257 results about "Sequence matching" patented technology

The invention discloses a data security dynamic evaluation system and a protection method, belongs to the technical field of information security, and is used for solving the problem of terminal equipment access control and behavior risk dynamic collaborative protection. The method comprises the following steps: generating fingerprints through terminal equipment features, verifying authorization, inputting access feature slices into a time sequence model by authorized terminal equipment, generating a trust score based on cosine similarity of a behavior sequence and a prediction sequence, and constructing a Markov model to dynamically select an authentication mode according to the trust score; calculating a risk index by combining network and geographic information, and distributing the risk index to a real or virtual environment; and the unauthorized terminal equipment distributes the virtual environment after registration. Differentiated monitoring is carried out, a time sequence library is established in the virtual environment, and doubt scores are generated through sequence matching; the state deviation of the real environment is calculated through a hidden Markov model, and the risk score is generated by fusing the multi-dimensional features. And based on the result management authority, the suspicion terminal equipment isolates and shrinks the authority, the compliance terminal equipment authenticates and migrates, and the access is regulated and controlled according to the minimum privilege principle and the time window mechanism.

The invention provides a network attack detection method and system based on a distributed intelligent probe, and the method comprises the steps: receiving real-time flow data synchronously collected by the distributed intelligent probe at each node of a network, carrying out the inter-node interaction relation modeling processing of the real-time flow data, recognizing a flow communication mode between different network nodes, and carrying out the detection of the network attack. Generating a flow association map containing the node connection relationship and the communication frequency; carrying out abnormal communication path mining based on the flow association map, and extracting a node communication sequence with an abnormal mode by analyzing the deviation degree of a node connection relationship and the fluctuation characteristics of communication frequency; performing pattern matching processing on the node communication sequence and an attack behavior template in a preset attack feature library, calculating sequence matching similarity and generating an attack matching degree score set; and determining a network attack type and attack source node positioning information, and generating a network attack detection result. According to the invention, the practicability and effectiveness of network attack detection are improved.

A computing system, for automated generation of instructional text for driver safety, executes steps including: 1) accessing predefined datasets of telematic alerts, of predefined alert sequences, and of sequence categories; 2) acquiring one or more alert vectors during driving, each alert associated with a time of occurrence; 3) scanning each of the one or more alert vectors, over multiple time windows, to identify a set of alert sequence occurrences matching alert sequences in the sequence dataset and conforming to predefined time windows; 4) according to the severity of each alert sequence in the identified set of alert sequences, increasing by a proportional amount a priority score of a corresponding sequence category, to generate an aggregate priority score for each sequence category; and 5) providing instructional text associated with said sequential category from a text dataset to the driver.

The invention relates to the field of photovoltaic power prediction, in particular to a photovoltaic power accurate prediction method considering fusion of global information and local information. The method comprises the following steps: (1) establishing a bidirectional stacked long-short-term memory model based on time pattern attention as a global branch, processing all input sequences and capturing long-term dependency of time sequences; (2) establishing an improved Transform model based on similar time sequence matching as a local branch by considering the utilization of historical similar information by a photovoltaic power prediction model, and processing a dependency relationship between a local input sequence capture prediction period and a nearby time node; and (3) establishing a hybrid prediction model of a double-branch architecture based on the long and short term memory network and Transform, designing two independent branches to respectively extract global information and local information, and integrating the two types of information through a special decoder module. Through example analysis, it is verified that the model provided by the invention can realize accurate prediction of photovoltaic power.

The invention relates to an unmanned aerial vehicle detection method and system based on pilot frequency synchronization sequence matching, and belongs to the technical field of unmanned aerial vehicle detection. Receiving a to-be-detected signal, and intercepting a signal segment of which the length is a preset point number from the to-be-detected signal; performing fast Fourier transform on the signal segment to obtain frequency domain representation of the to-be-detected signal; performing fast Fourier transform on the general reference sequence according to a preset point number to obtain a frequency domain general reference sequence; performing conjugate operation on the frequency domain general reference sequence to obtain a frequency domain reference signal; performing convolution operation on the frequency domain representation of the signal to be detected and the frequency domain reference signal to obtain a frequency domain convolution result; and performing constant false alarm rate detection on the frequency domain convolution result to obtain an unmanned aerial vehicle detection result. According to the invention, the requirement of rapid and efficient detection of the unmanned aerial vehicle in a complex signal environment can be met.

