14results about How to "Improve statistical accuracy" patented technology

The invention belongs to but not limited to the technical field of animal husbandry statistics, and particularly relates to an alpine meadow yak number calculation method and system based on an unmanned aerial vehicle image, and the method comprises the steps: S1, employing an unmanned aerial vehicle to shoot an orthoimage of a sample plot, and carrying out the statistics of the yak number; s2, splicing the shot images by using Pix4D software, screening a proper sample plot, and respectively counting the quantity of wet cow dung and the quantity of dry cow dung in a visual interpretation mode; and S3, carrying out linear fitting on the obtained data by using Origin 2024b, so as to obtain three relation curves. According to the method for estimating the number of the yaks through statistics of the number of the cow dung in the unmanned aerial vehicle image, the workload of data collection is greatly reduced, and the limitation that the number of the yaks cannot be obtained when the yaks are not grazed in the grassland is avoided. According to the invention, the data acquisition frequency of experimenters is effectively reduced, and the research cost is reduced.

The invention discloses an intelligent ecological protection and management method for a natural reserve, and the method comprises a satellite remote sensing ecological environment monitoring method which achieves the remote sensing image segmentation based on a satellite remote sensing image and a neural network model, is used for accurately distinguishing ecological systems, and accurately calculates the area of each ecological system through two-dimensional integral operation. Visual display is realized in a thermodynamic diagram form, and real-time monitoring of ecological system changes is realized; according to the species quantity change prediction and decision-making method, a neural network model is used for extracting a nonlinear feature relationship between species quantity change and each environmental factor in a species quantity change prediction data set, and accurate prediction of the species quantity change trend on the premise of known environmental factor change trends is realized; according to the species identification method, accurate identification and distinguishing of similar species are realized through big data and a neural network model. The method has the advantages of being large in monitoring range, automatic in monitoring, high in species identification and quantity statistics accuracy and high in population quantity change trend prediction accuracy.

The invention relates to the technical field of space target monitoring, and discloses an RCS information and Doppler information-assisted adaptive PHD filtering method, which comprises the following steps of: 1, establishing a Gaussian mixture logarithmic normal distribution model; 2, on the basis of the Gaussian mixture logarithmic normal distribution model, improving the Gaussian component weight of the Gaussian mixture logarithmic normal distribution model, and establishing an adaptive PHD filter assisted by RCS information and Doppler information; according to the method, target RCS information and Doppler information are introduced into a multi-target filtering updating process, and target feature information is fully utilized to perform space multi-target tracking in a space-based scene; meanwhile, according to the method, the difference between the target and the clutter is enlarged by using the target RCS information and the Doppler information; the problems that an existing filtering method cannot provide target amplitude and RCS information, the accuracy cannot be effectively guaranteed, and different target tracks cannot be effectively distinguished are solved.

The invention provides an adaptive azimuth updating method for radar signal sorting, and relates to the technical field of electronic warfare radar reconnaissance signal processing. The method comprises the following steps: step 1, a temporary result azimuth feature statistics module respectively counts parameter features of all pulses and azimuth features of large-amplitude pulses in each radar pulse sequence, and outputs a single-frame temporary result of each signal; and 2, a large-amplitude signal identification judgment module carries out large-amplitude signal identification judgment according to the target scanning type and the target amplitude information. And step 3, a self-adaptive azimuth updating processing module performs self-adaptive updating processing on the azimuth of the target table signal for three states of a tracking signal, a non-tracking large-amplitude signal and a non-tracking small-amplitude signal according to a large-amplitude signal identification judgment result. According to the invention, self-adaptive azimuth updating processing of radar signal sorting is realized aiming at the change of the target scanning type and the detection amplitude information of the radiation source, and the statistical precision of the output azimuth of the signal sorting is improved.

The application relates to a wireless channel modeling method, computer equipment, a storage medium and a computer program product. The method comprises the following steps: acquiring a small-scale channel matrix sample; generating a first distribution matrix; the first distribution matrix is an independent and identically distributed complex normal random matrix; generating a first constant matrix, a second constant matrix and a second distribution matrix according to the small-scale channel matrix sample; the first constant matrix is used for reflecting the energy coupling ability of a line-of-sight component, the second constant matrix is used for reflecting the energy coupling ability of a scattering component, and each element of the second distribution matrix is a power of a mutually independent generalized gamma distribution random variable; and acquiring a target channel matrix according to the first constant matrix, the second constant matrix, the first distribution matrix, the second distribution matrix and the small-scale channel matrix sample. The method can realize equivalence of GBSM and CBSM statistical characteristics which are universally applicable to any application scenario.

This invention discloses a method and system for local differential privacy aggregate value data aggregation based on sketches and sampling, belonging to the field of privacy computing and big data analysis technology. The method includes: initializing and disclosing sketch structure parameters on the server side; constructing aggregate value data on the user side, randomly selecting counter indices and determining the hash collision set; randomizing the hash collision set elements on the user side according to the aggregation function type, calculating the hit rate and performing adaptive pruning; reporting triples on the user side; and accumulating and updating the sketch counter on the server side, calculating the aggregated statistics through median estimation. This invention replaces traditional multi-element perturbation with sketch sampling and lightweight reporting, without requiring additional privacy budget consumption, effectively solving the noise accumulation problem, significantly reducing computational and communication overhead, and achieving a balance between privacy protection and statistical utility.

