48results about How to "Rich dimension" patented technology

The embodiment of the invention provides an access control strategy construction method and device, electronic equipment and a storage medium. The access control strategy construction method comprises the following steps: determining access control elements and attributes thereof of an application based on an acquired resource access scene; based on the access control elements and the attributes thereof, an access control strategy template is created according to different access control scenes, and the access control strategy template comprises preset access control elements and attributes; selecting the access strategy template based on a service demand and assigning a value to the attribute to create a corresponding access control strategy; and performing matching calculation on the access control strategy and the intercepted resource access request based on a strategy calculation engine, and if matching succeeds, executing a corresponding strategy action. Through the steps, access control configuration is more convenient and easier to understand, and access control is more flexible.

The invention relates to the related technical field of digital data processing, in particular to an intelligent ancient book information processing method and device based on artificial intelligence, and the method comprises the steps: scanning an ancient book, constructing a knowledge graph, dividing a domain database, and training a vertical processing model; introducing a multi-form historical carrier to form a multi-mode sensing set, establishing a multi-information network, and embedding a processing model; the method comprises the following steps: establishing a dialog box, realizing multi-round interaction and combining threshold optimization output, solving the technical problems of digitization and fragmentation limitation in ancient book information processing and incapability of effectively integrating and utilizing ancient book information due to diversity and complexity of ancient books and literatures, and realizing construction of a knowledge graph and division of a domain database. A knowledge system with a hierarchical structure and logic association is formed, deep learning and optimization are performed according to specific requirements in the field of ancient books by training a vertical processing model, a dialog box is established, multi-round interactive feedback with the user is performed, and the user is assisted to quickly and deeply explore the ancient books.

A transparent visual power grid operation and maintenance system comprises a data acquisition and preprocessing module which is composed of a sensor network and SCADA system docking unit and a data preprocessing unit; the data processing and analysis module is composed of a fault prediction and diagnosis unit, an operation and maintenance strategy optimization unit and a three-dimensional modeling and dynamic simulation unit; the visual display and user interaction module is composed of an AR / VR interface development unit and a user-defined interface and report generation unit; and the system integration and communication module is composed of a standardized API interface and cloud platform unit and a remote access and cooperation unit, and the scheme of the invention solves the problem that the complexity of power grid operation and maintenance system data causes that detection information is difficult to provide visually, thereby affecting the operation and maintenance work quality and efficiency.

The invention discloses an NFC testing method based on machine learning, and relates to the technical field of wireless communication testing, and the testing method comprises the specific steps: S100, data collection and preprocessing: carrying out the basic testing of an NFC signal under different environment conditions, collecting the multi-dimensional data of signal intensity, transmission speed and error rate, and carrying out the data collection and preprocessing; by introducing deep fusion of the electromagnetic field theory and the machine learning technology, dimensions and methods of NFC testing are greatly enriched, the electromagnetic field theory serves as an important branch of physics, an accurate mathematical model and an experimental verification method of the electromagnetic field theory provide a solid theoretical basis for propagation characteristics of NFC signals in a complex environment, and the electromagnetic field theory and the machine learning technology are combined in advance. In combination with the strong data processing and prediction capability of a machine learning algorithm, the attenuation, reflection and diffraction phenomena of NFC signals in different media can be predicted theoretically, the model can be continuously corrected and perfected through actual test data, and the accuracy and reliability of a prediction result are ensured.

The invention discloses a credit risk assessment system for small and medium-sized enterprises in the production and manufacturing industry, and the system comprises a data collection and preprocessing module which is used for collecting and preprocessing data; the data enhancement module is used for training the generated adversarial network model and performing data generation and fusion; the credit risk assessment model construction and training module is used for constructing and training a credit risk assessment model; and the credit risk prediction and application module is used for credit risk prediction and result application. According to the invention, through a data enhancement technology, robust model construction and integration of multiple data sources, the accuracy, robustness and adaptability of credit risk assessment of small and medium-sized enterprises are significantly improved, and the problems of data imbalance, poor model generalization ability and the like in the prior art are effectively solved.

