253 results about "Filtering rules" patented technology

The invention discloses a data filtering and noise reduction method based on laser point cloud. According to the method, the multi-scale features are intelligently screened through the random forest algorithm, and the system can automatically generate the optimal filtering rule according to the local geometric characteristics of the point cloud without depending on manual parameter presetting. In a complex urban scene, a fine structure of a high-rise vertical face can be accurately reserved through curvature features, and sparse noise of a vegetation area is rapidly eliminated through a density threshold value. The data-driven adaptive mechanism not only reduces the manual intervention cost, but also greatly improves the scene generalization ability of the filtering strategy, so that the filtering strategy can still keep stable output in a dynamic environment. The dynamic interference is accurately positioned by combining the consistency verification of the motion trails of the multi-frame point clouds and utilizing the time sequence correlation analysis, so that the data reliability in a complex dynamic scene is remarkably improved, and a solid foundation is provided for high-precision three-dimensional reconstruction and real-time perception.

The invention discloses a multi-path suppression positioning method and system for a banded sparse single Beidou CORS network, and relates to the technical field of satellite navigation positioning. According to the multi-path suppression positioning method for the banded sparse single Beidou CORS network, initial pseudo-range time sequence data are acquired, the time sequence data and regional state data are received, the pseudo-range data are corrected and analyzed, then, filtering processing is performed by using a preset filtering rule, a virtual base station is established, data fusion is performed, and the multi-path suppression positioning method for the banded sparse single Beidou CORS network is obtained. According to the method, the pseudo-range time sequence data of each satellite is dynamically corrected, and particularly, through comprehensive analysis of the reflecting surface information, the environment data and the signal arrival time difference, the accurate position information of the receiver is obtained. Errors caused by reflecting surface and environment changes can be recognized and corrected in real time, and the stability and precision of a positioning system in a complex environment are remarkably improved.

The present application provides a model segmentation method, a device and a storage medium. Segmentation parameters in different segmentation dimensions can be generated for a target model, and the generated segmentation parameters are filtered according to preset filtering rules, such that the remaining segmentation parameters in the segmentation dimensions are significantly reduced, and thus the number of segmentation strategies generated by means of combining the remaining segmentation parameters can also be significantly reduced. Candidate segmentation strategies that meet verification conditions are searched for among the segmentation strategies obtained by means of combination. After multi-level filtering operations, low-quality segmentation strategies can be rationally discarded, thereby making the number of retained candidate segmentation strategies more streamlined. The performance of the target model under each candidate segmentation strategy is evaluated, such that an appropriate target segmentation strategy can be finally determined to serve as the basis for distributed deployment of the target model.

The invention belongs to the technical field of natural language processing and knowledge engineering, and discloses a method, a system, equipment and a medium for automatically constructing a multi-field scientific knowledge base, and the method comprises the following steps: based on an input identifier list or a field search word, retrieving a full text of a literature, analyzing and converting the full text into a structured text; combining a pre-configured large language model with a field cue word, extracting key information in the structured text, and outputting structured data; the automatic script filters irrelevant, repeated or incomplete structured data according to a pre-configured filtering rule; performing standardization processing on the filtered structured data so as to realize the consistency and comparability of the data; and inserting the standardized structured data into an interactive knowledge base or database, establishing data association, and verifying association logic. The method supports cross-field rapid adaptation, solves the problems of low efficiency and high error rate of a traditional method, and can be widely applied to the fields of biomedicine, material science, synthetic biology and the like.

The invention belongs to the field of data processing, and discloses a real-time data processing system and method for the Internet of Things. Comprising a long-tail device, data of a long-tail device end is transmitted to an edge layer through a communication protocol, an edge gateway in the edge layer is used for receiving the data, the edge layer further comprises a data filter, and the data filter discards useless data based on a filtering rule and retains value data; performing normal data and potential anomaly marking on the data based on a filtering rule, and finally outputting high-value data through an anomaly confirmation mechanism; the event detector performs anomaly detection on the value data through a model rule, if the data is abnormal, the data is divided into a high-priority queue, otherwise, the data is a low-priority queue, the high-priority data is transmitted to the cloud for application preferentially, and the low-priority data is subjected to settlement processing; and the cloud is used for receiving the high-priority data and triggering an alarm notification, thereby realizing high-efficiency and high-quality processing of real-time data oriented to the Internet of Things.