The present application relates to a target object statistical method, a target detection method, a neural network training method, a computer device, a computer-readable storage medium and a computer program product, wherein the target object statistical method obtains at least one frame of video image obtained by shooting a target area; performs target detection on the video image to identify at least one target object; tracks the target object to determine the direction of movement of the target object, and generates an identity corresponding to the target object; determines the quantitative statistical information of the target object according to the position distribution between the direction of movement of the target object and a reference line set for the target area, thereby solving the problem that statistical errors are prone to occur in object statistical methods based on computer vision recognition, and improving statistical accuracy.

The invention discloses a statistical method, system and device for the ear yield and leaf width of rice ears and a medium, and the method comprises the steps: collecting a to-be-segmented rice image, carrying out the preprocessing of the to-be-segmented rice image, and obtaining a preprocessed rice image; the preprocessed rice image is input into a trained rice detection and segmentation model for image detection and image segmentation, feature information of rice ears and rice leaves in the to-be-segmented rice image is obtained, and the rice detection and segmentation model is constructed based on a Transform model; and according to the feature information, performing statistics on the ear yield and the leaf width corresponding to the to-be-segmented rice image. The method can improve the statistical accuracy of the ear yield and the leaf width of the rice ears.

The invention discloses a line change relation statistical method and device, electronic equipment and a storage medium, and relates to the computer technology, and the method comprises the steps: constructing a network topological graph according to equipment information in a distribution network single line diagram; obtaining line change information between the current transformer node and the substation node from the network topological graph, wherein the line change information comprises a current transformer identifier and a line identifier corresponding to at least one target distribution line; and associating the current transformer identifier with the line identifier corresponding to the at least one target distribution line to obtain a line change relationship between the current transformer and the substation, and after statistics of each transformer in the distribution network single line diagram is completed, obtaining a statistical result of the line change relationship between each transformer and the substation. The method can automatically obtain the line change relation between each transformer and each transformer substation in the distribution network single line diagram, and achieves the beneficial effects of improving the statistical efficiency of the line change relation and improving the statistical accuracy of the line change relation through formulating the standard line hunting rule.

The present invention relates to a drilling depth statistics method and system based on target detection. The method comprises: inputting an image frame of a drilling rig into a pre-trained target detection model, identifying the coordinates of the plug and the tail of the drill rod of the drilling rig in the image frame, and obtaining a first recognition result; calculating the pixel distance between the plug and the tail of the drill rod according to the first recognition result; if the difference between the pixel distance between the plug and the tail of the drill rod in the image frame and the previous frame is greater than a preset threshold, the number of drill rods is increased by 1; and the drilling depth is calculated according to the known length of the drill rod and the number of drill rods. The scheme provided by the present invention can realize real-time, efficient and accurate drilling statistics, and has the advantages of strong pertinence, high recognition rate and strong generalization ability. Compared with traditional methods, the real-time performance of drilling depth statistics can be greatly improved, the statistical accuracy can be improved, and the labor cost can be reduced. In addition, the scheme does not require hardware changes to the existing drilling rig equipment, thereby reducing the transformation cost.

The embodiment of the present application provides a method and device for deduplicating traffic statistics, which relates to the field of communication technology. The method for deduplicating traffic statistics includes: obtaining data flow information of a target session; parsing the data flow information to obtain parsed data; judging whether the data flow information is duplicate traffic based on a preset hash table and the parsed data; if not, caching the data flow information; and when the target session ends, storing the cached data flow information on a disk. It can be seen that the implementation of this implementation method can deduplicate traffic, avoid multiple repeated statistics of the same traffic, improve the accuracy of traffic statistics, and thus improve traffic query performance.

The embodiment of the invention provides an inertia probability prediction method and device, and the method comprises the steps: constructing a comprehensive feature set containing basic operation features and real-time dynamic features, and enabling the comprehensive feature set to serve as the input of a prediction model; constructing a mixed risk objective function fusing an economic cost item, a decision risk cost item and a physical safety penalty item, wherein the mixed risk objective function is used for training a prediction model; and training a probability prediction model by adopting a risk-guided probability modeling method based on the mixed risk objective function so as to generate inertia probability distribution of the embedded decision risk and the security constraint. Through a risk-guided probability modeling method, complete probability distribution of the embedded decision preference and the security boundary is generated, so that the statistical accuracy of prediction is improved, and the prediction robustness in an extreme risk scene is ensured; and a more reliable inertia uncertainty description which better meets the decision demand is provided for fine scheduling and security defense of the power system in a new energy high-permeability environment.

The present application relates to the technical field of railway construction management, and more particularly to a railway operating line centralized repair workload management method and system, which comprises obtaining multi-source heterogeneous construction original data and structurally analyzing, executing work efficiency equivalent standardization conversion to generate a uniform dimension workload sequence, accurately associating with construction track and mileage markers, constructing a multi-dimensional progress control model for real-time progress fitting and deviation checking, dynamically starting resource scheduling correction, and multi-terminal visualizing the presentation of decision information flow. The present application can realize the unified quantification of heterogeneous workload, real-time monitoring and intelligent resource allocation of progress, and improve the digital and intelligent management level of centralized repair construction.

The invention provides a multi-user data traffic management method, electronic equipment and a storage medium, and relates to the technical field of communication. The method comprises the steps that service content data and service feature data of a plurality of terminals are acquired, the service feature data comprise service types, and the service content data and the service feature data are data extracted from data code streams acquired from a data acquisition control function entity; screening out at least two terminals with the same service type from the plurality of terminals, analyzing the service content data of the at least two terminals, and determining the service relevance of the at least two terminals; and managing the data traffic of the at least two terminals by adopting a preset management strategy matched with the service relevance according to the service relevance of the at least two terminals. The statistical accuracy of the data traffic of each terminal is improved, so that each terminal determines the use cost and the like based on the correct quantity traffic statistical information, and the use experience of a user is improved.