25 results about "Interval Sequence" patented technology

The invention discloses an operation ticket intelligent analysis and sequence control logic closed-loop verification method and system, and belongs to the field of power system automation technology and power transformation operation and maintenance, and the method comprises the steps: obtaining a typical interval sequence control operation ticket and an SCD file; identifying the typical interval sequence control operation order through a BERT-ERNIE multi-head text extraction model, and generating a corresponding test script; querying corresponding object path information in the SCD and completing association; constructing a closed-loop acceptance environment; simulating a local operation scene and initiating sequence control operation according to the associated test script to carry out correctness acceptance; on the basis of a similar interval operation ticket generation tool, carrying out one-key replacement on part of description information of the test script passing acceptance, generating similar interval sequential control operation tickets to be accepted, and carrying out correctness acceptance; and simulating a sequence control master station address in the closed-loop acceptance environment, issuing a sequence control instruction to a sequence control host based on the sequence control operation order passing correctness acceptance, and automatically virtualizing the test environment to perform forward and reverse closed-loop automatic acceptance.

The invention relates to the technical field of test regulation and control for 5G terminals, and discloses a test regulation and control system and method for 5G terminals. And connecting the service plane data after the UE-base station is established. Firstly, test parameters and cyclic variables are uniformly initialized, throughput rate is acquired point by point according to a current sampling interval, and a network state is accurately captured. Calculating a mean value and a standard deviation of the window sample, adaptively determining a fractional order derivative order according to the mean value and the standard deviation, and calculating a fractional order derivative sequence by using a fractional order binomial coefficient; and counting the local fluctuation quantity mapped by the sequence standard deviation, taking the local fluctuation quantity as a closed smooth reconstruction weight, and quickly outputting the smooth throughput rate. Based on the smoothing result and the fluctuation quantity, adaptively adjusting the sampling interval and the starting moment of the next window: prolonging the interval to save resources when the network is stable, and shortening the interval to improve the sampling density when the fluctuation is violent; and finally, automatically terminating the test according to an end condition and outputting a smooth throughput rate and a self-adaptive sampling interval sequence.

The application relates to the field of computer data processing and discloses a traffic automatic playback method for software testing, which comprises the following steps: obtaining software traffic data and obtaining data packets and time intervals in the software traffic data; according to interval values and time sequence distribution relationships of the time intervals, a first category is obtained through multi-threshold segmentation, a third category is obtained through threshold segmentation of the first category, and all intervals except the third category in a time interval sequence are classified into a fourth category; a first compression rate of each interval in the fourth category is obtained, and a second compression rate of each interval in the third category is obtained; a correction coefficient is obtained according to the number of elements of the first category to which each interval in the fourth category belongs and packet values of adjacent data packets, and a third compression rate is obtained; and the traffic data is compressed and automatically played back according to the obtained compression rates. The application aims to solve the problems that the existing equal compression of time intervals between data packets leads to packet loss and large differences between traffic data before and after compression.

This invention relates to the fields of network security and network simulation technology, and discloses a method for reshaping malicious traffic based on feature serialization. By collecting traffic data from the target network environment, serialized features of load and time intervals are extracted, and session flow features are further statistically obtained. Then, based on Pareto, normal, log-normal, and Poisson probability distribution models, serialized features conforming to the target network traffic characteristics are generated, and the probability distribution model with the highest similarity to the target network traffic is selected by calculating Euclidean distance. Finally, based on this model, the load and time interval sequences of malicious traffic are reshaped to generate network attack traffic that is difficult to detect. This invention effectively improves the concealment of malicious traffic, making it more difficult for existing detection systems to identify; the generated malicious traffic can effectively test and evaluate the capabilities of network intrusion detection systems.

The invention discloses an anti-eavesdropping-based self-defined interval combination password method, which specifically comprises the following steps of: recording a time interval of adjacent keys in a password input process of a user by adopting a sliding window mechanism, and storing the time interval as a rhythm interval sequence; in the password input process, random jitter and rhythm speed scaling are applied to the rhythm interval sequence to generate a disturbed rhythm sequence; constructing a basic camouflage event comprising a camouflage sound source and a volume parameter, and randomly inserting an interference camouflage event into the basic camouflage event; combining the basic camouflage events and the interference camouflage events into an event queue, and performing sorting and anti-congestion adjustment according to a time sequence to form an interruptible camouflage event queue; and based on the camouflage event queue, playing corresponding camouflage sound according to event triggering time so as to carry out acoustic masking on a real key pressing rhythm.

