130 results about "Combination algorithm" patented technology

The invention relates to the field of construction engineering, in particular to a roadbed construction slope displacement monitoring system based on cloud computing. A sensor network is used for collecting roadbed construction data in a roadbed, wavelet transform is used for denoising the data, a dynamic time warping algorithm in a cloud computing unit is used for aligning time sequence data in the initial roadbed construction data, and the weight of each sensor data is dynamically distributed based on an entropy weight method. A hybrid prediction model is established based on an LSTM long short-term memory network and FEA finite element analysis, a slope stress field result simulated by FEA is used as a physical constraint layer of the LSTM, an attention layer is embedded in the physical constraint layer, hyper-parameters of the initial hybrid prediction model are optimized by using a Cs-Ant improved cuckoo-ant colony combinatorial algorithm, and a slope stress field is obtained. And inputting the feature roadbed construction data into the target Cs-FEA-LSTM hybrid prediction model for prediction. The manual analysis cost is effectively reduced, and the level of roadbed engineering full-period monitoring is improved.

The invention discloses an advertisement optimized putting system and putting method, and the method comprises the following steps: S10: obtaining user behavior data, the user behavior data comprising historical interaction information and real-time environment data of a user; s20, analyzing the historical interaction information and the real-time environment data of the user, and identifying user features and user interests; s30, based on a combined algorithm of a convolutional neural network and a generative adversarial network, dynamically generating an optimal advertisement content and an optimal advertisement format matched with the user features and the user interests; and S40, performing real-time advertisement putting on a target advertisement platform by using the optimal advertisement content and the optimal advertisement format. According to the method provided by the embodiment of the invention, the personalized advertisement content and format are dynamically generated by acquiring and analyzing the user behavior data, and the advertisement is put on the target platform in real time, so that the accuracy and effect of the advertisement are improved.

The invention discloses an in-tunnel cable facility defect feature extraction and identification method and system based on YOLOv8, and relates to the technical field of artificial intelligence, and the method comprises the steps: collecting data through an automatic moving platform and a high-definition camera, carrying out the preprocessing of denoising, contrast enhancement and the like, and extracting defect features through a designed convolutional neural network. And real-time defect detection is realized through a YOLOv8 algorithm, and the efficiency is improved through model lightweight processing. A detection result is optimized through a non-maximum suppression and double combination algorithm, and finally a multi-format visual report is generated. According to the method, efficient extraction and accurate identification of defect features of the cable facilities in the tunnel are achieved, the rapid detection capability and the fine feature extraction capability of the YOLOv8 are combined, the risk and cost of manual inspection are reduced, the cable facilities in the tunnel are efficiently managed, and the method is suitable for detecting the defects of the cable facilities in the tunnel and has good application prospects. And features of different defects can be learned, so that accurate identification of defect types is realized.

The invention discloses an electric energy quality comprehensive treatment method and device based on multilevel collaborative optimization, and belongs to the technical field of electric energy quality treatment of an electric power system. According to the method, voltage and current data of a power grid are collected in real time and multi-parameter monitoring is performed; processing the data by using an adaptive wavelet transform and singular value decomposition combined algorithm, extracting disturbance characteristics and identifying the type and position of a disturbance source; a multi-objective optimization function including harmonic suppression, voltage stabilization, three-phase balance and power factor improvement is constructed, a Pareto optimal solution set is solved, and an optimal solution is selected; and according to an optimization result, generating and executing a cooperative control strategy of each type of electric energy quality treatment equipment. Cooperative treatment of various electric energy quality problems and cooperative control of various treatment devices are realized, the accuracy, self-adaptability and economical efficiency of electric energy quality treatment are improved, and the reliability and stability of an electric power system are enhanced.

The invention relates to a thermocouple position layout optimization method based on feature point extraction, and the method comprises the following steps: heating a patch and an adhesive through a hot patching instrument, obtaining the temperature field data of an adhesive interface based on a finite element simulation method, and extracting the temperature value and coordinates of each node; analyzing the time sequence change of the temperature field data, and screening the key frame with the maximum node temperature standard deviation; performing spatial interpolation on the node temperature data of the key frame to generate a two-dimensional temperature distribution matrix; feature points are extracted from the temperature distribution matrix through a combined algorithm of extreme value layering, OPTICS density clustering, gradient analysis and adaptive spatial distribution; and optimizing the thermocouple installation position according to the feature point distribution. Through the method, the heating conditions of the bonding interface and the patch are monitored and fed back by using the accurate number of the thermocouples and setting the accurate positions of the thermocouples, and meanwhile, the problem that uneven heating cannot be monitored due to the fact that the positions of the thermocouples are improperly set is solved.

