34results about How to "Increase data dimension" patented technology

The invention provides a surrounding type hybrid optical field imaging device and method. The method includes parameter calibration of a surrounding type hybrid optical field imaging device, and also includes using the surrounding type hybrid optical field imaging device to obtain images, fusing the obtained images, rendering the obtained images, and generating a final image. The surrounding type hybrid optical field imaging device and method provided by the invention combine a parameter calibration means with the depth capability of an optical field camera and a high-definition image of a traditional camera, and can obtain a high-quality scene three-dimensional image.

The invention discloses a method and a system for determining fault characteristics of an active power distribution network. The determination method comprises the steps of S1, generating sample databased on acquired historical operation data; S2, performing feature selection on the sample data by using a support vector machine model-recursive feature elimination algorithm, and extracting fault features; S3, substituting the data corresponding to the fault features in the sample data into a fault prediction model built based on a support vector machine, determining the fault prediction accuracy of the fault prediction model, setting the fault feature as the fault feature of the active power distribution network when the fault prediction accuracy meets the requirement, or otherwise, executing the step S1 to regenerate the sample data. According to the fault feature determination method provided by the invention, the prediction efficiency of the fault prediction model is improved, a reference is provided for power distribution network operation and maintenance personnel, and the labor intensity of the maintenance personnel is reduced.

The invention discloses a micro-seismic signal multi-scale denoising method and device and a readable storage medium, and the method comprises the steps: 1, obtaining a micro-seismic signal, carryingout the EMD or EEMD decomposition, and filtering the high-frequency noise in the decomposed signal; 2, respectively constructing a Hankel matrix of each IMF component; 3, carrying out singular value decomposition is based on the Hankel matrix of each IMF component to obtain a score vector of principal component analysis, carrying out primary denoising, and carrying out soft threshold secondary denoising on each component signal and residual component after primary denoising; and 4, superposing the component signal subjected to secondary denoising and the residual component to obtain a denoisedmicro-seismic signal. According to the method, singular value decomposition is associated with principal component analysis, information of singular value decomposition serves as a score vector of principal component analysis, the PCA calculation process is simplified, and the defect that denoising cannot be conducted on a single column vector through the score vector of singular value decomposition is overcome.

The invention discloses an attribute reasoning and product recommendation method based on an adaptive graph convolutional network. The method comprises the following steps: 1, constructing heterogeneous data: a scoring matrix of a user to a product, a user attribute matrix, a product attribute matrix, a user attribute index matrix and a product attribute index matrix; 2, performing missing value filling preprocessing on the user attribute matrix and the product attribute matrix; 3, obtaining a cooperative matrix through one-hot coding; 4, constructing a feature fusion layer according to the attribute matrix and the collaborative matrix; 5, carrying out feature propagation through a graph convolution layer; 6, constructing a prediction layer to perform attribute reasoning and product recommendation; 7, updating the node attribute matrix according to the output result of the prediction layer; and 8, repeating the steps 4-7 until the attribute reasoning and product recommendation effectsare optimal. According to the method, the high-order structure information of the graph, the internal interaction between the node attributes and the potential association between the node attributesand the link relationship can be fully mined, so that more accurate attribute reasoning and product recommendation are realized.

The invention discloses an information recommendation method and device, computer equipment and a storage medium, which can be used for improving the pertinence of information recommendation. The method comprises the steps of calculating interestingness of a user to each first application according to search data, click data and installation data; obtaining an application description text corresponding to each first application; determining a feature vector of the user according to the TF-IDF vector of the application description text and the contribution degree of each first application to the user;; clustering the users according to the feature vectors of the users to obtain user groups; determining a second application for the target user as a to-be-recommended application according tothe similarity between the target user and other users in the user group and the interestingness of other users for the second application; and generating recommendation information according to the to-be-recommended application and recommending the recommendation information to the target user.

The invention relates to the technical field of internet, and discloses method and system for automatically acquiring a data model. The method comprises the steps of configuring a data access rule; defining and building the data model according to the type and demand of acquired data; analyzing the data according to the forms and rules of the acquired data; filtering the analyzed data; mapping the filtered data to the data model again for matching; configuring a display module to the successfully matched data; starting to acquire. Compared with the prior art, the method has the advantages that the real-time big data stream technology is adopted, the advantage of big message data is fully utilized, and the effective information are mined to provide support to a target; the accuracy of the complementing result is increased as the dimension of the data adopted increases.

The invention discloses a financial analysis report generation method and a device. The method comprises the steps of obtaining a data message of a target object; performing data arrangement on the data message by using the structured query statement to generate a standard message, and performing data cleaning; carrying out field extraction and calculation on the cleaned standard message accordingto an index construction rule to generate a financial index; and calculating the deviation rates of the same financial indexes from different sources, counting the financial indexes and the deviationrates, generating a financial analysis report, and outputting the financial analysis report. By applying the method of the invention, the cross validation among various data can be carried out by utilizing the deviation rate, so that the analysis direction of financial analysis, namely the analysis of the authenticity of financial data, is increased, meanwhile, the quality of data used later is ensured, and the data dimension and depth are expanded. And the financial analysis result is more accurate and comprehensive, so that the report can better conform to the overall state and developmenttrend of an enterprise.