The invention relates to the technical field of data security, in particular to a security operation method and system based on multi-agent collaboration, and the method comprises the steps: intercepting and capturing a TLS length and a time interval sequence of an encrypted session by using an edge-aware agent, constructing a spatio-temporal topology embedding vector based on a linear visibility criterion and a graph attention mechanism, and constructing a spatial-temporal topology embedding vector; and the flow agent maps the vector into a Gaussian distribution parameter to generate a token adjustment coefficient, dynamically adjusts the token bucket frequency and executes asynchronous delay shaping by using a time wheel, and the reflection agent combines a flow confusion escape rate and a processing delay index to carry out closed-loop updating on model parameters through a strategy gradient algorithm. According to the invention, adaptive defense of the encrypted covert channel is realized through dynamic traffic shaping.

The invention belongs to the technical field of digital data transmission, and particularly relates to an adaptive modulation data transmission method and system based on bit error rate statistics, and the method comprises the steps: recording the bit error interval length between adjacent bit error bits, and obtaining a bit error interval length set; sorting the error code interval length set to obtain an ordered error code interval sequence, and calculating an error code gathering index by using weighted summation; constructing a background noise retention weight by using an error code aggregation index, and calculating an effective background error rate in combination with a physical statistical error rate; and determining a target modulation mode according to the effective background bit error rate, and performing data transmission. According to the method, whether the error code is caused by the random background noise or the burst transient interference can be distinguished from the statistical domain, the effective background error rate is restored by stripping the burst component when the transient interference occurs, the throughput loss caused by blind order reduction modulation is avoided, and the link transmission efficiency and reliability under a complex channel are improved.

The present application relates to a kind of automatic unpacking device of present cash, including roller conveyor, roller conveyor includes multiple interval sequencing roller body, each roller body is rotationally sleeved rolling sleeve tube, the gap between two adjacent rolling sleeve tube is the storage space for placing coin column, further including support, pivot and swing arm;When the coin column conveying support is directly below, driving member drives pivot positive rotation, pivot is driven by swing block to move the swing arm close to coin column upward, while another swing arm moves downward, rotating roller starts to rotate, after obliquely arranged scraper and the seal of coin column contact, the paper of coin column in rotating state is gradually stripped, further, the paper of suction passage is recycled, by such, mechanical automation is realized to coin column and is disassembled, greatly improve work efficiency.

The application discloses a kind of MEC task unloading methods and devices for interval uncertainty, it is related to edge computing technical field.The method includes: obtaining the task parameter of task to be handled, terminal resource parameter and MEC resource parameter, and the uncertain parameter in it is expressed as interval parameter;According to unloading decision variable and interval parameter, construct interval uncertain optimization model including energy consumption, time delay and user side cost;Interval energy consumption target is converted into interval center value target and interval radius value target based on interval sequence relation, and interval constraint is converted into deterministic constraint based on interval possibility, to obtain deterministic multi-objective optimization model;Dual-layer optimization unloading algorithm is used to solve, to obtain target unloading strategy.The application can consider energy consumption, time delay, cost and resource constraint in the case where parameter exists interval uncertainty, improve the robustness of task unloading.

The invention discloses a data stream change detection method based on an isolation mechanism, and the method comprises the following steps: S1, data partitioning: dividing input sequence data into non-overlapping interval sequences according to the length w, and enabling one interval to be a window; s2, constructing isolated kernel mapping: selecting a series of representative windows, and uniformly sampling psi data points from the window data; s3, interval feature representation: aiming at each window, mapping all data contained in the window to a Hilbert space of an isolated kernel, and calculating a mean vector of the data in the space; s4, calculating the similarity of adjacent intervals; s5, automatically searching parameters; and S6, change interval detection. According to the method, a point-to-interval target detection method and an isolated kernel similarity measurement mode are adopted, the real-time performance, robustness and fine change capturing capacity in data flow change detection are balanced, and a practical solution is provided for distribution change detection in real large-scale streaming data.