The invention relates to a fault detection method and device, computer equipment and a readable storage medium. The method comprises the following steps: acquiring alarm fault information and to-be-detected fault information of data resource information; converting the alarm fault information into a plurality of standard fault monitoring data arranged according to a first time sequence, and converting the to-be-detected fault information into a plurality of to-be-detected monitoring data arranged according to a second time sequence; according to the first time sequence and the second time sequence, performing cross combination on the plurality of standard fault monitoring data and the plurality of to-be-detected monitoring data to obtain cross combination grid data; detecting the fault information similarity between the alarm fault information and the fault information to be detected according to the distance information between the standard fault monitoring data and the monitoring data to be detected in each monitoring data grid; and based on the fault information similarity, generating a fault detection result corresponding to the to-be-detected fault information. By adopting the method, fault detection can be accurately carried out.

The invention relates to a method for analyzing user data in recruitment service. The method comprises the following steps: acquiring recruitment data of a target user; calculating an active score of the target user according to one or more of resume processing data, position release data and position interaction data in the recruitment behavior data; calculating an income score of the target user according to a handshake score and a handshake rate coefficient in the recruitment position data; calculating a consumption score of the target user according to the actual consumption cost progress and the predicted consumption cost progress in the recruitment payment data; and determining the health degree of the target user according to the active score, the income score and the consumption score, wherein the health degree is used for analyzing the service quality of the recruitment service platform to the user. According to the method, multiple data sources including the recruitment behavior data, the recruitment position data and the recruitment payment data are combined, so that the dimension of the data is greatly enriched. According to the method, the health degree of the user can be calculated more accurately, personalized services are provided, and the user experience is optimized.

The invention relates to a data processing method and device, computer equipment, a storage medium and a computer program product. The method comprises the steps of obtaining a reference dimension of user data through a reference platform, querying a target dimension complementary to the reference dimension in a preset dimension list of the user data, determining a target platform of the user data according to the target dimension, and controlling the reference platform and the target platform, and performing homomorphic encryption processing on the user data of the reference platform and the user data of the target platform to obtain at least two pieces of homomorphic encryption data, decrypting the combined homomorphic encryption data to obtain combined user data, and inputting the combined user data into a pre-trained user portrait evaluation model, according to the method, the user data of the multiple platforms are integrated by querying the target dimension complementary with the reference dimension, and the safety among the user data of the platforms is guaranteed.

This invention relates to the field of non-contact biosignal processing technology, providing a method, device, electronic device, and storage medium for determining psychological state assessment parameters. The method includes: inputting millimeter-wave radar signals into a psychological state assessment model to obtain psychological state assessment parameters; the psychological state assessment model includes a physiological feature extraction module, a micromotor feature extraction module, a multimodal feature fusion module, and a psychological state inference module. This invention reconstructs electrocardiogram waveforms through the physiological feature extraction module to obtain detailed physiological features, extracts micromotor features through the micromotor feature extraction module, and integrates features reflecting internal physiological changes and external behavioral manifestations through the multimodal feature fusion module. This forms a more comprehensive and multidimensional fused feature set for comprehensive analysis by the psychological state inference module, greatly improving the comprehensiveness and accuracy of psychological state assessment in unconstrained daily environments.

The present application belongs to the technical field of ecological system or natural environment protection by using big data analysis, further to the technical field of biodiversity monitoring and protection, and specifically relates to a biological species loss risk assessment method and a monitoring and early warning system.The intelligent monitoring and early warning system for monitoring the species loss risk of the present application comprises a data acquisition module, a data transmission module, an analysis module and a model saving module.The intelligent system or method of the present application can intelligently monitor the species loss risk through big data analysis and integration, and is more accurate, fast and convenient than artificial monitoring and evaluation.According to the monitoring result, the person skilled in the art can effectively formulate corresponding protection strategies, and further effectively protect the biodiversity and the natural environment.

