6results about How to "Small absolute error" patented technology

The invention discloses a breakable crop stalk discrete element simulation model construction method, which comprises the following steps: firstly, measuring the actual feature size of a crop stalk, and layering the internal structure of the crop stalk based on a microstructure; then performing an experiment to obtain intrinsic parameters and contact parameters of the stalks, constructing a multi-layer geometry three-dimensional model according to measurement characteristics, filling each layer of the geometry three-dimensional model with different types of particles, establishing an initial discrete element simulation model, introducing a contact model, and constructing an initial breakable discrete element simulation model; and finally, adjusting the mesoscopic parameters of the simulation model according to the actually measured data until the mesoscopic parameters are kept consistent. According to the method, the contact model is introduced, different structural layers are filled with particles with different material attributes, the biological characteristics and mechanical characteristics of multiple layers of real stalks from outside to inside are restored, and errors are smaller when mechanical behaviors are simulated.

The present invention discloses a method and system for quickly calculating flood depth based on multi-layer grid overlay analysis, and belongs to the technical field of flood risk analysis. The method includes constructing a meteorological grid, a catchment area grid, and a hydrodynamic model grid; using the intersection area between the meteorological grid and the catchment area grid as the allocation weight, and obtaining real-time rainfall data to calculate the rainfall allocated on the catchment area unit; using the overlay relationship between the catchment area grid and the hydrodynamic model grid and the rainfall allocated on the catchment area unit, the maximum flood depth of the hydrodynamic model grid unit is calculated. The present invention combines distributed databases and parallel computing technology, and proposes an interpolation method based on static-dynamic variable decoupling, which provides results that are relatively consistent with professional models in a short time; through the organic combination of overlay analysis, distributed databases, and parallel computing, not only the accurate calculation of complex data analysis and simulation is achieved, but also the ability to respond quickly is ensured.

The invention relates to a road alignment safety evaluation method based on three-dimensional point cloud spatial modeling, and aims to overcome the defects of poor adaptability of a road surface point cloud segmentation algorithm and strong dependency of vertical line fitting on a road marking in a complex scene by utilizing characteristics of obtained high-density point cloud data. The road key information collaborative extraction method comprises the following steps: firstly, reducing the influence of environmental noise on road surface features through a normalized gradient filtering algorithm and a statistical outlier filtering algorithm; secondly, constructing a joint clustering model and an interactive region growing algorithm considering elevation, normal vector and pavement material reflection heterogeneity, and realizing precise segmentation of pavement point cloud in a complex scene; and then extracting a road surface edge line, obtaining road center line data, and generating a safety evaluation result list based on road center line parameters of a road plane, a longitudinal section and a cross section line shape. The research results provide technical support for application scenes such as road maintenance detection and automatic driving high-precision map construction.

The invention belongs to the field of high-temperature superconducting, and particularly relates to an alternating-current loss measuring device and method for a large-diameter high-temperature superconducting coil by utilizing self-excitation compensation, and the device comprises a power supply loop and a measuring loop. The power supply loop comprises an alternating current power supply and a large-caliber high-temperature superconducting coil; the measuring loop comprises a compensating coil, a current sensor, a voltage lead and a signal collector; the AC power supply, the large-caliber high-temperature superconducting coil and the current sensor are connected in series; the current sensor is connected with the signal collector; the large-caliber high-temperature superconducting coil, the signal collector and the compensation coil are connected in series through a voltage lead; the compensation coil and the large-diameter high-temperature superconducting coil are arranged close to each other, so that the compensation coil and the large-diameter high-temperature superconducting coil are mutually coupled. Compared with the prior art, the method solves the problems that in the prior art, a conventional thermal measurement method and an indirect electrical measurement method need to be calibrated more complicatedly, and a direct electrical measurement method is high in requirement and large in implementation difficulty; the alternating current magnetization loss test with a simple scheme and relatively high flexibility and feasibility is realized.

This invention discloses a noise perception annoyance prediction method based on a convolutional recurrent neural network, comprising the following steps: Step 1) generating a preprocessed monophonic noise signal sample set; Step 2) generating a time-frequency image; Step 3) constructing a training sample set and a validation sample set; Step 4) training a deep neural network model using the training sample set to obtain a noise perception annoyance prediction model; Step 5) fitting a univariate linear relationship between the actual perceived annoyance and the original network prediction value using the validation sample set to obtain a linear correction function; Step 6) obtaining the noise perception annoyance prediction value; Step 7) correcting the noise perception annoyance prediction value using the linear correction function to obtain the final noise perception annoyance prediction structure. This invention maintains a low absolute error and an average relative error of approximately 1% to 2% even on high-perceived-annoyance noise samples, providing a stable and reliable objective indicator for noise assessment.

The invention discloses a rock reservoir average porosity estimation method, electronic equipment and a storage medium, and the method comprises the steps: obtaining the maximum effective porosity, the minimum effective porosity and the average porosity of a plurality of existing well target reservoirs around a research work area, calculating the maximum and minimum arithmetic average porosity of the maximum effective porosity and the minimum effective porosity of the target reservoir of each existing well; based on the average porosity of a plurality of existing well target reservoirs and the maximum and minimum arithmetic average porosity, fitting to obtain correlation coefficients in the corresponding function relation formula; and substituting the calculated maximum and minimum arithmetic average porosity of the maximum effective porosity and the minimum effective porosity of the target reservoir in the research work area into the corresponding function relation formula, and calculating the average porosity of the target reservoir in the research work area. According to the method, the porosity of the target reservoir in the research work area can be accurately estimated under the condition that only the maximum effective porosity and the minimum effective porosity in the rock reservoir sample in the research work area exist.