50results about How to "Efficient discovery" patented technology

The invention discloses a metering-based carbon emission accounting system, which relates to the technical field of carbon emission accounting, and comprises the steps of acquiring energy consumption data, modeling the acquired energy consumption data, predicting an energy consumption trend, analyzing the energy consumption data, generating a preliminary carbon emission factor according to different energy types and consumption, and calculating the carbon emission of the carbon emission accounting system according to the preliminary carbon emission factor. And performing iterative optimization on the initial carbon emission factor through a carbon emission factor generation and optimization module, calculating the carbon emission by using the optimized carbon emission factor, setting a threshold value for comparison, performing early warning on the abnormal condition of the carbon emission in real time, and matching an emission reduction suggestion through an emission reduction optimization suggestion module. According to the invention, through energy consumption data acquisition, energy consumption trend prediction, carbon emission factor generation and optimization, and early warning and emission reduction optimization suggestion, the automation and intelligence level of carbon emission management is improved, and powerful technical support is provided for green low-carbon transformation.

The invention discloses a power prediction method considering photovoltaic power clustering, which comprises the following steps of: firstly, acquiring historical data of a photovoltaic power station, decomposing a photovoltaic power time sequence by using an STL time sequence decomposition method, performing DBSCAN clustering on the decomposed photovoltaic power data, identifying a low-power cluster and a high-power cluster, and predicting the power of the photovoltaic power station according to the low-power cluster and the high-power cluster; establishing a photovoltaic power prediction model based on a time convolutional network and Times Net for low power and high power respectively; secondly, a badger algorithm is improved, Chebyshev chaotic mapping is adopted to improve initialization of a badger population, and a Gaussian mutation strategy and a lens imaging reverse learning strategy are introduced to obtain MHBA; and optimizing hyper-parameters of the TCN photovoltaic low-power prediction model and the TimesNet photovoltaic high-power prediction model by using an improved badger algorithm, and predicting photovoltaic power by using the optimized models to obtain a final prediction value. Compared with the prior art, the precision and effectiveness of the photovoltaic power prediction model can be improved.

The invention belongs to the technical field of distributed databases, and particularly relates to a decentralized copy control method of a distributed database, which comprises the following steps: step 1, copy management: determining the number and storage positions of copies according to data volume and system load requirements, and reasonably distributing data copies to different nodes; 2, replica consistency: selecting a consistency model to balance system performance and data consistency requirements; 3, synchronizing the copies: determining a data synchronization strategy between the copies, and adjusting according to the real-time requirement of the system; 4, conflict detection and resolution: detecting data conflict by using a timestamp, a version number or a logic clock mechanism, and designing a conflict resolution strategy; and 5, replica recovery: monitoring the state of each node, quickly detecting replica faults, and recovering data from other replicas. The stability, reliability and performance of the distributed database system can be effectively improved, and the distributed database system adapts to constantly changing service requirements.

The invention discloses a power distribution network fault positioning method and equipment based on a graph convolutional neural network, belongs to the technical field of power distribution network fault positioning, and is used for solving the technical problems that a traditional fault positioning method depends on feature information of a single node, neglects the overall structure of a power distribution network and is difficult to deal with a complex and changeable power distribution network. The method comprises the steps of performing data preprocessing on a collected data set to obtain a target data set; constructing an optimization matrix based on the target data set and the topological structure diagram of the to-be-tested power distribution network; performing node feature extraction on the topological structure diagram to obtain a node feature vector; training a graph convolutional neural network through the optimization matrix and the node feature vectors, and performing sample balance adjustment to obtain a power distribution network fault positioning model; and inputting the to-be-detected data into the power distribution network fault positioning model for identification to obtain state parameters of each node, and positioning a fault node according to the node state parameters. According to the invention, the accuracy and robustness of power distribution network fault positioning are improved.