The invention relates to the technical field of occupational simulation training evaluation, and discloses a system for college student occupational scene simulation training evaluation. The system comprises a task analysis unit, a dynamic behavior modeling unit, a multi-mode interaction management unit, a state evolution tracking unit, a strategy adaptation unit and a comprehensive evaluation generation unit. The system receives the initial scene description and generates a structured task framework, and behavior parameters are configured for student roles; constructing a multi-modal interaction atlas by fusing aligned voice, action and sight line data in real time; identifying a key decision node, and dynamically tracking a team state evolution path; matching and adjusting strategies in a behavior rule base according to the evolution sequence, and outputting an adaptive intervention scheme; and finally generating a multi-dimensional structured evaluation report. According to the system, deep insight and dynamic and objective intelligent evaluation of complex interaction behaviors in the simulation training process are realized.

The invention relates to the technical field of traffic event identification, and discloses an abnormal traffic event identification method and system based on a traffic large model, and the method comprises the steps: obtaining a traffic data flow, extracting an abnormal feature vector, and obtaining an abnormal signal candidate set; grouping the candidate sets and calculating a deviation degree, and if the deviation degree exceeds a threshold value, taking the deviation degree as a risk signal to form an input subset; environment variables are extracted from the subsets, a mapping relation is established, and anomaly recognition embedding representation is obtained; classifying the embedded representation, judging a congestion precursor and generating an early warning signal to obtain an early warning signal sequence; matching the sequence to obtain an abnormal event chain; if the integrity is higher than a threshold value, analyzing the type to obtain an abnormal event type; extracting a correlation feature vector from the type, pushing the correlation feature vector to a traffic management platform to obtain an instruction, and obtaining an emergency response trigger instruction sequence; and executing the instruction sequence to extract a feedback data stream, inputting the traffic large model to judge the accuracy rate, and if the judgment accuracy rate is met, determining an optimized anomaly recognition framework. The method can solve the problem of insufficient early warning capability.

The invention relates to the technical field of power system protection, in particular to a high-temporal-spatial-resolution power carbon emission factor calculation method and system and a readable storage medium. The method comprises the following steps: extracting entities and relationships from an electricity-carbon document to form an electricity-carbon triple, designing an electricity-carbon table data extraction method based on a regular expression for an electricity-carbon table, and constructing an electricity-carbon knowledge graph according to the obtained entities, relationships and attributes; then regarding a given question and an answer corresponding to the question as a sequence, designing an electric power carbon emission data retrieval method by combining distance measurement query based on a sequence matching idea and a bidirectional attention mechanism, and realizing discovery of a target electric power carbon entity and an electric power carbon attribute from an electric power carbon field knowledge graph; further generating a corresponding calculation graph, and according to the topological sorting of the calculation graph, calling related formulas in an electric carbon formula library to complete calculation, so as to obtain a regional direct carbon emission factor; and finally, according to an electric power calling-in relation in the electricity-carbon knowledge graph, performing correction on the basis of the regional direct carbon emission factor to obtain a regional average carbon emission factor considering electric power calling-in. The invention aims to solve the problem of how to improve the accuracy of power carbon emission factors.

Compressing files is disclosed. An input file to be compressed is first aligned. Aligning the file includes splitting the file into sequences that can be aligned. When splitting the file into sequences or when performing subsequent recursive splitting, the splitting is based on a longest sequence match. The result is a compression matrix, where each row of the matrix corresponds to part of the file. A consensus sequence is determined from the compression matrix. Using the consensus sequence, pointer pairs are generated. Each pointer pair identifies a subsequence of the consensus matrix. The compressed file includes the pointer pairs and the consensus sequence.

The invention discloses a large model and sequence matching-based battery health state evaluation method and system. The method comprises the following steps of: classifying battery health states according to a numerical range; extracting a charging sequence in a general form from the test battery monomers, and defining the charging sequence as a current sequence; the method comprises the following steps: extracting charging sequences with different median thresholds in a general form from known single batteries, and defining the charging sequences as candidate sequences; performing sequence matching on the current sequence and each candidate sequence; performing fine tuning on the large language model by adopting a matching sequence with a tag; and acquiring actual charging data of the to-be-tested single battery, extracting a charging sequence in a general form as a current sequence, performing sequence matching on the current sequence and each candidate sequence, and obtaining an evaluation category of the health state of the battery by using a fine-tuned large language model. According to the method, the numerical range of the health state of the battery is used as a state evaluation result, and the problem that the confidence coefficient of the method is reduced due to outlier estimation values in a traditional estimation method is solved.