The invention discloses an indoor positioning method based on a WiFi hot spot, which comprises an offline stage and an online stage, wherein the offline stage comprises the steps that a sample reference point and an AP node for receiving the WiFi hot spot are set in a designated area range, and information of all the AP nodes of all the reference sample points is collected; the mapping relation between the information of each AP node collected by each sample reference point and the position information of the corresponding reference point is calculated, and a fingerprint database is established; and a characteristic fingerprint space of the fingerprint database is extracted by adopting a PCA analysis method based on MapReduce. The online stage comprises the following steps: an RSSI signalof each AP received at each sample reference point is collected on line through a positioning terminal, and therefore an RSSI signal vector is formed; the PCA analysis method is adopted to extract themain positioning characteristic of the RSSI signal vector, so as to obtain a characteristic vector of the RSSI signal of each sample reference point; and accurate positioning is carried out accordingto the characteristic vector of the RSSI signal and the data information of the characteristic fingerprint space by adopting an EWKNN algorithm based on MapReduce.

The invention discloses a collaborative filtering recommendation method based on enhanced graph learning, and the method comprises the steps: 1, constructing a bipartite graph of a user to a product, wherein the bipartite graph comprises a user node set, a product node set and an adjacent matrix; 2, obtaining an embedded matrix as a node feature through one-hot coding; 3, calculating a similar matrix according to the current node characteristics, and performing sparsification; 4, taking the sparse similar matrix as a residual item and adding the residual item to the adjacent matrix to obtain an enhanced adjacent matrix; 5, carrying out feature propagation according to the enhanced adjacent matrix structure graph convolution layer, and obtaining node representation; and 6, obtaining a score matrix from the prediction layer according to the node representation, thereby realizing product recommendation. According to the method, the graph structure information can be adaptively learned based on the similarity between the nodes, and the robustness and integrity of the graph are enhanced, so that more accurate node representation is learned, and the recommendation performance is improved.

The invention provides a domain name detection method and device, equipment and a storage medium, and relates to the technical field of network security. The method comprises the following steps: acquiring a domain name to be detected and inter-domain information corresponding to the domain name to be detected; associating the domain name to be detected with inter-domain information corresponding to the domain name to be detected; and inputting the associated domain name to be detected and the inter-domain information corresponding to the domain name to be detected into a pre-trained domain name classifier to obtain a detection result of whether the domain name to be detected is the target domain name or not.

The invention relates to a genetic diagnosis system integrating data acquisition, analysis and report generation. The system comprises a clinical module, a medical history module, an association module and a report module. The medical history module carries medical history data of a patient and a plurality of groups of family data distinguished based on family tags, wherein a plurality of identity tags are linked to the family tags, and every two identity tags are associated through family attributes; the association module is respectively connected with the clinical module and the medical history module, and associates the clinical data with the medical history data of the patient through the identity tags, so that the identity tag of the patient can be taken as a center, and a family data network can be formed through outward expansion of family attributes; and the personal clinical data and the medical history data of the corresponding members are linked through the identity tags of the members of different families, so that a multi-dimensional family data network is formed, and comprehensive and accurate genetic diagnosis is realized.

The invention discloses an online retrieval method and system. The method comprises the steps of constructing query points based on query operation; searching a neighbor point of which the direction is closest to the query point in a direction navigation map; and determining at least one return point closest to the query point based on the operation of searching the neighbor point closest to the query point in the direction. According to the method, the concept of the direction navigation graph is introduced on the basis of the direction vector, and the attribute that the direction navigation graph can be used for performing direction pruning on neighbors is utilized, so that the graph retrieval efficiency is greatly improved, and the method can adapt to online retrieval application scenes with larger data scales and higher data dimensions.

The invention discloses a multi-target human body activity sensing device based on a radar echo analysis algorithm, which comprises a preceding-stage radar module and a data processing and main control unit, and is characterized in that the preceding-stage radar module is used for receiving and sending signal data and performing data transmission with the data processing and main control unit; the data processing and main control unit comprises a main control MCU, the main control MCU comprises a waveform calibration module and a data processing module, the waveform calibration module carries out echo processing analysis and identification and sends processed data to the data processing module, and the data processing module completes identification of waveform basic feature points and carries out data processing. The novel sensing device is used in an indoor space, can identify and comprehensively measure the multi-target activity behavior amplitude according to a radar echo analysis principle, and normalizes the multi-dimensional data to measure the human body thermal environment comfort level load index.

The invention discloses a mechanical ventilation man-machine asynchronous detection method and device based on a graph neural network, a storage medium and equipment. The detection method comprises the following steps: acquiring real-time waveform data of a to-be-detected object in a mechanical ventilation process; converting the obtained real-time waveform data into real-time graph structure data; and inputting the real-time graph structure data into a pre-trained graph convolutional neural network model to obtain a man-machine asynchronous type. According to the detection method, the waveform data is converted into the graph structure data in the non-Euclidean space, and the graph convolutional neural network model is adopted to predict the man-machine asynchronous type, so that the data dimension is improved, the data analysis freedom degree is enhanced, and the visual sense of analysis processing is widened; therefore, the man-machine asynchronous type prediction accuracy of the to-be-tested object in the mechanical ventilation process is improved.

The invention discloses a method and device for monitoring grain condition in a bulk grain container, and the method comprises the steps: collecting temperature and humidity data, obtaining the temperature and humidity data of the environment where grains are located in real time, transmitting the temperature and humidity data to a collection terminal, marking a time label on the received temperature and humidity data by the collection terminal to generate timing temperature and humidity data; transmitting the timing temperature and humidity data to a remote server; performing temperature and humidity data processing: enabling the remote server to perform filtering and wavelet analysis on the timing temperature and humidity data, interpolate and eliminate repeated data, and obtain continuous temperature and humidity data of each acquisition node; and performing temperature and humidity data fusion: fusing the continuous temperature and humidity data by using a k-medoids clustering algorithm, carrying out fusion once in each acquisition period, fusing the continuous temperature and humidity data of the plurality of acquisition nodes into a piece of continuous overall temperature and humidity data, and reflecting the overall state of the environment in which the grains are located by the overall temperature and humidity data. The invention further discloses a monitoring device applying the monitoring method.