The invention discloses a non-vision field imaging detection method and system fused with an event camera, and the method comprises the following steps: enabling the event camera and a standard optical camera on a detection prototype to be aligned with a ground region of a corner, forming a video file based on a tiny pixel color difference amplification technology, and carrying out the calculation and analysis of the video file; processing the video file by using an image matching algorithm, and eliminating noise by using Kalman filtering; establishing a linear system, and then obtaining a reconstructed image by using a forward transmission light intensity function; performing Euler video amplification processing on the reconstructed image, wherein the Euler video amplification comprises motion estimation, spatial decomposition, time filtering and signal enhancement; detecting the detection area, and mapping the motion track of the target hidden behind the corner to a two-dimensional plane; the system comprises a simulation scene construction module, a three-dimensional point cloud set construction module and an information integration module. According to the invention, a micro motion algorithm and optical flow calculation are popularized to non-vision field imaging, so that the optical imaging technology can act on a vision field range and also can act on a non-vision field range.

The invention provides an operation ship monitoring method and device, a program product and electronic equipment, and relates to the technical field of information monitoring. The method comprises the following steps: determining a reference operation duration range of one or more processes related to a target ship according to historical operation information; the reference operation duration range of each process comprises a plurality of levels of reference operation duration ranges, and the ranges are increased along with the increase of the levels; obtaining the operation duration of the target ship in the current process, and obtaining a plurality of levels of reference operation duration ranges of the current process, including a first-level reference operation duration range; and if the operation duration of the current process exceeds the first-level reference operation duration range of the current process, determining the operation abnormality level of the target ship according to the reference operation duration range of the operation duration of the current process, and sending corresponding alarm information to the target ship. According to the method and the device, the abnormity of the operation ship can be timely and effectively found under the condition of not depending on an artificial report.

The embodiment of the invention discloses a power failure fault warning method and device, electronic equipment and a computer readable medium. A specific embodiment of the method comprises the following steps: acquiring a real-time digital twinborn model; in response to the received equipment fault detection information, obtaining a target equipment identifier; obtaining a power equipment association relationship graph from a distributed server; according to the target equipment identifier, performing preliminary cutting on the electrical equipment association relationship graph to generate a first cut graph; determining first power failure influence range information according to the first clipped map; obtaining a distribution map from a distributed server; screening out at least one piece of first key facility object information from the distribution map; and displaying a first real-time region image corresponding to the first power supply sub-region in the real-time digital twin model. According to the implementation mode, the corresponding related power failure information can be quickly and efficiently generated for the fault equipment, subsequent power equipment maintenance can be carried out in time, and stable power supply is guaranteed.

The invention provides an automatic vulnerability utilization and construction method based on symbol solution. The method comprises the following steps: step 1, a utilization generation method based on constraint solution; specifically, code injection and utilization are analyzed, three vulnerability utilization methods of bypassing ASLR by using a springboard and bypassing NX by using return-to-libc are used, and a corresponding automatic utilization data construction process by using a constraint expression phi exp (epsilon) is constructed respectively; step 2, utilizing and generating the automatic vulnerability Exploit; checking a security mechanism of a program starting place through CheckSec; if the program starts NX protection, performing ROP utilization construction in combination with an ROP utilization means; if the program does not start NX protection, whether an ASLR mechanism is started or not is checked, if the ASLR mechanism is started, ROP utilization construction is carried out in combination with an ROP utilization means, and if the ASLR mechanism is not started, two kinds of utilization can be constructed in combination with a Shellcode utilization means and the ROP utilization means. By applying the technical scheme, the automation level, accuracy and efficiency of vulnerability utilization construction can be improved, and progress in the field of security research is promoted.

The invention relates to the technical field of network space security, in particular to an IPv6 address prediction method and system based on a double-space tree, and the method comprises the steps: dividing an address seed set into seed address subsets of different BGP prefix spaces according to an open-source BGP prefix list; generating a double-address space tree by taking the seed address subset of each BPG prefix space as a unit; extracting leaf nodes in the prefix space tree and the suffix space tree and splicing the leaf nodes in the prefix space tree and the suffix space tree to generate a candidate address mode; and according to the number of the seed addresses in the BGP prefix space, carrying out descending sort on the BGP prefixes and setting address generation priorities, so as to carry out address generation in the corresponding BGP prefix space according to the sequence of the address generation priorities, and obtaining a candidate address set in the corresponding BGP prefix space through address alias deletion. According to the method, active addresses and more / 64 active address prefixes can be found more efficiently, scanning of a large number of possibly inactive addresses in a BGP prefix space is avoided, and the efficiency of an IPv6 address prediction process is improved.