The invention provides a retrieval method and device based on graph structure retrieval enhancement, electronic equipment and a storage medium, and the method comprises the steps: obtaining original data, screening the original data based on a preset screening rule to obtain a plurality of candidate phrases, calculating the similarity between the plurality of candidate phrases and a preset central semantic vector of each layer, the multiple candidate phrases are layered according to the similarity, feature vectors are constructed, levels and feature vectors corresponding to the multiple candidate phrases are obtained, graph entities are obtained based on the candidate phrases, context fragments of the graph entities in original data are extracted, and relation types between the graph entities are obtained based on the context fragments; according to the relationship type between the graph entities and the hierarchy of the graph entities, a multi-hierarchy knowledge graph is obtained, and retrieval is performed based on the multi-hierarchy knowledge graph and the corresponding associated information block, so that the technical problems of result redundancy and logic fracture of a retrieval enhancement generation method are solved through the method.

The embodiment of the invention provides a model segmentation method and device and a storage medium. According to the embodiment of the invention, the segmentation parameters under different segmentation dimensions can be generated for the target model, and the generated segmentation parameters are filtered according to the preset filtering rule, so that the residual segmentation parameters under each segmentation dimension are obviously reduced, and the number of segmentation strategies generated by mutual combination is also obviously reduced. In addition, candidate segmentation strategies conforming to verification conditions are searched from the combined segmentation strategies. Therefore, through multi-level filtering operation, low-quality segmentation strategies can be abandoned reasonably, so that the number of the reserved candidate segmentation strategies is more simplified. Performance evaluation is carried out on the target model under each candidate segmentation strategy, and an appropriate target segmentation strategy can be finally determined. Therefore, the appropriate target segmentation strategy can be efficiently determined for the target model, the appropriate target segmentation strategy is used as a basis for distributed deployment of the target model, manual experience does not need to be relied on any more, and therefore the model segmentation effect can be effectively improved.

The invention discloses an unpowered device binding and positioning method and system based on the passive Internet of Things, and the method comprises the steps: receiving device identification information broadcasted by a plurality of passive tags through a positioning gateway installed on a tractor, and enabling the passive tags to be fixed to a dragged unpowered device; processing the equipment identification information based on a preset electromagnetic signal filtering rule, and generating a bound equipment list; generating a marshalling sequence list according to the signal intensity data of each passive tag in the binding equipment list; acquiring real-time position data of the tractor, wherein the real-time position data comprises latitude and longitude and azimuth angles; according to the marshalling sequence list, pre-stored equipment physical length data and the real-time position data, absolute position coordinates of all the unpowered equipment are solved through a space relation model. The technical problems of poor safety, high cost and insufficient marshalling positioning precision caused by dependence on battery power supply in the prior art are solved.

The invention relates to a message processing method and device, an electronic device and a storage medium. The method comprises the following steps: in response to a to-be-processed source message, acquiring analysis rule configuration information corresponding to the source message through a rule real-time monitor so as to analyze and convert the source message into a first intermediate message of a memory object structure; obtaining a message filtering rule corresponding to each message theme from the rule offline file through a rule real-time monitor so as to filter the first intermediate message to obtain a second intermediate message matched with each message theme; obtaining generation rule configuration information configured under each message theme and a target theme subscribed by a target receiving end; and performing message format conversion processing on the second intermediate message matched with the corresponding message theme by using the generation rule configuration information to obtain a target message, and forwarding the target message matched with the target theme to a target receiving end. On the premise of not invading logic of a generator end and a consumer end, messages can be filtered and forwarded universally and flexibly.

