4results about How to "Loss mitigation" patented technology

The application belongs to the technical field of target detection, and discloses a UAV image target detection method based on an improved RT_DETR model, which introduces an FAPPA module in a backbone network, effectively alleviating the information loss problem of small target features in a deep network. The method also replaces the feedforward neural network of the AIFI module in the encoder with an EDFFN module, which selectively enhances high-frequency features such as edges and textures by using a patch_wise FFT strategy and learnable frequency domain weights. In addition, the method also uses a Zoom_cat module to realize adaptive alignment of multi-scale features, and uses the convolution_attention dual-path architecture of the CAFMFusion module to fuse local details and global semantics, thereby fully utilizing complementary information at different levels. The method can significantly improve the UAV image target detection capability and also identify small target features in a complex background.

The invention discloses a wake detection model construction method based on frequency domain multi-scale perception, which relates to the technical field of ocean observation, is used for capturing weak wake features to carry out sea surface internal wave wake detection, and comprises the steps of constructing a wake image data set, constructing a wake detection model by taking an RT-DETR model as a baseline model, and constructing a multi-scale texture information selection network. A backbone network of the baseline model is replaced, a frequency domain multi-scale attention perception module is constructed, an AIFI module of the baseline model is replaced, a golden cudgel convolution down-sampling module is adopted to replace a standard convolution down-sampling module of the baseline model, training and optimization are performed on the wake detection model based on the wake image data set, and a target detection result is obtained. According to the method, the wake detection model AUVRT-DETR is constructed, the detection precision is improved while the advantage of light weight is kept, the optimal balance is achieved between the detection precision and the calculation efficiency, and the model parameter quantity and the calculation overhead are remarkably reduced while the highest detection precision is achieved.

This invention discloses an optimized scheduling method for a multi-source reservoir-canal system in an irrigation district based on the effective gravity-flow water level at the end of the canal. First, parameters of the irrigation district's reservoir group and main canal system are obtained, and the minimum effective water level required for gravity flow at the end of each canal is determined. The minimum water supply flow limit and pre-storage threshold are derived to form a baseline constraint. The pre-storage period and water supply period are divided, and a gravity-flow discriminant function is established. A mixed-integer linear programming model is constructed to solve the macroscopic discharge and water distribution process. This model is used as the upstream boundary of a one-dimensional unsteady flow model, and the hydraulic response is simulated using the Saint-Venant equations to calculate the net effective water supply. The deviation between this deviation and the target water demand is calculated, with the maximum deviation less than the tolerance used as the convergence criterion; otherwise, iterative optimization is performed after correction using a damping learning rate. This invention couples macroscopic scheduling with microscopic simulation, dynamically embedding the gravity-flow water level at the end of the canal into the model for optimization, alleviating ineffective water supply and tailwater loss, improving water resource utilization efficiency, and enhancing the feasibility of the solution.

This invention discloses a method and apparatus for constructing a microdroplet self-Fenton system. The construction method includes the following steps: mixing an iron salt with an acidic solution, and subjecting the resulting mixed solution to ultrasonic atomization to form micron-sized droplets, thereby obtaining the microdroplet self-Fenton system. The construction apparatus includes an atomizing reactor for storing the mixed solution and an ultrasonic generator for providing ultrasonic waves. The microdroplet self-Fenton system constructed by this invention has the following advantages: good adaptability, enabling the acquisition of a self-Fenton system under conditions of no light, no catalyst, and no sacrificial agent; it helps to increase the generation rate and yield of ·OH in the system, giving the system stronger redox capabilities and enabling efficient degradation of organic pollutants, providing important guidance for promoting the effective treatment of organic pollutant wastewater; the process is simple, easy to operate, low in cost, environmentally friendly, suitable for industrial applications, and facilitates the effective treatment of organic pollutant wastewater.