The invention belongs to the technical field of electricity charge management, and discloses an electricity charge business online management method and system. The method comprises the following steps: establishing a digital twin model based on a cloud data center, and constructing an electric charge business data analysis model and an electric energy scheduling model; based on the data transmission base station, a plurality of pieces of real-time electricity charge service data are collected and uploaded to the cloud data center; performing data analysis on a plurality of pieces of real-time electricity charge service data by using an electricity charge service data analysis model and a digital twin model; performing electric energy scheduling on the real-time data analysis result by using an electric energy scheduling model; and based on the cloud data center, a digital twin model is used to visualize a plurality of pieces of real-time electric charge business data, real-time data analysis results and real-time electric energy scheduling strategies of the electric charge business service subareas. According to the method, the problems of high cost investment, low efficiency, lack of information interaction, low practicability, poor intuition and poor data processing capability in the prior art are solved.

The invention discloses a real estate supervision method and system based on artificial intelligence. The method comprises the steps of data acquisition, data preprocessing, real estate data balancing, real estate property right risk assessment model construction and real estate supervision. The invention belongs to the technical field of real estate management, and particularly relates to a real estate supervision method and system based on artificial intelligence. According to an included angle between real estate data, favorable neighbors are screened out to construct a self-adaptive neighborhood set, similarity measurement is introduced to calculate the number of synthetic data, and the data are synthesized; detecting the quality based on the classification confidence of the synthetic data, and constructing a real estate data balance set according to the high-quality synthetic data; a dynamic frequency factor is designed to calculate a frequency adjustment loop learning rate, a dynamic cutting threshold is introduced to carry out gradient norm constraint, depth Q network parameters are updated, a real estate property right risk assessment model is constructed, the real-time requirement is met, and it is ensured that different types of real estates can be equally and effectively supervised.

The invention discloses a relay communication method and device, communication equipment and a readable storage medium, and belongs to the technical field of communication, and the relay communication method comprises the steps that a relay terminal receives or monitors a first relay discovery message; the first relay discovery message comprises at least one of the following items: a first hop count and first relay routing queue information, the first hop count is a relay hop count of a terminal which sends or broadcasts the first relay discovery message, and the first relay routing queue information comprises information of a relay terminal before the relay terminal; and executing a relay discovery process according to the first relay discovery message, or determining that the relay discovery process is not executed.

The invention discloses a walnut source DPP-IV inhibitory peptide as well as a preparation and screening method and application thereof. The walnut source DPP-IV inhibitory peptide comprises FPAG and / or LPSYQPTP, the preparation and screening method comprises the following steps: (1) adding walnut protein powder into deionized water, and fully dissolving to obtain a walnut protein solution; (2) adding hydrolyzed compound protease into the walnut protein solution for enzymolysis to obtain walnut protein hydrolysate freeze-dried powder; (3) re-suspending the walnut protein hydrolysate freeze-dried powder in deionized water, and performing ultrafiltration separation by using an ultrafiltration membrane with the molecular weight cutoff of 1kDa to obtain a component F1; step (4), performing peptide fragment sequence identification on the obtained F1 component through peptidomics; and step (5), screening from peptide fragment sequences obtained by identification through a bioinformatics technology. The walnut source DPP-IV inhibitory peptide screened by the invention can be used for preparing a medicine or food with a DPP-IV inhibition function, so that the problems that the existing walnut source DPP-IV inhibitor has many side effects and the like are solved.