The present invention relates to a quantitative method for the quality of online reviews of e-commerce companies based on the AHP-fuzzy comprehensive evaluation method, which belongs to the technical field of data analysis and mining. First, an online review quality evaluation framework is constructed, the framework includes several dimensions, each dimension includes several indicators; the dimensions and indicators are quantitatively calculated; the review quality levels are divided, and the weights of different indicators under the same dimension are determined to calculate the quantitative values ​​of each dimension; for the quantitative values ​​of each dimension, the weights of different dimensions are determined, and the fuzzy comprehensive evaluation method is combined to calculate the quality values ​​of the online reviews, and then the quality level evaluation of the reviews is obtained according to the corresponding relationship between the values ​​and the quality levels. The present invention constructs a relatively comprehensive online review quality evaluation system, integrates the quantitative values ​​of these dimensions and indicators, and calculates the quantitative representation of the quality of online reviews.

The invention relates to the technical field of multi-modal corpus construction, in particular to a multi-modal corpus construction method and system. Comprising a multi-source heterogeneous data acquisition module, a multi-modal preprocessing and analysis module, a cross-modal automatic alignment and association module, a translation feature labeling and management module, a structured storage and index module, an AI intelligent retrieval and teaching application module, a semantic optimization multi-modal adaptation module and a user display terminal. The multi-source heterogeneous data acquisition module comprises a data source interface unit and a metadata extraction unit; a multi-modal corpus system deeply integrated with a translation theory is constructed to directly serve the core demand of a translation subject, and a triple screen array mode is adopted to cooperate with display, so that display content is reasonably distributed, a user can check and operate in multiple dimensions, the use experience and the working efficiency are greatly improved, and the user experience and the working efficiency are improved. And various requirements of translation teaching and the like are met.

This invention discloses a method and system for processing personnel information for business administration based on big data, relating to the field of personnel information data processing technology. The method includes the following steps: acquiring personnel information; preprocessing the personnel information to obtain preprocessed text information; processing the preprocessed text information through an embedding layer based on a CNN-BERT model to obtain a word vector matrix; processing the word vector matrix sequentially through a CNN convolutional layer, pooling layer, and fully connected layer to obtain structured data; using an improved ant colony optimization algorithm to perform path optimization for multi-condition combined queries on the structured data to obtain the globally optimal retrieval path; retrieving personnel information that satisfies the multi-condition combined query from the structured data based on the globally optimal retrieval path; and adaptively updating the global pheromone of the improved ant colony optimization algorithm after each round of multi-ant colony collaborative search to accurately locate the target personnel information.

The invention relates to the technical field of feed water heater operation performance analysis, and provides a nuclear power feed water heater operation performance analysis method which comprises the following steps: calculating a pipe side state according to pipe side measuring point data of a feed water heater, calculating states of a feed water heater shell side and a drain outlet pipeline, and calculating heat exchange performance of a condensation zone. Comprising condensation zone heat transfer efficiency and condensation heat transfer coefficient. The operation performance and the interface thermodynamic state of the nuclear power plant feed water heater can be efficiently and accurately analyzed.

The present invention discloses a method, device, storage medium and terminal for recommending tasks based on user portraits. The method includes: collecting and preprocessing truck data and user data; associating the preprocessed truck data and user data to generate a pulled-through data set; wherein the pulled-through data set includes multiple successfully associated truck data and user data; setting a label theme set of the user portrait according to a target application scenario; mapping multiple successfully associated truck data and user data one by one to each label theme in the label theme set of the user portrait to generate a label theme set of associated data; filtering the label theme set of the associated data according to a preset filtering rule to generate a target user group; and recommending at least one task corresponding to the target application scenario to the target user group. Therefore, by adopting the embodiments of the present application, the dimensions and quality of constructing user portraits can be enriched, and the accuracy of service recommendation for users can be further improved.