The invention relates to the technical field of cloud computing monitoring, in particular to a water consumption monitoring system based on a cloud platform, which comprises a data trend identification module, a water consumption transmission scheduling judgment module, a water consumption interval reconstruction module, a user behavior identification module and a scheduling feedback correction module. According to the method, by introducing a sequence matching strategy of a timestamp and a flow value, the recognition precision of continuous flow change is improved, terminal grouping and amplitude consistency screening are combined, the trend sequence stability is enhanced, short-time fluctuation interference is reduced, extreme value positioning and state segmentation processing are utilized, and multi-level sensing of water volume change is achieved; flow map features are enriched, the time sequence and behavior start-stop information are fused to identify the offset state, the response ability to water consumption mode changes is improved, a dynamic allocation mechanism is constructed through response codes and transmission features, channel resource allocation is optimized, and the data processing and resource response efficiency of the system in an abnormal state is improved.

The invention discloses a VR / AR martial art teaching method, device and equipment based on dynamic time warping and a computer readable storage medium. The method comprises the steps of obtaining a user skeleton point sequence corresponding to a user action and a standard action template; determining a specific weight coefficient of the joint for comparison processing; comparing the user skeleton point sequence with a standard action template based on a specific weight coefficient of a joint by applying a weighted dynamic time warping algorithm so as to generate an optimal warping path; obtaining a sequence matching score and a posture matching score according to the optimal regular path and the key force generation event sequence; inputting the sequence matching score, the posture matching score and the determined existing force application sequence error and / or action posture error into a language generation type model to generate a text feedback instruction; and based on the text feedback instruction, generating and displaying immersive teaching feedback in a VR or AR environment. The method has the advantages of multi-dimensional evaluation, immersive feedback and the like.

The invention discloses a network traffic prediction method based on periodic decomposition and similarity matching, and relates to the technical field of time sequence prediction, and the method comprises the steps: S1, collecting network traffic historical data; s2, extracting a time period from the network traffic historical data sequence through fast Fourier transform, and segmenting the network traffic historical data sequence into a plurality of periodic subsequences and a to-be-predicted sequence; s3, clustering all the periodic subsequences based on the dynamic time stretching distance to obtain a median subsequence capable of representing each class of features; s4, matching a median sequence with the highest similarity with the to-be-predicted sequence as a reference median sequence; and S5, based on the reference median subsequence, predicting the residual sequence value of the to-be-predicted sequence by using an energy amplitude ratio method. According to the method, subsequence matching is carried out by utilizing the periodicity and similarity of the network traffic, the data change in a short period can be accurately predicted, a complicated parameter selection process is not needed, and thus the prediction efficiency of the network traffic is improved.

The invention discloses a single-photon laser ranging method based on laser pulse frequency modulation deblurring, and belongs to the field of laser ranging. In the ranging process, two different pulse frequency references are firstly set to correspond to two coding code elements respectively, n-bit random codes are generated according to n-time non-fuzzy distance expansion requirements, it is guaranteed that the n-bit random codes do not have displacement symmetry, then a laser source is made to repeatedly emit corresponding pulse signals according to a sequence represented by the random codes, then echo signal sequences are received, and the pulse frequency references correspond to the two coding code elements respectively. And performing cross-correlation operation on the single photon accumulation histogram and a pulse sequence represented by a known random code to obtain an operation result, determining one of the single photon accumulation histograms with the maximum amplitude, and calculating a histogram time position corresponding to the result, namely, calculating a distance measurement result of de-blurring. According to the method, the problem of range ambiguity of pulse radar ranging can be solved, the time sliding sequence matching method proposed in cross-correlation operation has the advantages of being efficient and flexible, and the time complexity of cross-correlation operation is effectively reduced.

The invention provides a control method and a control device of an underwater robot. The control method of the underwater robot comprises the following steps: establishing an underwater robot system model; performing obstacle avoidance path planning by using a sampling algorithm to obtain a discrete geometric path point set connecting the starting point and the ending point; a full-state reference sequence matched with the control method underwater robot system model is generated based on the control method discrete geometric path point set; constructing a cost function for trajectory optimization based on the control method underwater robot system model and the control method full-state reference sequence; generating an initial control sequence and an initial state sequence according to the deviation between the current state of the underwater robot in the control method and the full-state reference sequence in the control method; and performing iterative optimization by taking the control method cost function as an optimization target and taking the initial control sequence and the initial state sequence of the control method as hot start initial values to obtain a control instruction sequence of the underwater robot of the control method.