The invention provides a security vulnerability detection system based on an API interface, and relates to the technical field of security vulnerability detection.The system firstly analyzes the API interface through an analysis module to obtain calling information, and then analyzes calling of the API interface through a static analysis module and a dynamic analysis module to obtain calling information; according to the method, a calling graph capable of representing calling relations among different APIs is generated, a detection queue is generated according to the calling graph, and test parameters of the APIs are generated according to the calling graph, so that the generation efficiency of the test parameters is improved, the security vulnerability detection efficiency is improved, and finally, the method calling when the APIs process the test parameters is analyzed, so that the security vulnerability detection efficiency is improved. The API interface with the recursive structure with vulnerability suspicion is marked as possible security vulnerabilities, so that the system can more efficiently and accurately help testers to find related types of security vulnerabilities in the API interface, and then can timely optimize the API interface to defend attacks against the vulnerabilities.

This invention discloses a blockchain address association analysis method based on graph database risk propagation, belonging to the field of blockchain association analysis technology. The invention includes attribute graph modeling, risk propagation analysis, and incremental risk mechanism updates. It is based on modeling blockchain transaction data as an attribute graph and storing it in a graph database. Then, using marked risk addresses as seed nodes, a multi-hop risk propagation algorithm with a decay factor propagates risk scores along transaction edges. Finally, combined with community detection and threshold truncation mechanisms, it outputs a set of associated risk addresses and their risk levels, achieving quantitative identification of hidden associated risk addresses. Simultaneously, it accurately and efficiently discovers organized abnormal networks and fund loops, enabling timely risk prediction and prevention, effectively controlling the propagation range, and meeting the real-time requirements of risk control and early warning scenarios.

The invention relates to a real-time detection method for a ground disaster hidden danger of an electric power infrastructure. The method comprises the following steps: S1, acquiring different types of monitoring data of a ground disaster monitoring area; independently constructing initial time sequence data of a univariate time sequence for any kind of monitoring data; s2, constructing a residual sequence according to a difference value between each data element and the average value of the front window; s3, solving two model parameters; s4, calculating latest upper and lower limit residual error thresholds by applying a second theoretical model of the extreme value theory so as to determine a normal value range; s5, calculating a residual value of the latest data; and S6, carrying out abnormity determination on the residual value. The data mode of each monitoring type is analyzed through unsupervised learning, the detection model is adjusted in real time with the self-adaptive capacity, the latest upper limit threshold value of the data can be adjusted along with the data fluctuation trend, and it is ensured that the method can adapt to various types of monitoring data.

The utility model provides a warning system for forbidding pedestrians to enter a highway. The warning system comprises a supporting seat, an infrared sensor, a rain shelter and a voice alarm, wherein baffles are arranged on three continuous sides of the supporting seat; the infrared sensor is arranged on a bottom plate of the supporting seat; the infrared sensor, the electromagnetic relay and the first voice alarm are connected with the distribution box through the air switch to obtain electric energy; warning words and expelling words for prohibiting pedestrians from entering are stored in the voice alarm, so that the warning words and the expelling words can be automatically played when the working power supply loop is switched on. The warning system is simple in structure, easy and convenient to assemble and capable of effectively finding pedestrians intending to enter the highway at any time and giving out a warning in time.

An exemplary system includes a processor to trim a machine learning model based on importance of neurons or weights. The processor is further configured to permutate and pack remaining neurons or weights of the trimmed machine learning model to reduce the amount of ciphertext computation under selected constraints.

This application provides a method, apparatus, electronic device, and storage medium for road cleanliness detection, relating to the field of road detection technology. The method includes: acquiring a road image to be detected; dividing the road image into multiple sub-regions according to a preset division method; statistically analyzing the pixel distribution of each sub-region to obtain multiple pixel histograms to be processed; acquiring multiple preset pixel histograms, each preset pixel histogram being obtained by statistically analyzing the pixels of the sub-regions in a clean state; calculating the similarity between each pixel histogram to be processed and the corresponding preset pixel histogram to obtain multiple similarities; using the similarity scores below a similarity threshold as target similarities, and using the sub-regions corresponding to the target similarities as target sub-regions; identifying the areas occupied by objects to be cleaned in each target sub-region, and determining the road cleanliness based on the areas occupied by objects to be cleaned in each target sub-region. This method can efficiently identify objects to be cleaned.