The invention belongs to the technical field of data representation, classification and electric signal processing, and relates to a classification system and method based on data inspection and controllable feature selection. The system comprises a data acquisition module, a feature extraction module, a feature crossing unit and a machine learning classification module, and further comprises a data preprocessing module and an I / O control module. And the I / O control module realizes controllable feature selection by controlling input and output. According to the system and the method, autocorrelation and active section secondary inspection are introduced by means of the data preprocessing module, so that the data quality is improved; multi-dimensional feature extraction is realized through a feature extraction module; controllable feature selection is introduced into the I / O control module, dynamic selection and optimization of features are achieved, and the accuracy and flexibility of diagnosis are improved; machine learning model classification is adopted, and automation and intelligentization of signal classification are achieved; the modular design enables the functional units to be closely connected, data flow is smooth, and stable operation, upgrading and maintenance of the system are facilitated.

The invention discloses a decision-making assistance method based on correlation analysis, relates to the technical field of big data processing, and solves the problem that more accurate decision-making assistance data cannot be provided for decision-making due to the fact that correlation analysis of decision-making influence factors and environmental data is not performed in the prior art. The method comprises the steps of firstly collecting power grid data, weather data and transaction data; then obtaining association conditions between the weather data and the power grid data and between the weather data and the transaction data, obtaining a sequence of association degrees between the weather data and the power grid data and between the weather data and the transaction data, further obtaining a comprehensive sequence, and assigning a value to each sequence; then obtaining prediction data of the power grid data and the weather data; and finally, constructing a decision-aided objective function, taking benefit maximization as an objective and considering a fluctuation coefficient in the objective function, and inputting prediction data to obtain a strategy for decision reference, thereby providing more accurate decision-aided data for decision.

The invention belongs to the technical field of optical communication, and particularly discloses an underwater encryption communication method and device for multi-dimensional optical parameter fusion, and the method comprises the steps: mapping to-be-transmitted real information (real codes) and false information (virtual codes) to a plurality of physical parameters of an optical carrier at a transmitting end; and a brand-new and high-concealment composite signal is constructed through fusion of the two signals. And the composite signal is decoded at a receiving end, so that real information is obtained. The invention aims to solve the problems that the existing underwater laser communication is easy to intercept, the anti-interference capability is poor and the safety is insufficient.

The invention provides a three-mode rotating support operating under an electric arc wind tunnel condition and a using method thereof. The three-mode rotating support comprises a rotating disc, a rotating shaft, an electric rotating disc, an electric push-pull rod, a model support, a push-pull sliding ring and a supporting rod. The outer ring of the rotating disk is provided with three uniformly distributed mounting sheets, and each mounting sheet is provided with a model support through a rotating shaft. The electric rotating disc drives the rotating shaft and the rotating disc to rotate integrally, and sequential switching of the three models at the arc wind tunnel nozzle outlet checking station is achieved. The electric push-pull rod drives the push-pull slip ring to move axially and converts linear motion into pitching rotation of the model support through the supporting rod, so that the attack angle of the model is adjusted in real time during examination. According to the invention, continuous examination of three models can be completed in one vacuum-pumping period, dynamic change of the angle of attack in the test process is supported, and the efficiency and the data acquisition capability of the arc wind tunnel test are greatly improved.

The invention relates to a semantic change detection method, in particular to a tower footing hyperspectral semantic change detection method considering illumination change. The method comprises the following steps: S1, determining a target scene according to the position of a tower footing remote sensing platform and an optical path coverage range, and presetting a hyperspectral imager; moving the at least three gray level targets with gradient differences to the target scene; s2, acquiring image data of the target scene and all the gray scale targets by using a hyperspectral imager, and acquiring radiance values of all the gray scale targets according to the image data of all the gray scale targets; performing radiation correction on the target scene by using the radiance values of all the gray scale targets and the known reflectivity values thereof to obtain the radiance value of the target scene; and S3, performing semantic change detection analysis by using the hyperspectral data subjected to radiation correction. According to the invention, radiation correction of the target scene can be realized, and more accurate surface feature reflectivity data can be obtained.

