6results about How to "Improve analytical performance" patented technology

The invention discloses a multi-dimensional training method and device for a support vector machine, electronic equipment and a computer readable storage medium, and the method comprises the steps: carrying out the discretization of a training sample data set, and obtaining a discretized data set, the discretized data set comprises a plurality of different attributes, and each attribute corresponds to a plurality of feature vectors; calculating a classification contribution parameter of each attribute feature vector to obtain a plurality of classification contribution parameters; performing data mapping on the plurality of classification contribution degrees by using a kernel function to obtain a target function; and optimizing and training the objective function by using a gradient descent algorithm to obtain a support vector machine model. According to the method, different dimension data are mapped through the kernel function, the data gain weight can be determined, the linear separable effect of the mapped dimension data can be improved, and then the classification and analysis capability of the SVM can be improved.

The application provides a self-evolving intelligent fund analysis method, relates to the field of data processing, and comprises the following steps: receiving a natural language analysis instruction, combining a large language model decomposition task, extracting account fund flow characteristics and matching with historical cases, and generating a weighted execution instruction; identifying a transfer path based on a fund correlation graph, extracting a priority path subgraph structure according to a user identifier, and forming a directional analysis model; performing node risk scoring on the fund correlation graph, outputting a risk account identifier and an analysis report, and realizing intelligent and accurate fund risk identification.

This invention discloses a method for measuring Rydberg atoms using micro-Doppler agility under a polarization-multiplexed microwave field, belonging to the field of quantum precision measurement technology. The method includes generating a dynamic coded sequence and an interleaved coded microwave field by aperiodically pairing and jumping the microwave polarization state with the carrier frequency; acquiring the target echo signal and applying it to the Rydberg atom ensemble with a reference microwave field to generate a quantum coherent state; applying a synchronous laser pulse to acquire a time-series optical response signal; obtaining the signal's fundamental frequency, envelope spectrum, and initial phase component through time-frequency transformation and feature separation; and performing parameter mapping and synthesis to generate three-dimensional micro-motion parameters. This invention uses an aperiodically agile polarization-frequency-multiplexed microwave field for active target detection and utilizes the Rydberg atom ensemble for quantum coherent detection and optical readout of the echo signal, enabling high-sensitivity, high-precision, and high-anti-interference measurement of the target's three-dimensional micro-motion parameters.

This invention belongs to the field of radiative heat transfer technology, specifically relating to a method for obtaining the radiation characteristics of divergent suppressed particles. The calculation results of the absorption factor and scattering factor obtained by this method are in good agreement with those obtained by traditional Mie scattering calculations. When the shape factor increases to the point that traditional Mie scattering calculations diverge, the proposed divergent suppressed particle radiation calculation method does not diverge, effectively solving the divergence problem that occurs in traditional Mie scattering calculations when the shape factor increases. By introducing the divergent suppressed Riccati-Bessel formula and stepwise recursive calculations, the stable calculation of the absorption factor Qa and scattering factor Qs is ensured, avoiding divergence and thus improving the reliability and accuracy of particle radiation characteristic calculations.

The application provides a control block method and system of a UI interface, comprising: obtaining geometric information of each control to construct a control information sequence; calculating geometric characteristics of any two controls; based on a Gaussian distribution model, calculating similarity probability of the controls in each geometric characteristic according to the geometric characteristics, and fusing to obtain block probability between the two controls; taking each control in the control information sequence as a node, and taking the block probability between the two controls as the weight of the directed edge to construct a weighted directed graph; determining a classification threshold based on control block information of a historical UI interface, converting the weighted directed graph into a weighted undirected graph according to a preset selection mode and the classification threshold; analyzing the weighted undirected graph through a graph connected component algorithm, extracting each connected component as a block, and obtaining block information of the UI interface, so that the method realizes intelligent conversion from a UI design draft to structured block information, and improves page performance and response efficiency.

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.