A traffic filtering method includes a network edge node that provides a cloud service that receives target traffic; obtains a filtering rule, where the filtering rule is for filtering, based on a filtering action, target traffic that meets a filtering condition; invokes a rule engine to parse and execute the filtering rule, where the rule engine is deployed in the network edge node or in a network edge processing system connected to the network edge node; and obtains filtered target traffic based on an execution result, where the filtered target traffic is traffic that meets a filtering requirement corresponding to the filtering rule. The target traffic filtered according to the filtering rule includes at least one of traffic sent by a network side to a user terminal and traffic sent by the user terminal to the network side.

This disclosure relates to data association, attribution, annotation, and interpretation systems and related methods of efficiently organizing heterogeneous data at a massive scale. Incoming data is received and extracted for identifying information (“information”). Multiple dimensionality reducing functions are applied to the information, and based on the function results, the information are grouped into sets of similar information. Filtering rules are applied to the sets to exclude non-matching information in the sets. The sets are then merged into groups of information based on whether the sets contain at least one common information. A common link may be associated with information in a group. If the incoming data includes the identifying information associated with to the common link, the incoming data is assigned the common link. In some embodiments, incoming data are not altered but assigned into domains.

According to the intelligent terminal equipment intelligent adaptation method and device, intelligent terminal automatic discovery is carried out based on scene-based adaptive ARP scanning and multi-fingerprint UPnP filtering, access equipment is obtained, automatic and precise discovery of intelligent terminal equipment is achieved, and the intelligent terminal equipment can be automatically and accurately found by standardizing the scanning frequency and the filtering rule. The equipment discovery efficiency and accuracy are improved, the access equipment is subjected to prefabricated API library matching and AI reverse analysis to obtain interface information of the access equipment, automatic analysis of a standard interface and a private interface is realized based on a multi-dimensional analysis technology of an AI large language model, and the equipment discovery efficiency and accuracy are improved by utilizing the AI large language model and combining a built-in multi-language programming template. According to the method, the adaptive code matched with the interface information is automatically compiled, the adaptive code is automatically generated based on the AI technology, the compatibility of multi-protocol and multi-interface type equipment is supported, and finally the core problems of low efficiency, poor compatibility, difficult maintenance and high threshold in the existing intelligent terminal adaptation process are solved.

The invention relates to a data packet filtering method and device. The method comprises the following steps: extracting dimension information of a data packet, wherein the dimension information comprises at least one of a source IP address, a destination IP address, a source port, a destination port and a protocol type; sending the data packet to a corresponding virtual system; the virtual system matches the dimension information of the data packet with a pre-configured strategy template; when the matching is successful, filtering the data packet according to a filtering rule corresponding to the strategy template; and when the matching is unsuccessful, filtering the data packet through a strategy tree. According to the data packet filtering method and device, the packet filtering strategy analysis and matching efficiency can be improved, and the network attack protection efficiency of packet filtering is improved.

The invention discloses a network high-speed traffic acquisition method, system and device based on a clouded environment, and relates to the technical field of network communication. According to the invention, a clouded environment is created; a two-stage clouded environment capacity expansion and contraction strategy is constructed by using an optimized FCN network high-speed flow prediction model and a real-time load index, and pre-allocation and accurate adjustment of resources are realized; the optimal solution of the model learning rate is dynamically searched by introducing an optimization algorithm, the session continuity is guaranteed by adopting a consistent Hash algorithm, and the load balance degree and the processing throughput are improved in combination with a three-level dynamic filtering rule and a lightweight DPI (Deep Packet Inspection) technology; due to an annular buffer management strategy and a Kafka message queue synchronization mechanism, the key data loss rate and the data synchronization delay are reduced, and the requirements of real-time analysis and long-term storage in a high-speed network scene are met; according to the method, the problem of insufficient resource elasticity of a clouded environment is effectively solved, the resource supply response speed is improved, and the cost and the prediction error rate are reduced.

