4results about How to "Avoid overestimation" patented technology

This invention provides a user incentive and points management method and system for carbon emission reduction behavior, relating to the field of carbon emission reduction behavior management technology. The method includes: acquiring the user's original trajectory information in the target travel behavior, and simultaneously collecting corresponding environmental feature data and equipment motion status data; performing segmentation processing; performing anomaly identification processing on each trajectory segment; performing segment consistency reconstruction processing on trajectory segments containing anomaly segment markers; performing travel mileage calculation processing to obtain the user's actual travel mileage in the target travel behavior, and generating corresponding carbon emission reduction data; performing points generation processing based on the carbon emission reduction data, converting the carbon emission reduction data into user points records; and mapping user points to a preset incentive resource pool to generate incentive resource availability data. This invention improves the autonomy and accuracy of carbon emission reduction behavior management.

The application provides a rice field evapotranspiration prediction method and device based on public weather forecast and crop coefficient method, and relates to the technical field of agricultural information processing. The method comprises the following steps: obtaining the public weather forecast information of a target area, calculating a reference crop evapotranspiration dynamic prediction value; constructing an average crop coefficient model coupled with a density coefficient and a plant growth temperature constraint, and calculating an average crop coefficient, wherein the density coefficient is calculated by a canopy coverage and a crop height based on a nonlinear regression model of cumulative heat time; and calculating an actual evapotranspiration based on the reference crop evapotranspiration dynamic prediction value and the average crop coefficient. The method can break through the technical bottleneck of precise evapotranspiration prediction under the condition of limited meteorological information, realize daily dynamic evapotranspiration estimation based on easily obtained data such as air temperature and weather type, provide a scientific basis for efficient use and intelligent decision of farmland water resources, and promote the intelligent transformation of agriculture and water conservancy.

The present application belongs to the technical field of computer aided engineering simulation, and relates to a kind of offshore floating photovoltaic support structure wind resistance stability simulation analysis method, comprising: according to the relative wind direction angle row determination shelter, determine effective wind area;With the height difference between pressure center and resistance center as independent force arm, combined with effective wind area, get each row independent wind inclination torque;Sum up the wind inclination torque of all support rows, photovoltaic equipment and floating body structure to get total wind inclination torque;With the deviation of initial inclination angle restoring torque and total wind inclination torque driving iteration, update the shelter interval boundary and pressure center height varying with inclination angle, execute shelter determination and calculation cyclically, until the deviation converges or the iteration number reaches the upper limit, and output the final inclination angle as the wind resistance stability equilibrium floating state.The present application fully considers the dynamic change of aerodynamic shelter caused by floating body inclination, realizes wind inclination and stability coupling iteration, truly reflects the equilibrium floating state, and improves the simulation accuracy.

The application provides a large model intelligent quality inspection method, device and equipment and medium, relating to the technical field of artificial intelligence, which comprises: performing a preprocessing operation on a multi-modal original data set formed by collecting voice data and text data around the same quality inspection object to generate structured conversation data, then performing rule matching processing, and forming a corresponding rule determination result when the rule is triggered. When the rule determination result is not formed, the structured conversation data is subjected to emotion state recognition and sensitive expression detection to output corresponding detection results and convert them into a structured semantic feature vector; the structured conversation data and the structured semantic feature vector are subjected to semantic analysis to output a semantic determination result, and the rule determination result and the detection result are combined to perform fusion decision processing and generate a quality inspection result through dynamic weighted calculation. The application can effectively fuse multi-source data and output stable and consistent quality inspection results, thereby improving the accuracy of quality inspection.