The invention relates to the technical field of heterogeneous computing power allocation, in particular to a heterogeneous computing power dynamic allocation method based on big data analysis, which comprises the following steps: analyzing a source, a target, a type and dependency of a data task, normalizing parameters and extracting features, identifying a key task, combining a computing power resource queue and historical scheduling efficiency, optimizing an allocation state, and allocating the heterogeneous computing power according to the allocation state. And screening the computing power resources which run normally, analyzing the dominant frequency temperature and response performance, adjusting the distribution relation, and forming a dynamic distribution sequence. According to the method, standardization, normalized mapping and feature aggregation are carried out on the data task multi-dimensional labels, deep mining and classification of task features can be achieved, dynamic linkage of task requirements and computing power resource states is completed according to big data analysis, relevance between the tasks and heterogeneous computing power resources is finely quantified, and the method has the advantages of being simple in structure, convenient to operate and high in efficiency. And in combination with a resource response expression and grading mechanism, a task allocation strategy is automatically adjusted, and the resource adaptation degree and allocation sequence matching during task processing are guaranteed.

The invention provides a memory parking repositioning method and device, electronic equipment and a storage medium, and in the method, a continuous path is decomposed into a plurality of topological path segments, so that a complex continuous space positioning problem is converted into a discrete path segment sequence matching problem, and the positioning accuracy is improved. Complexity and calculation amount of subsequent positioning search are greatly reduced, cost is low, in addition, when it is recognized that the vehicle enters the next topological path section from one topological path section, the database is inquired to obtain the starting point pose of the new topological path section, the starting point pose of the new topological path section is directly used for resetting the pose of the vehicle subjected to track plotting, and therefore the accuracy of track plotting of the vehicle is improved. According to the method, when a vehicle runs in a topological path section from zero, the transverse distance from the vehicle to the reference path of the current topological path section is measured according to a preset interval, and the pose of the vehicle is subjected to filtering correction, so that the effects of regular zero clearing of a large error and real-time suppression of a small error are achieved; and high precision of full-path relocation is ensured.

The invention relates to the technical field of bioinformatics, and discloses a novel sugar chain structure identification method based on a GU value, and the method comprises the following steps: calculating the GU value of an unknown sugar chain sample; converting the known carbohydrate chain structure into a known carbohydrate chain feature vector; selecting a graph convolutional network model to process the sequence, and training a sugar chain structure model by using a cross validation method; inputting the GU value of the sugar chain sample into the model for similarity analysis; compared with a sugar chain structure identification method depending on accurate molecular weight or sequence matching in the prior art, efficient and accurate identification is difficult to realize when a complex sugar chain structure is processed, especially under the condition that a sample structure is complex. According to the method, GU value calculation is combined with the deep learning model to predict the carbohydrate chain structure, so that the structure of an unknown carbohydrate chain can be efficiently and accurately deduced, the limitation caused by high complexity and long consumed time in the prior art is avoided, and the efficiency and accuracy of carbohydrate chain structure identification are remarkably improved.

The invention provides a radar ranging interference echo filtering method, a laser radar and a readable storage medium, and relates to the technical field of laser radars. The method comprises the following steps: driving a laser radar to emit a multi-detection pulse coding sequence in a current distance measurement period, and performing pulse sequence construction on all echo pulses received in the current distance measurement period to obtain at least one echo pulse sequence to be matched; wherein the total number of echo pulses of each to-be-matched echo pulse sequence is consistent with the total number of detection pulses of the multi-detection pulse coding sequence, and then pulse distribution characteristic matching is carried out on each to-be-matched echo pulse sequence and the multi-detection pulse coding sequence, so that all the echo pulses received in the current distance measurement period are subjected to pulse distribution characteristic matching; and a target echo pulse sequence successfully matched with the multi-detection pulse coding sequence is screened and reserved, so that over-period echo interference and multi-radar echo interference in the laser radar ranging process are removed, and the laser radar ranging accuracy is improved.