The invention provides a data packet real-time filtering method and device for a vehicle-mounted host firewall, and relates to the technical field of vehicle-mounted host firewall application, and the method comprises the steps: receiving a preset rule set sent by an upper computer; monitoring the current vehicle state in real time, determining a first filtering rule of the current network traffic data packet from a preset rule set based on the first vehicle state of the current vehicle, and analyzing and filtering each protocol layer data of the current network traffic data packet; if the current vehicle is switched from the first vehicle state to a second vehicle state, determining an application layer data filtering rule and / or a transmission layer data filtering rule corresponding to the second vehicle state from a preset rule set, and updating the first filtering rule to generate a second filtering rule, and analyzing and filtering each protocol layer data of the current network flow data packet based on the second filtering rule. The technical problem that a vehicle-mounted host firewall in the prior art cannot enable the filtered data packet to accurately meet the requirements of a complex vehicle application scene is solved.

A source content processor receives content from a crawler and calls a text mining engine. The text mining engine mines the content and provides metadata about the content. The source content processor applies a source content filtering rule to the content utilizing the metadata from the text mining engine. The source content filtering rule is previously built based on at least one of a named entity, a category, or a sentiment. The source content processor determines whether to persist the content according to a result from applying the source content filtering rule to the content and either stores the content in a data store or deletes the contents from the data ingestion pipeline such that the content is not persisted anywhere. Embodiments disclosed herein can significantly reduce the amount of irrelevant content through the data ingestion pipeline, prior to data persistence.

The invention relates to the technical field of signal processing, and provides a multi-frequency bio-electricity signal anti-interference method and device, equipment and a storage medium. The multi-frequency bio-electricity signal anti-interference method comprises the steps that multi-frequency-band bio-electricity signals of multiple channels are synchronously collected; based on a time-frequency analysis rule, performing frequency domain decomposition on the multi-band bio-electricity signal of each channel, and extracting an interference frequency component; according to the identified interference frequency component, denoising the main frequency band signal of each channel by using a collaborative adaptive filtering rule, and dynamically adjusting a filtering parameter based on a reference characteristic of a non-interference signal in an auxiliary frequency band; and performing multi-scale fusion on the features of the filtered main frequency band signal and the features reserved in the auxiliary frequency band, and performing recovery through a weighted reconstruction rule to obtain a target bio-electricity signal. The invention aims to improve the reliability and stability of the multi-frequency bio-electricity signal.

Provided are a data filtering method and apparatus for a generative artificial intelligence model, a device, and a medium. The method comprises: determining a time point for filtering data of a generative artificial intelligence model; when the time point is reached, constructing a first knowledge graph on the basis of the data; querying the first knowledge graph in a second knowledge graph, wherein the second knowledge graph comprises a third knowledge graph constructed on the basis of valid data and a fourth knowledge graph constructed on the basis of invalid data; and filtering the data on the basis of the query result and a filtering rule, wherein the filtering rule is related to the third knowledge graph and / or the fourth knowledge graph. On the basis of knowledge graphs, data of a generative artificial intelligence model can be accurately filtered. In addition, the data is filtered in pre-training and model fine-tuning stages, preventing in advance the model from generating invalid data. The data is filtered in a model output stage, improving the security of the data.

The embodiment of the invention provides an unknown cross-site script security detection method and device generated based on a test script, and intelligent construction of the test script is realized through innovatively constructing a script generation mechanism driven by a Markov chain and through atomic element sequence analysis and a random walk strategy. And designing a DOM tree difference-based filtering analysis mechanism, and establishing a filtering rule identification strategy in combination with multi-dimensional mark extraction and node positioning. And a matrix iterative optimization mechanism is introduced, and self-adaptive optimization of the test script is realized through dynamic updating and convergence calculation of a state transition matrix. According to the method, the defects of the traditional technology in the aspects of script generation, filtering analysis, optimization adjustment and the like are effectively overcome, and the unknown cross-site script detection effect is remarkably improved.

The invention discloses a data processing method and device, electronic equipment and a medium, and relates to the technical field of data processing. The method comprises the following steps: acquiring vehicle data, and loading a data filtering rule in a database to a cache; under the condition that it is determined that the data filtering rules in the database are updated, a weight coefficient corresponding to each updated data filtering rule is determined based on a preset configuration file, and the preset configuration file comprises a plurality of data filtering rules and the weight coefficient corresponding to each data filtering rule; determining a target weight coefficient based on the weight coefficient corresponding to each updated data filtering rule; and updating a data filtering rule in the cache based on the target weight coefficient, and carrying out data filtering operation on the vehicle data according to the data filtering rule in the cache. Therefore, the reading and writing times of the database can be remarkably reduced, the consistency of the cache data and the database data can be effectively kept, data processing delay and message blocking are avoided to a certain extent, and the stability of a service system is improved.