The invention discloses a Web end real-time path planning method and system, a storage medium and equipment, and relates to the technical field of path planning, and the method comprises the steps: collecting traffic data and environment change information in a Web end application scene in real time in the driving process of a vehicle, and converting the traffic data and environment change information into a standard data format for algorithm processing; performing path initial planning by adopting a hybrid algorithm to obtain an initial path; acquiring actual path driving information fed back by the environment sensing device and the user, comparing the actual path driving information with the initial path, and judging whether an actual path in the actual path driving information is different from the initial path or not; if yes, revising the recommended path in the navigation system in real time according to a preset proofreading rule to obtain a target navigation path shared to other vehicles; wherein the hybrid algorithm is a combination algorithm of a genetic algorithm and an ant colony algorithm. According to the invention, real-time optimization of the distribution path is realized, various road condition changes are efficiently coped with, and individual requirements of clients are met.

The invention discloses a distribution box room environment parameter integrated measurement method, and particularly relates to the field of multi-parameter measurement, and the method comprises the steps: firstly constructing a machine room three-dimensional model and a sensor correlation degree matrix, then building a heat balance, humidity diffusion and airflow motion model, and calibrating parameters; deploying a measurement system and calibrating through dual synchronization and cross check; establishing a sensor confidence evaluation system and an adaptive threshold based on 72-hour reference data; fusing calibration data by adopting a three-level correlation calibration mechanism; four types of measurement modes and conversion logics are designed, and measurement resources are dynamically allocated through environmental risk assessment; multi-dimensional state parameters are extracted, a comprehensive evaluation value is calculated through normalization, dynamic weighting and combinatorial algorithms, and five-level early warning response is achieved; according to the method, multiple models and an intelligent algorithm are integrated, the parameter measurement precision and the environment risk identification efficiency are improved, the response delay is reduced, the fault diagnosis accuracy is improved, and reliable technical support is provided for safe operation and maintenance of the distribution box room.

The invention provides a building change detection method and system based on a multi-source live-action three-dimensional model, and the method comprises the steps: obtaining the triangulation network topology data of a two-stage live-action three-dimensional model in a to-be-detected region, and carrying out the preprocessing and standardization processing; a plane-elevation layered registration technology is adopted for automatic registration, and coordinate unification without manual intervention is achieved; calculating and identifying a three-dimensional change area of the two-stage live-action three-dimensional model by using a spatial index difference, and optimizing the three-dimensional change area by adopting a multi-scale expansion-corrosion combination algorithm; filtering the optimized three-dimensional change area by using three-dimensional feature dual channels, and verifying the real building change; and generating a four-dimensional spatio-temporal result, and outputting a visual model including the elevation change value, the material type and the three-dimensional reconstruction parameters. According to the method, the problem that the subtle change of the building in a large-scale real scene model can be read by a machine is solved, and a high-reliability three-dimensional quantitative analysis tool is provided for urban illegal building monitoring and urban safety management.

A deep learning based method for integrating demand forecasting and scheduling of online ride-hailing at a hub is provided. The method includes: S1, performing data processing: performing missing value filling, outlier processing and normalization processing on the historical orders of online ride-hailing and relevant feature data of the urban transportation hub; S2, performing feature screening: primarily screening the relevant features by means of a Pearson correlation test and box plot analysis, calculating an influence degree of data of each feature on the orders of online ride-hailing by using an XGBoost algorithm, and secondarily screening the features; S3, performing model construction: constructing an integrated model for demand forecasting and scheduling decision of online ride-hailing at the urban transportation hub; and S4: performing algorithm design: designing a decision tree and deep learning combination algorithm, and calculating the number of online hailed rides to be scheduled.