The invention provides a code statement speculation method and device, a storage medium, electronic equipment and a program. A specific embodiment of the method comprises the following steps: in response to an obtained current priori lexical element sequence, executing speculative decoding on the current priori lexical element sequence, and generating a plurality of candidate lexical element sequences for connecting the current priori lexical element sequence; verifying whether each candidate lexical element sequence is valid or not; in response to determining that any candidate lexical element sequence is invalid, correcting the invalid candidate lexical element sequence into an effective candidate lexical element sequence; determining a current target lexical element sequence matched with the current priori lexical element sequence from each effective candidate lexical element sequence; and forming a code statement by the current priori lexical element sequence and the current target lexical element sequence in response to an end identifier recognized from the current target lexical element sequence. According to the embodiment, the accuracy of the code statements is improved.

The invention discloses a text matching positioning method, system and device and a medium. The method comprises the steps of obtaining an original long text and segmenting the original long text into ordered text blocks; selecting the first N text blocks to form a first candidate set based on the common substring sorting of the to-be-matched text and each text block; intercepting the first candidate set according to head and tail characters of the to-be-matched text to obtain a second candidate set; calculating similarity scores of the text blocks in the second candidate set and the to-be-matched text through a sequence matching similarity algorithm; combining the scores with the first candidate set to determine a matching result and output a position, and judging that no matching exists when all the scores are lower than a preset minimum threshold value. According to the method, the limitation of a traditional matching mode is broken through through primary screening of common substrings, accurate interception of head and tail features and multi-layer processing of a sequence matching similarity algorithm, complex scenes such as text missing and semantic equivalent expression can be effectively handled, the accuracy and robustness of text positioning are improved, and the user experience is improved. The method can be widely applied to the fields of document management, information retrieval, academic analysis and the like.

The invention discloses a storage type passive covert channel method and system using multiple protocols, a covert transceiver synchronization mechanism and a reversible data hiding mechanism are designed based on an m sequence, and the appointed m sequence is searched for a network data packet load through a sequence matching method to determine a covert carrier data packet. Calculating an allowable maximum matching fault-tolerant bit r to improve the matching probability of the m sequence; in the fault-tolerant bit r, the hidden sender allows the load to be modified so as to embed hidden data; a hidden receiver searches a hidden carrier through an agreed m sequence, extracts hidden data and recovers a data packet to realize reversible data hiding; a kernel module based on an Openwrt system is designed to realize covert channel construction, and the system can be deployed in equipment such as an intelligent router carrying the Openwrt system. According to the invention, while the capacity and the transmission rate of the covert channel are ensured, relatively low calculation storage resources are consumed, and the method has the anti-flow analysis capability.

The invention discloses a lossless compression storage method and system based on heterogeneous data in a credential environment, and the method comprises the steps: firstly, extracting a mapping relation between a file type and a structural feature through scanning a target file, carrying out the preliminary lossless compression after classification and grouping, and further employing a sliding window matching and sequence matching algorithm to optimize compressed data for a redundancy mode, and then generating a metadata structure containing a check code and a compression parameter, packaging the metadata structure into a data packet supporting cross-platform transmission, finally transmitting the data packet to a target storage device through a secure write-in protocol, and verifying data consistency and recovering path feasibility by using the check code. According to the method, the data compression efficiency is remarkably improved, the compatibility of cross-platform transmission and the integrity of stored data are ensured, and efficient and reliable technical support is provided for complex electronic file processing.

The invention relates to the technical field of Internet of Things communication, in particular to a cellular Internet of Things multi-node keep-alive communication system and method, and the system comprises a first module which is used for intercepting and copying uplink and downlink data streams of a plurality of nodes forwarded by gateway equipment in a bypass mode to obtain a data packet, and extracting a specified message from the data packet; the second module is used for receiving a specified message, matching the specified message with a pre-stored sequence, and updating a corresponding sequence field and determining a sequence state if matching succeeds; updating a sequence state and a period based on a matching result; feature vectors are extracted according to the matched specified messages and sequence periods, and all sequences are clustered and grouped; according to a clustering result, a periodic keep-alive channel is established between the gateway equipment and the target servers, a cellular IP address obtained by the gateway is used as a source address, and a keep-alive detection request is sent to each target server according to a set time slot; after the response is received, the sequence keep-alive state is updated and fed back to the corresponding node.

The invention relates to a cross-camera vehicle tracking system and method, in particular to a cross-camera vehicle tracking system and method based on license plate historical sequence matching. The invention aims to solve the problems that license plate matching among different cameras is difficult in a large traffic network, and particularly, license plate matching and vehicle tracking cannot be quickly and accurately carried out under the condition that coverage areas of a high-flow road section or a plurality of cameras are overlapped. According to the invention, license plate recognition is carried out on the video stream captured by each camera, all license plate recognition results of vehicles tracked by the same camera are used as a sequence, and Hungary matching is carried out on the historical license plate recognition sequences of the plurality of cameras; and if yes, the two vehicles are considered to be the same tracking target. And if the matching is successful and the vehicles are confirmed to be the same vehicle, the system distributes the same unique ID to the vehicles, so that continuous tracking across cameras is realized. The invention belongs to the technical field of computer vision.