The invention discloses a file system event processing method and device based on an intelligent filtering rule, and the method comprises the steps: obtaining a file system original event of a monitoring directory, carrying out the cross-platform standardization processing, and extracting event feature vectors of four dimensions: time, a file, a process and a path; the method comprises the following steps: constructing a rule base containing software operation modes such as an editor, a compiler and a version control tool, performing mode matching on an event sequence, calculating confidence, determining a filtering strategy type based on a matching result, executing corresponding processing, and dynamically optimizing system parameters through statistical analysis. The technical problems that an existing file monitoring system is serious in event redundancy and frequent in false triggering are solved, effective file operation and temporary intermediate operation can be intelligently distinguished, invalid synchronous triggering is greatly reduced, the accuracy is improved to 95% or above from 60-70% of a traditional scheme, and invalid event processing is reduced by 90% or above.

The invention relates to a 5G signaling plane traffic screening method based on a multi-core processing unit, and the method comprises the steps: receiving network mirror image traffic through a physical interface unit, and screening out transmission control protocol traffic; the switching chip unit identifies HTTP / 2 protocol traffic from transmission control protocol traffic according to a target port number or an application layer protocol handshake feature, and forwards the HTTP / 2 protocol traffic to the multi-core processing unit; the binary framing structure of the HTTP / 2 protocol is analyzed, a data frame and a control frame are distinguished, and an HTTP request head is restored; analyzing and decoding an HTTP request header, and extracting a pseudo header field of a uniform resource identifier path in the HTTP request header; generating a traffic filtering rule corresponding to the service signaling traffic bearing the specific network function; and issuing the generated flow filtering rule to a switching chip unit, and outputting specified 5G signaling plane flow. The method automatically adapts to the dynamic change of the 5G network element, and effectively solves the problem of traffic loss or inaccuracy caused by difficult maintenance and untimely updating of the static work parameter data.

A packet-filtering system configured to filter packets in accordance with packet-filtering rules may receive data indicating network-threat indicators and may configure the packet-filtering rules to cause the packet-filtering system to identify packets comprising unencrypted data, and packets comprising encrypted data. A portion of the unencrypted data may correspond to one or more of the network-threat indicators, and the packet-filtering rules may be configured to cause the packet-filtering system to determine, based on the portion of the unencrypted data, that the packets comprising encrypted data correspond to the one or more network-threat indicators.

This application provides a traffic scheduling method, apparatus, and electronic device, relating to the field of communication technology. The method includes: when a target channel group determined from a shaping group and a non-shaping group is a shaping group, determining a first target channel from the shaping group based on a filtering rule that uses the channel corresponding to the highest credit value as the target channel, and determining whether it meets preset shaping conditions; if it does, scheduling the traffic of the first target channel, adjusting the credit values ​​of the first target channel and other first channels according to a preset credit value adjustment rule, and continuing to schedule the shaping group; if all channels in the shaping group have been scheduled at least once or the preset shaping conditions are not met, re-determining the target channel group. The non-shaping group is scheduled using a round-robin scheduling method. This can alleviate the problem of uneven traffic distribution among channels with traffic shaping enabled when some channels have traffic shaping enabled and others do not.

The invention relates to a method and a device for identifying multi-class dispersed phases in a multiphase flow system, which relate to the technical field of multiphase flow dispersed phase image processing, and adopt a plurality of independent and special deep learning detection models to carry out parallel detection on the same frame of image; based on the physical priori knowledge of each target, asymmetric filtering rules (different confidence thresholds, sizes and length-width ratio constraints) customized for each model are applied to the initial output of each model; meanwhile, a conflict arbitration mechanism based on the space overlapping degree and the preset category priority is introduced, and the overlapping targets recognized in a cross-model mode are precisely judged so as to eliminate recognition ambiguity, that is, the technical route of'special model detection, asymmetric screening and conflict arbitration 'is adopted, and therefore the recognition accuracy of the overlapping targets is improved. And the accuracy, the reliability and the result uniqueness of online detection of multiple types of dispersed phases in a complex multiphase flow system are remarkably improved.