The invention relates to the technical field of communication security, in particular to a security authentication method and system and electronic equipment, and the method comprises the steps: sending an algorithm support list, a mixed key exchange parameter, a first random number and a first certificate request to a second terminal, and enabling the second terminal to generate a second handshake key and a ciphertext; and determining the first handshake key and verifying the target first certificate chain sent by the second terminal by using the first handshake key to obtain an authentication result. Identity authentication is performed based on the mixed key exchange parameter, so that the terminal has the security of quantum attack resistance, and in the whole identity authentication process, the authentication efficiency of the terminal is improved. The leakage of plaintext parameters in the initial handshake message is reduced, and subsequent messages are subjected to different encryption processing, so that the risk of leakage of an identity authentication key is reduced, and the security of identity authentication is improved. Meanwhile, the algorithm selection list is sent in a combined algorithm mode, the algorithm selection matching time of the second terminal can be effectively shortened, and the identity authentication efficiency is improved.

The invention provides a database anti-ransomware method and device based on user SQL (Structured Query Language) feature behavior analysis, and relates to the technical field of database security. The method comprises the following steps: constructing an SQL data set by utilizing a multi-source data aggregation algorithm, a real-time and historical combination algorithm and a data cleaning and checking algorithm; extracting SQL statement structure features according to BERT and a semantic matching method; according to the features, training a user SQL behavior model based on a Transform; in the real-time monitoring stage, a monitoring engine captures a new SQL operation in real time, rapidly extracts features and inputs the features into the trained behavior model for evaluation. Once the deviation between the operation and a normal behavior model exceeds a preset threshold value and suspicious behavior modes such as data encryption, large-scale data deletion or abnormal high-authority operation similar to ransomware are presented, an alarm mechanism is triggered immediately, and a preset protection strategy is executed automatically, so that data loss and business influence are reduced to the greatest extent.

A mechanical online residual life prediction method adopting a model recursion updating strategy comprises the following steps: firstly establishing a degradation model and a model library of mechanical equipment, then determining three thresholds, and determining an initial degradation time and an initial prediction time based on the thresholds; then, on the basis of an observation value sequence after the initial degradation time, model parameters are updated through a maximum likelihood estimation-expectation maximization combination algorithm, and an optimal degradation model is automatically selected through a recursive Bayesian information criterion (RBIC); and finally, according to the selected model and the updated parameters, obtaining a residual life prediction result. The method is driven by the state monitoring data of the mechanical equipment, and the monitoring data is matched with the optimal degradation model in real time by using the RBIC score, so that the degradation condition of the mechanical equipment in the operation process in industrial practice is effectively represented, and the residual life prediction precision of the mechanical equipment is improved.

The invention discloses a zero-trust gateway single packet authentication method and system for a new energy fan control system, computing equipment, a computer storage medium, a computer program product and a chip. The authentication method comprises the steps of generating an authentication material; exchanging and deriving a mixed key; binding Hash calculation is carried out; encrypting and assembling the message; receiving and verifying by the gateway; and binding verification and registration are carried out. The invention relates to a zero-trust gateway single packet authentication method combining a post quantum cryptography algorithm and a national commercial cryptography algorithm. The method is applied to secure communication between a wind power plant and a centralized control center, an SM2, SM3 and SM4 combined algorithm in a national secret system is combined with a post-quantum key agreement algorithm CRYSTALS-Kyber512, identity authentication, encryption and integrity verification are completed through a single message, confidentiality protection and anti-quantum security guarantee under one-time interaction are achieved, and the security of the wind power plant is improved. The method is especially suitable for new energy scenes with wide fan distribution, complex links and high real-time requirements.

The invention provides a collaborative design method for geometric parameters of a sandwich structure based on frequency response, and belongs to the technical field of sandwich structure materials for ships. According to the collaborative design method, a sandwich structure basic model of a carbon fiber composite panel and a honeycomb aluminum core is established, and a basic sweep frequency excitation test of 0.1 Hz to 1000 Hz is carried out; carrying out fusion processing on the basic excitation response data and the supplementary excitation response data through a weighted vector combination algorithm to establish a dynamic response mechanism equation considering the material performance time-varying characteristic; and constructing a geometric parameter collaborative optimization model taking minimization of mass and maximization of rigidity as targets, solving a Pareto optimal solution set by adopting a multi-target genetic algorithm, finally outputting optimized panel thickness, core material height and honeycomb cell size parameters suitable for long-term service in the marine environment, and carrying out frequency response verification test. The technical problem that frequency response characteristic prediction is not accurate due to material performance degradation under the marine environment service condition is solved.

