear stress distribution, and uses the Stoer-Wagner minimum cut algorithm based on the edge weight function of velocity gradient and turbulence intensity to divide the flow field into a high-uniformity core region and a low-uniformity boundary region. A transition prediction model based on the Monte Carlo method is established to quantify the random influence of wall roughness. The uniformity of the flow field is determined based on velocity uniformity indices, turbulence indices, and flow deflection angle indices, and the contraction section profile parameters and rectifying grid configuration parameters are iteratively optimized. This solves the technical problem of inaccurate flow field boundary identification caused by the lack of a three-dimensional full-field real-time measurement and numerical simulation collaborative verification mechanism in the evaluation of the flow field uniformity in wind tunnel test sections.