This disclosure relates to systems and methods for efficiently organizing data association, attributes, annotation, and interpretation of large-scale heterogeneous data. Incoming data is received and identification information (“information”) is extracted. A multi-dimensional reduction function is applied to the information, and the information is grouped into sets of similar information based on the function results. Filtering rules are applied to the sets to exclude mismatched information. The sets are then merged into information groups based on whether they contain at least one common piece of information. Common links can be associated with information within a group. If the incoming data includes identification information associated with a common link, the incoming data is assigned a common link. In some embodiments, the incoming data is not modified but assigned to a domain.

A method for obtaining characteristic peaks of compounds, wherein one or more characteristic peaks of compounds are obtained from a mass spectrometry file based on a parameter table. The parameter table records a filter parameter set for each compound, and the selection of characteristic peaks for each compound is determined by the filtering rules defined by its own filter parameter set. Another method for obtaining characteristic peaks of compounds is based on the positions of the characteristic peaks obtained from the mass spectrometry file, from which one or more characteristic peaks of compounds are obtained from another mass spectrometry file.

A threat intelligence gateway (TIG) may protect TCP / IP networks from network (e.g., Internet) threats by enforcing certain policies on in-transit packets that are crossing network boundaries. The policies may be composed of packet filtering rules with packet-matching criteria derived from cyber threat intelligence (CTI) associated with Internet threats. These CTI-derived packet-filtering rules may be created offline by policy creation and management servers, which may distribute the policies to subscribing TIGs that subsequently enforce the policies on in-transit packets. Each packet filtering rule may specify a disposition that may be applied to a matching in-transit packet, such as deny / block / drop the in-transit packet or pass / allow / forward the in-transit packet, and also may specify directives that may be applied to a matching in-transit packet, such as log, capture, spoof-tcp-rst, etc. Often, however, the selection of a rule's disposition and directives that best protect the associated network may not be optimally determined before a matching in-transit packet is observed by the associated TIG. In such cases, threat context information that may only be available (e.g., computable) at in-transit packet observation and / or filtering time, such as current time-of-day, current TIG / network location, current TIG / network administrator, the in-transit packet being determined to be part of an active attack on the network, etc., may be helpful to determine the disposition and directives that may best protect the network from the threat associated with the in-transit packet. The present disclosure describes examples of methods, systems, and apparatuses that may be used for efficiently determining (e.g., accessing and / or computing), in response to the in-transit packet, threat context information associated with an in-transit packet. The threat context information may be used to efficiently determine the disposition and / or one or more directives to apply to the in-transit packet. This may result in dispositions and / or directives being applied to in-transit packets that better protect the network as compared with solely using dispositions and directives that were predetermined prior to receiving the in-transit packet.

The present application relates to a network device information delivery method, a terminal, and a communication system. The method comprises: in response to a terminal being in a dual-connectivity state of being connected to a first network device and a second network device at the same time, using a dual-connectivity communication delivery policy to transmit acquired collaborative information of the first network device to the second network device, or transmit acquired collaborative information of the second network device to the first network device, wherein the dual-connectivity communication delivery policy is used for indicating a trigger rule or a filtering rule for delivering collaborative information.

The invention is suitable for the technical field of substation automation of a power system, and provides a multi-protocol-based data processing method, terminal equipment and a storage medium, and the method comprises the steps: obtaining first message data which is a communication instruction sent to target equipment by a remote control system; filtering out second message data from the first message data according to a preset filtering rule; wherein the second message data is message data, in which the first message data contains a first control instruction, and the first control instruction is used for indicating the target equipment to execute an operation action; and carrying out blocking processing on the second message. According to the method, the control instruction sent by the remote control system can be blocked, and the remote control authority of the operation interval equipment is automatically locked locally, so that the working efficiency is effectively improved, and the safety risk is reduced.