This utility model relates to a simple galvanometer adjustment device suitable for laser processing equipment. It includes a connecting plate with a Z-axis adjustment device mounted on it. A reference mounting plate is mounted on the Z-axis adjustment device, and a main galvanometer connecting plate is also mounted on the reference mounting plate. The main galvanometer connecting plate faces the main mating surface of the reference mounting plate and has four arc-shaped elongated holes. A secondary galvanometer connecting plate, also with four arc-shaped elongated holes, is connected to the main galvanometer connecting plate, allowing the secondary galvanometer connecting plate to be adjusted for pitch angle on the main galvanometer connecting plate. A galvanometer device is mounted on the secondary galvanometer connecting plate, and a field lens is mounted on the galvanometer device. Thus, through the perpendicular contact surface design between the main galvanometer connecting plate and the reference mounting plate, and between the secondary galvanometer connecting plate and the main galvanometer connecting plate, combined with the arc-shaped elongated holes, independent adjustment of left-right yaw and pitch angles can be achieved. This allows for precise perpendicularity of the galvanometer device and the field lens to the virtual reference plane, effectively improving the precision of laser processing.

The application discloses a method for generating a test sample, comprising: receiving a generation request for generating a test sample, the generation request comprising a test sample generation strategy for a target application under test, the target application under test having a downstream application; in response to receiving the generation request, obtaining a to-be-varied sample of the target application under test, the to-be-varied sample comprising historical request data for the target application under test and historical response data responded by the downstream application to the response data of the target application under test, the response data of the target application under test being response data of the target application under test to the historical request data; and generating the test sample according to the test sample generation strategy and the to-be-varied sample for testing the target application under test.

The invention provides a resource pushing method and device, equipment, a medium and a program product, and is applied to the technical field of artificial intelligence and the technical field of financial science and technology. The method comprises the following steps: acquiring a user behavior data stream related to a user, wherein user behavior tensors corresponding to a plurality of specified moments in the user behavior data stream represent interaction behaviors executed by the user at the plurality of specified moments; according to the difference between at least two adjacent user behavior tensors, performing incremental tensor decomposition on the specified user behavior tensor to obtain time factor data and behavior feature data related to the specified moment; performing interaction behavior evolution analysis on the user based on the time factor data corresponding to the plurality of specified moments to obtain behavior evolution data representing a user interaction behavior change trend; and determining an interaction intention of the user based on the behavior evolution data and the behavior feature data, and pushing a target resource matched with the interaction intention to the user.

The application discloses a method for generating a test sample, comprising: receiving a generation request for generating a test sample, the generation request comprising a test sample generation strategy for a target application under test, the target application under test having a downstream application; in response to receiving the generation request, obtaining a to-be-varied sample of the target application under test, the to-be-varied sample comprising historical request data for the target application under test and historical response data responded by the downstream application to the response data of the target application under test, the response data of the target application under test being response data of the target application under test to the historical request data; and generating the test sample according to the test sample generation strategy and the to-be-varied sample for testing the target application under test.

The invention discloses an identity recognition method and device of an unmanned aerial vehicle, a storage medium and electronic equipment. The method relates to the technical field of safety, and comprises the steps that first identity information of a target unmanned aerial vehicle to return is acquired, and the first identity information at least comprises flight parameters and energy consumption parameters of the target unmanned aerial vehicle; performing identity verification on the first identity information according to multiple pieces of second identity information in a target database to obtain a first verification result; under the condition that the first verification result represents that verification is passed, secondary identity verification is carried out according to the external image and the internal image of the target unmanned aerial vehicle, a second verification result is obtained, and the second verification result is used for representing whether identity verification of the target unmanned aerial vehicle is passed or not. Through the method and the device, the problem of relatively low accuracy of identity recognition of the unmanned aerial vehicle caused by identity recognition through the ID of the unmanned aerial vehicle in related technologies is solved.