The embodiment of the invention discloses an SSA rule calculation method and device of a layout, electronic equipment and a storage medium. According to the scheme, the data table required by the process window can be determined according to the focal length exposure matrix data corresponding to the layout and the preset rule, the data table records the minimum line width and the minimum spacing meeting the photoetching process window under different center distances, and the predefined SSA rule table is generated according to the preset line width interval sequence and the spacing interval sequence. And traversing each cell of the predefined SSA rule table, calculating a compensation value corresponding to each cell according to the data table, filling the compensation values into the predefined SSA rule table, and outputting a final SSA rule table. According to the embodiment of the invention, the process window requirement data table is generated through the focal length exposure matrix data of the layout, and then the compensation values of different line width intervals and interval intervals are calculated, so that the SSA rule table is obtained, the SSA rule can keep the design size of the original layout to a large extent after being used, and the calculation efficiency and accuracy are greatly improved.

The present application relates to the technical field of test regulation for 5G terminal, and discloses a test regulation system and method for 5G terminal. After the service plane data of UE-base station connection is established, the test parameters and the loop variable are initialized, the throughput rate is collected point by point according to the current sampling interval, and the network state is accurately captured. The mean and standard deviation of the window sample are calculated, the fractional derivative order is adaptively determined according to the mean and standard deviation, the fractional derivative sequence is calculated by using the fractional binomial coefficient, the standard deviation of the sequence is mapped to the local fluctuation, which is used as the closed smooth reconstruction weight, and the smooth throughput rate is quickly output. Based on the smooth result and the fluctuation, the next window sampling interval and starting time are adaptively adjusted: when the network is stable, the interval is lengthened to save resources, and when the fluctuation is severe, the interval is shortened to improve the sampling density; finally, the test is automatically terminated according to the end condition, and the smooth throughput rate and the adaptive sampling interval sequence are output.

The invention discloses an anti-interference frequency hopping sequence construction method based on sequence combination, and belongs to the field of communication signal processing. The frequency band hopping sequence is constructed by adopting a wide interval sequence design means, and the frequency band interval dbw meets the condition that the interval between the selected frequency point and the other frequency points in the adjacent frequency band is greater than the minimum frequency hopping interval d, so that the probability that the adjacent working frequency points fall into an interference band during frequency hopping communication is greatly reduced, and the resistance to blocking interference is ensured. Randomization mapping is carried out on frequency points in a frequency band, a pseudo-random sequence with excellent balance is constructed, combination mapping is carried out on the pseudo-random sequence and a wide-interval frequency band hopping sequence, the random performance of the sequence is improved through random disturbance, and then the decoding risk is reduced. By adopting balance characteristics and approximate entropy evaluation criteria, flexible selection of a sequence proportion is realized, and optimization of anti-interference performance of the sequence is realized at the same time; a data link frequency hopping synchronization verification scene is adopted, a frequency hopping communication condition is simulated in a blocking interference environment, and accurate evaluation of the anti-interference performance of the sequence is realized.

The invention belongs to the technical field of e-commerce, data analysis and platform supervision, and provides a scalping behavior analysis method and system, and the method specifically comprises the steps: arranging a customer service interactive collection and unified coding scene, recognizing a merchant code from the scene, collecting an adjacent reply time interval sequence of a session and a customer service reply field sequence for each merchant according to the merchant code, and carrying out the collection of the adjacent reply time interval sequence and the customer service reply field sequence; the method comprises the steps of firstly obtaining a reply field sequence, then obtaining a rhythm index based on the adjacent reply time interval sequence, obtaining a process transfer index based on the customer service reply field sequence, finally obtaining a scalping homogeneous volume through the rhythm index and the process transfer index, and judging whether a merchant carries out a scalping behavior or not according to the scalping homogeneous volume. In combination with the characteristics that the manual service is influenced by information retrieval and input time delay, the beat is discrete and multi-peak, and the flow path is multi-path walk, and the characteristic that the script beat converges and the path multiplexing is stable and homogeneous, the difference quantification of normal customer service and scalping scripting group control behaviors is realized at the merchant level, and the merchant management efficiency is improved.