The invention discloses an intelligent electric power system remote monitoring device and a monitoring method thereof, relates to the technical field of electric power monitoring interference prevention, solves the problem that comprehensive and deep feature extraction is difficult to perform on complex waveforms, and provides an intelligent electric power system remote monitoring device and a monitoring method thereof through careful analysis of signal waveform features in a monitored line. A scientific characteristic value sequence recognition system is established; aiming at the standard waveform of each monitoring item, the characteristic value sequence of the standard waveform is accurately locked, and whether the signal waveform is interfered or not can be sensitively identified by virtue of change characteristic analysis and characteristic sequence matching; according to the method, the abnormal waveform points and the interference waveforms are accurately calibrated, a proportion value judgment method is applied, misjudgment caused by parameter numerical value fluctuation is effectively avoided, the interference recognition accuracy is greatly improved, frequency filtering is directly carried out on the waveforms which do not belong to monitoring items, and the filtering efficiency is improved; for the waveforms belonging to the monitoring item, the time of different waveforms is ingeniously adjusted by determining a time difference characteristic sequence.

The invention relates to the technical field of warehouse management, in particular to a modular PCB workbin three-dimensional storage system and method.The system comprises a to-be-warehoused obtaining module used for obtaining product information of multiple workbins carried by an AGV intelligent carrier to be warehoused to obtain multiple pieces of to-be-warehoused product information; the warehouse state monitoring module is used for acquiring a storage position list in a current warehouse in real time; the sequence generation module is used for generating multiple warehousing sequences based on the multiple pieces of to-be-warehoused product information; the matching degree analysis module is used for analyzing the highest matching degree of each warehousing sequence and each storage cabinet in a storable state; the screening module is used for screening out the warehousing sequence corresponding to the matching degree meeting the preset condition as a final warehousing sequence; the sending module is used for sending the final warehousing sequence to the AGV intelligent carriers to be warehoused; and the AGV intelligent carrier warehouses the material boxes corresponding to the information of the multiple products to be warehoused according to the received warehousing sequence. The method has the effect of improving the ex-warehouse efficiency.

The invention relates to the technical field of cross-network data management, in particular to a cross-network data aggregation method and system based on holographic perception, and the method comprises the steps: obtaining a network field path identifier, a grade and a time period, accumulating and sorting access frequencies, analyzing the frequency and grade combination distribution, extracting a field name, a network grade and a time label, and matching and comparing the frequency difference. And counting field hopping frequency, marking, and matching field paths and channel numbers to obtain cross-network fusion data sequence output. According to the method, through dynamic grouping, frequency analysis and fusion positioning of the data fields under the network level and the time dimension, the field distribution rule identification precision is improved, and the affiliation perception consistency is enhanced. And by utilizing residual error ratio screening and path sequence matching, the field screening precision and the transmission sequence structural property are improved, and synchronous enhancement of data fusion output efficiency, transmission stability and resource configuration coordination in a multi-network environment is realized.

The invention relates to the technical field of residual current protection, in particular to a power distribution network residual current protection method and system based on a distributed photovoltaic power supply, and the method comprises the following steps: obtaining a zero-sequence current waveform in a disturbance period, recognizing an abrupt change node, analyzing the fluctuation rhythm and trend, and constructing a response structure; the method comprises the following steps: extracting a sequence relationship between abrupt change nodes and fluctuation rhythms, constructing a response fragment set with trend consistency and rhythm coherence, screening response fragments capable of triggering protection, adjusting a starting point and a sequence, completing action triggering rhythm merging, and generating a residual current protection strategy, in the method, through sequence relationship extraction between the abrupt change nodes and the fluctuation rhythms, constructing a response fragment set with trend consistency and rhythm coherence, and combining a change cooperation relationship between sections; key paragraphs capable of triggering protection are screened out, the triggering sequence and the starting point position are adjusted according to trend continuity, the starting time sequence matching degree is improved, behavior stability is judged through trend coherence, rhythmic merging of response structures is achieved, action strategies with directivity and continuity are output, and the precise control capacity of protection response under variable disturbance is enhanced.