The application discloses a workshop production quality online detection system based on machine vision and AI, and particularly relates to the field of machine vision detection, and comprises the following steps: through a multi-modal data acquisition and preprocessing module, physical signals, process parameters and actual quality values of products are synchronously acquired, and after data cleaning, semantic alignment and standardization processing, structured data blocks of associated product information are generated; then, through a feature extraction and mixed vector generation module, physical information features and multi-modal data driven features are extracted and fused into a mixed vector, a network is trained to output a comprehensive quality index and a corresponding time sequence; finally, through a quality field energy coupling decision module, a quality toughness coefficient and a process fluctuation conduction coefficient are calculated, three types of energy fields, i.e., compliance, consistency and risk, are defined, a comprehensive decision value is obtained through coupling, four-level quality decisions, i.e., high-quality, qualified, to-be-checked and rejected, are output according to the value and field characteristics, production circulation is guided, and the accuracy and efficiency of quality detection are effectively improved.

The present application relates to a data processing method, device, computer equipment and storage medium. The method comprises: obtaining a water area data set, and constructing a characteristic sequence and a reference sequence based on the water area data set; the characteristic sequence contains water area data of each water quality influencing factor index in the water area data set; the reference sequence contains reference data of each water quality influencing factor index in the water area data set; according to the grey correlation algorithm, the correlation between the water area data of each water quality influencing factor and the reference data between the characteristic sequence and the reference sequence is calculated; according to the correlation corresponding to each water quality influencing factor index, the target water quality influencing factor index is determined in each water quality influencing factor index, and based on the target water quality influencing factor index, the water quality health impact result is determined in the correlation relationship library. The use of this method improves the accuracy of the water quality health impact result.

The application relates to the technical field of industrial safety production supervision and intelligent identification, and discloses a multi-modal multi-verification access control linkage method for industrial safety, which comprises the following steps: continuously acquiring a visible light video stream and an infrared light video stream of a to-be-passed region, extracting a to-be-processed image frame pair, inputting the to-be-processed image frame pair into a pre-trained multi-task neural network model, and outputting an identity verification result, a living body verification result and a wearing compliance verification result; only when the three verification results are all compliant and the wearing compliance result meets a preset work type-wearing mapping relationship, the door body is controlled to be opened; and within a time window from the opening of the door body to the closing of the door body, the actual number of passing people is counted based on background difference operation, and if the actual number of passing people is greater than the number of people passing through the verification, an abnormal alarm signal is generated. Through multi-modal data fusion and a multi-task parallel reasoning architecture, in combination with a work type-wearing differentiated judgment and a trailing detection mechanism, the application realizes high-precision, anti-fraud and anti-tailing safety access control in an industrial scene.

The invention discloses a VLA-based low-speed park automatic driving method, and relates to the technical field of automatic driving, and the method comprises the steps: collecting a plurality of park environment data, generating a panoramic park environment perception tensor, executing semantic element recognition and dynamic subject motion trend pre-judgment, and generating a park environment semantic analysis topology with a dynamic motion trend; performing advance obstacle avoidance path planning and stationary path optimization on the park environment semantic analysis topology with the dynamic motion trend and the preset driving path, and generating a park automatic driving control instruction set with dynamic safety redundancy; and executing the instruction set and collecting vehicle driving state feedback data to generate a multi-mode-path planning collaborative optimization parameter tensor, and continuously adjusting automatic driving execution logic. Therefore, automatic driving can continuously adapt to scene changes in long-term operation, and the operation stability and robustness are improved.