The present invention belongs to the field of adaptive dynamic priority caching technology and discloses an adaptive dynamic priority caching method, system, device and medium. The method includes calculating the average number of accesses per unit time based on the frequency domain characteristics and time domain characteristics of the cache items to obtain the access frequency of the cache items; calculating the access interval change rate based on a predefined discrete interval sequence, differential approximate differentiation, dimensional normalization processing and direction-sensitive design mechanism; calculating the cache items with the latest priority based on the access frequency and access interval change rate of the cache items in combination with an adaptive dynamic priority caching model, and re-inputting the cache items with the target priority into the adaptive dynamic priority caching model for calculation to eliminate the cache items with the lowest current priority. By integrating the access frequency and the access interval change rate, the present invention breaks through the limitations of traditional single-dimensional strategies.

The application relates to a symbol rate calculation method for a phase amplitude modulation mode, which uses a density clustering and statistical method to calculate the symbol rate according to the self characteristics of a radio phase amplitude modulation mode signal; specifically, a signal forward difference sequence of a phase is subjected to statistical analysis to find a suspected symbol position threshold in a distance sequence, suspected symbols whose positions are greater than the suspected symbol position threshold are found, the suspected symbols are counted and an interval sequence is reconstructed, then clustering calculation is adopted, and finally the symbol rate is obtained. A device for the symbol rate calculation method for the phase amplitude modulation mode and a storage medium are also disclosed. The application has the beneficial effects that even if noise exists in the signal, the calculation accuracy of the symbol rate is not affected, and the application has strong practicability and robustness.

The application provides an immersive script experience data processing system based on role selection, and relates to the technical field of data processing. The system is used for: constructing a behavior track under a role perspective, performing paragraph division and cluster reorganization on the behavior track, obtaining role paragraph data, and according to the node number span between the role paragraph data and a script preset node path, counting the number of jumps and the span difference, identifying the offset characteristics of the role behavior track, calculating a behavior jump factor, calculating the time interval sequence between consecutive nodes, performing timing stability analysis on the time interval sequence, calculating the synchronization deviation degree of the behavior timing, obtaining a timing offset factor, and performing deviation detection on each role number according to the behavior jump factor and the timing offset factor to obtain a behavior analysis result. The application can perform abnormal analysis on data generated by different role selections.

This invention belongs to the fields of e-commerce, data analysis, and platform monitoring technology. It proposes a method and system for analyzing fraudulent order behavior. Specifically, it involves: deploying a customer service interaction collection and unified coding scenario to identify merchant codes; collecting adjacent response time interval sequences and customer service response field sequences for each merchant based on their codes; obtaining rhythmic indicators based on the adjacent response time interval sequences and process transition indicators based on the customer service response field sequences; and finally obtaining the homogeneous product of fraudulent order behavior through the rhythmic and process transition indicators. The homogeneous product of fraudulent order behavior is then used to determine whether a merchant is engaging in fraudulent order behavior. This invention combines the characteristics of human service—affected by information retrieval and input delays, resulting in discrete, multi-peaked rhythms and multi-path processes—with the stable, homogeneous form of scripted rhythm convergence and path reuse. At the merchant level, it achieves the quantification of differences between normal customer service and scripted group control behavior for fraudulent orders, improving merchant management efficiency.

The application discloses a tunnel user fine behavior identification method and system, and belongs to the network flow detection field. Byte features of unlabeled tunnel flow are extracted, the context relationship of the unlabeled tunnel flow is learned through a pre-trained network model, and a vector representation of the byte features is generated; byte features of target tunnel user behavior flow, a data packet length sequence and a data packet arrival time interval sequence are extracted, and a vector representation of the byte features is obtained through the pre-trained network model; hidden state features of the vector representation of the byte features, the data packet length sequence and the data packet arrival time interval sequence are obtained based on a convolutional neural network (CNN), and then comprehensive hidden state features are obtained through fusion; and the comprehensive hidden state features are input into a classifier to predict the target tunnel user behavior. The application can solve the problem that existing methods are difficult to identify tunnel user behavior in a real network environment.