The invention relates to the technical field of computer aiding, and discloses a parallel rendering method and system for a molecular dynamics trajectory based on a supercomputing platform so as to improve the rendering efficiency. The method comprises the following steps: acquiring deployment of corresponding molecular dynamics visualization related components matched by a user aiming at a current supercomputing environment; the main node splits the big data track file by using Gromacs, generates sub-task track files related to task requirements, and distributes the sub-task track files to corresponding nodes; executing a non-interactive VMD task in parallel by each node which obtains the sub-task track file, calling a renderer to perform rendering operation, and storing a rendering result in a file folder corresponding to each node task in a shared memory in a tga file format; and the main node re-numbering the rendering subtask generation tga file, and then carrying out picture processing on the rendering tga through FFmpeg to generate an animation video file.

The invention belongs to the technical field of edge computing, and particularly relates to a software-defined edge computing network topology reconstruction method and system and a storage medium. The method mainly comprises the following steps: constructing an LLDP frame and an information binding table; calculating a backbone switch set; an LLDP message is constructed; constructing flow tables with high, medium and low priorities; the constructed flow table is installed in a corresponding switch; issuing the LLDP data packet to a backbone switch; the switch completes forwarding processing of the corresponding LLDP data packet; the network controller receives and analyzes the LLDP frame; and updating the link information table and the information binding table of the port. According to the method, the number of data packets in the network and the load of the controller are effectively reduced while the function of analyzing the link capacity and the connection relation between the nodes in the SD-ECN network topology reconstruction is ensured, effective compatibility with a native OFDP mode is provided, and the method has a good application prospect.

The present invention discloses a new word discovery method and device, and relates to the field of computer technology. A specific implementation of the method includes: performing word segmentation processing on a character string to be segmented based on a vocabulary; performing BIO annotation on the result after the word segmentation processing; performing unsupervised training using the result after the BIO annotation to obtain a named entity recognition model; using the named entity recognition model to predict the BIO annotation of the character string to be predicted; synthesizing words based on the BIO annotation of the character string to be predicted; comparing the synthesized words with the word segmentation processing results of the character string to be predicted to obtain new words. This implementation avoids the problem of large-scale labeling when obtaining training samples, and improves the accuracy of word segmentation processing and the efficiency of discovering new words based on the discovered new words.

The present invention discloses a test case generation method and device, the method comprising: obtaining a user interface screenshot of the software to be tested; using a pre-trained interface element recognition model to recognize the user interface screenshot, and obtaining each control in the user interface screenshot and related information of the control; generating an interface test case set according to each control in the user interface screenshot and related information. The present invention also discloses a method and device for automatically reproducing a problem scenario. By using the present invention, the efficiency of test case generation can be improved, and a comprehensive test of the user interface can be achieved.

This invention discloses an integrated monitoring method for virtual reality operation based on multi-dimensional data, belonging to the field of intelligent data management. It addresses the technical problems in existing intelligent teaching solutions, such as the limited means of monitoring and evaluating teachers' teaching, and the inability to provide dynamic prompts and adjustment suggestions, leading to poor overall effectiveness in virtual reality operation management. By implementing modular monitoring and analysis of different teaching knowledge points from the teacher's perspective, it not only obtains information on the teacher's different teaching states but also effectively improves the accuracy of monitoring and analysis of different teaching knowledge points. Furthermore, by integrating various data related to students' problem-solving for different teaching knowledge points to obtain a learning monitoring value, and using this value to comprehensively evaluate the teacher's teaching effectiveness from the students' perspective, it provides timely and efficient information on students' mastery of different teaching knowledge points.

The invention provides a business risk early warning method and device and a computer readable storage medium. The method comprises the following steps: acquiring employee basic information of a target employee and learning behavior information and learning result information of the target employee in a target business knowledge point type; inputting the employee basic information, the learning behavior information of the target employee in the target business knowledge point type and the learning result information into a trained extreme gradient boosting tree XGBOOST model to obtain a performance level prediction value of the target employee in the target business knowledge point type; and according to the performance level prediction value of the target employee in the target business knowledge point type, determining whether the target employee has a business risk. According to the method, the device and the computer readable storage medium, the problem that the business risk of employees caused by insufficient business knowledge learning cannot be timely and effectively found due to lack of a business knowledge learning-based business risk early warning method in the prior art can be solved.

The present invention discloses an automated UI interactive exploration method based on a multimodal large model, comprising the following steps: (1) collecting text, images, XML files and historical operation record information, analyzing the above information by the multimodal large model and generating a single-step exploration action, and realizing correct recognition, conversion and execution of the action through an execution system; (2) providing the multimodal large model with page information before and after the execution of the action and the current visual map, and the multimodal large model updates the visual map by extracting page features and identifying the relationship between pages; (3) using a page-level recursive exploration strategy to systematically construct a visual map of an application. By using the present invention, mobile applications can be automatically explored and visual maps can be constructed, thereby improving the accuracy and reliability of UI exploration.

The invention provides a picture processing method and device, equipment and a storage medium. The method comprises the steps that a to-be-processed picture sent by a user is acquired; determining a scene to which the to-be-processed picture belongs according to an environment generated by the to-be-processed picture, and extracting feature information of the to-be-processed picture by adopting a feature extraction method corresponding to the scene; a picture library is established for each scene, numbering and labeling operation is performed on new pictures entering the picture library, similarity calculation is performed on the new pictures and old pictures previously stored in the picture library after the numbering and labeling operation is completed on the new pictures entering the picture library, and the value of each identifier of the new pictures is adjusted based on a similarity calculation result; after the value of each identifier of the new picture is determined, checking the new picture according to the value of each identifier of the new picture to obtain a processing result; through the method, the identification capability of risk pictures in different scenes can be improved, the identification efficiency can be improved, and the manual auditing cost can be reduced.

The present disclosure relates to a 5G or pre-5G communication system to be provided for supporting a data transmission rate higher than that of a 4G communication system such as LTE. A method according to an embodiment of the present invention is a method for authenticating an electronic device that receives an edge computing service from an authentication server of a mobile communication system, wherein the method may include the following steps: performing a first authentication (403) of the electronic device through authentication and key agreement (AKA) with the electronic device, and, when the first authentication succeeds, providing first authentication information to the electronic device; and performing a second authentication (411) of an edge computing service for the electronic device, and, when the second authentication succeeds, providing the electronic device with second authentication information including an access token for authentication of the edge computing service.

The invention discloses a method and a system for supervising internet data processing, and relates to the technical field of internet supervising, the method comprises the steps of flow data capture, data doubt judgment, problem data coping and early warning prompt, real-time supervision is executed on each internet transmission data packet, each doubt data packet is captured, and each doubt data packet is sent to the internet supervising module; the method comprises the following steps: receiving doubt data packets, executing corresponding analysis and reduction on the doubt data packets, judging whether the doubt data packets are malicious data packets, extracting features corresponding to the malicious data packets, judging to obtain malicious types corresponding to the malicious data packets, and analyzing to obtain countermeasures of the malicious types corresponding to the malicious data packets. According to the method, the security of the Internet data in acquisition and transmission is guaranteed, the application security corresponding to the Internet data is reduced, and meanwhile, the data risk is quickly and efficiently found based on judgment on the malicious data packet corresponding to the Internet data, so that timely data security risk measure prevention is realized.

The invention discloses an associated risk hierarchical management and control and hidden danger troubleshooting and treatment method, which belongs to the field of dual prevention mechanisms, and comprises the following steps of: 1, forming a risk identification list by taking various places, equipment facilities and operation activities in the emergency industry as basic risk units; 2, obtaining previous disaster records of risk units of the same type through big data, and carrying out risk assessment on the risk units on the risk identification list according to the previous disaster records; 3, establishing a security monitoring identification list; step 4, generating a radar map based on the safety monitoring identification list, and constructing a hidden danger troubleshooting priority list based on the radar map; step 5, carrying out hidden danger investigation on the risk units according to the priority list; and 6, formulating accident potential treatment schemes and measures for the risk units with potential hazards. According to the invention, through deep association of risk grading management and control and hidden danger investigation and treatment, risk hidden dangers can be timely and effectively found and treated.