The invention discloses a network security analysis system and method based on artificial intelligence, and relates to the technical field of network security, and the method comprises the steps: calculating an opposite-end clock rate sequence based on a message arrival interval sequence and a timestamp increment sequence of a target encrypted session; carrying out detrending processing on the sequence to obtain a clock rate micro-drift sequence; determining a warming resonance index based on the micro-drift sequence and the arrival interval sequence; determining whether the session is suspicious by combining the index setting threshold value of the historical normal session; and executing key refreshing, channel pause and evidence packet generation according to a judgment result. According to the method and the device, the abnormal state of the encrypted session can be accurately identified under the condition that the message is not decrypted.

The invention provides a self-adaptive control method and system for hearth outlet pressure of a circulating fluidized bed boiler, and relates to the technical field of pressure control. The method comprises the steps that multiple historical operation samples are obtained by collecting historical operation data; a fixed load interval sequence is predefined for load interval grouping processing, and multiple groups of sample points are obtained; a least square method is adopted to fit a linear model to solve PID parameters, and multiple groups of load case points are obtained; performing associated storage to complete construction of a load case library; case matching retrieval is carried out, and if the same load value exists, K same load case points are returned; executing arithmetic mean value, and outputting real-time optimization parameters; and the pressure is sent to the PID controller to execute hearth outlet pressure control. The technical problems that in the prior art, boiler furnace outlet pressure control is generally based on preset static parameters, PID parameters cannot be updated in real time according to changes of different working conditions, the boiler efficiency is reduced, and even the equipment overpressure risk occurs are solved.

The invention discloses a household integrated energy system storage battery capacity configuration method based on interval optimization, and the method comprises the steps: constructing an interval optimization model of storage battery capacity configuration based on photovoltaic output and user demand uncertainty; converting the storage battery uncertainty optimization model of the household integrated energy system containing the interval number into a deterministic model through an interval order relation; and solving the deterministic model obtained by conversion by adopting a genetic algorithm to obtain the optimal storage battery capacity configuration. According to the method, the interval of the uncertainty parameter is directly obtained, the interval number is adopted to represent the uncertainty parameter, and a probability distribution model does not need to be obtained; and constructing a storage battery capacity configuration model by establishing an optimal objective function and constraint conditions. According to the method, uncertain factors existing in the storage battery capacity optimization configuration process can be effectively processed, and the economical efficiency and the low-carbon property of system operation are improved.

The invention provides a state reporting method, which comprises the following steps of: determining a serial number of a lost data packet as a first serial number when a current terminal starts to find that the data packet is lost in a receiving process, and determining a maximum serial number of the data packet received by the current terminal as a second serial number; obtaining the number m of bits capable of being filled in each row in the status report message; obtaining the total number n of a plurality of serial numbers after the first serial number and before the second serial number, and obtaining the multiple relation between the total number n and the bit number m; and according to the multiple relationship, filling an indication field of a first region in the status report, a complete interval serial number response result mapping field of a second region and a first non-response serial number field corresponding to an incomplete interval serial number of a third region. According to the invention, the packet loss state can be flexibly represented, the transmission efficiency is improved, and the occupancy rate of air interface resources is reduced.

The invention belongs to the technical field of self-adaptive dynamic priority caching, and discloses a self-adaptive dynamic priority caching method, system, device and medium, and the method comprises the steps: calculating the average access times of unit time based on the frequency domain characteristics and time domain characteristics of a cache item, and obtaining the access frequency of the cache item; calculating to obtain an access interval change rate based on a predefined discrete interval sequence, differential approximate differentiation, dimension normalization processing and a direction sensitive design mechanism; on the basis of the access frequency and the access interval change rate of the cache items, the cache item with the latest priority is obtained through calculation in combination with the self-adaptive dynamic priority cache model, the cache item with the target priority is input into the self-adaptive dynamic priority cache model again for calculation, and the current cache item with the lowest priority is eliminated. According to the method, the limitation of a traditional one-dimensional strategy is broken through by integrating the access frequency and the access interval change rate.

The present disclosure relates to service level agreement (SLA) performance prediction methods, apparatuses, and devices. In one example method, a first network device obtains timestamps and packet lengths of a plurality of data packets. The first network device determines an arrival time interval of each of the plurality of data packets based on the timestamps of the plurality of data packets, where arrival time intervals of the plurality of data packets constitute a time interval sequence according to an arrival order. The first network device determines time domain feature parameters of the plurality of data packets based on a Markovian arrival process (MAP) model and the time interval sequence.