The invention relates to an unbalanced data classification method based on a hybrid model. The method comprises the steps of obtaining a to-be-classified unbalanced data set; calling a twin support vector machine algorithm to form a hybrid model combination algorithm, and performing inner layer iteration; a classification node of the cascade model receives the sample set, a hybrid model combinatorial algorithm allocates an initial weight, and a pre-training set is generated according to the initial weight for training to obtain a component classifier; calculating the AUC value of the component classifier on the pre-selected training set, updating the weight distribution of the sample by taking the AUC value as a reference until the training is completed, and ending the inner layer iteration to obtain the component classifier; integrating all component classifiers into a node classifier to obtain a next sample set, transmitting the next sample set to a next classification node, and performing circulation to obtain the node classifier until the classification node circulation of the cascade model is finished; and integrating the node classifiers into a final classifier, and classifying the to-be-classified unbalanced data set to obtain a classification result. The unbalanced data classification method provided by the invention is high in calculation precision and stable in performance.

The invention discloses an elevation datum plane construction method and system based on a low-order cosine correction Stokes kernel function, a medium and a product, and relates to the technical field of physical geodetic survey. The method comprises the following steps: calculating by utilizing an earth gravitational field model, topographic data and a high-frequency topographic influence combined algorithm to obtain model data, direct influence of topographic compression on ground gravity anomaly and indirect influence of topographic compression on an elevation datum plane; determining an empirical value and a test value of a correction order of the low-order cosine correction Stokes kernel function based on the accumulative error of the model gravity anomaly and the test frequency bandwidth; calculating an empirical elevation datum plane and a test elevation datum plane based on the empirical value and the test value of the correction order by adopting a low-order cosine correction Stokes kernel function; and determining a final elevation datum based on the empirical elevation datum and the test elevation datum. The construction precision of the elevation datum plane can be improved.

The invention discloses an InSAR (Interferometric Synthetic Aperture Radar) land subsidence periodicity and trend feature extraction method considering spatial heterogeneity. According to the method, long-time-sequence synthetic aperture radar image data is acquired, high-precision monitoring is carried out on land subsidence by using a PS-InSAR technology, on the basis, dimension reduction processing is carried out on deformation information by using principal component analysis (PCA), a combinatorial algorithm integrating spatio-temporal spectral clustering and blind source signal separation ICA is provided, different types of subsidence characteristics are efficiently identified, and the accuracy of land subsidence monitoring is improved. According to the method, the periodic characteristics, the tendency characteristics and the randomness characteristics of different types of land subsidence are extracted, the land subsidence can be analyzed more comprehensively, meticulously and accurately, a more reliable and scientific basis is provided for subsidence monitoring, risk assessment and prevention and treatment decision, and the method has a wide application prospect.

The invention provides a financial analysis method and device based on intelligent questions and answers, and the method comprises the steps: capturing user input content through a preset information tool, and obtaining a to-be-processed question; verifying the user permission and the problem range according to the to-be-processed problem; under the condition that the user permission and the question range meet verification conditions, calculating and solving the to-be-processed question through the large combinatorial algorithm model, and displaying a question answer obtained through calculation and solving; wherein the combinatorial algorithm large model is obtained through real-time financial data training. Compared with the mode that a current universal intelligent question-answering system cannot acquire a large amount of effective data in a specific field, cannot deeply answer financial questions in the specific field and cannot provide major decision support, a mainstream interaction mode is provided for inputting the questions and outputting the answers; and the large model of the combinatorial algorithm is trained by accessing real data of an enterprise, so that financial data analysis in the deep professional field is realized.

The invention discloses an intelligent recognition method for a super-heavy beam under a multi-working-condition dynamic condition. The intelligent recognition method mainly comprises the following steps: defining a filter selection element; collecting and processing geometric data of the beam; detecting an intersection wall based on volume collision; through a multi-iteration combination algorithm, screening, classifying and identifying a beam upper wall, a beam lower wall and a beam side structure modeling line; further performing dynamic classification according to whether a beam side has a modeling line, whether a beam wall has a modeling line and a plate, and relative position relations thereof; defining corresponding calculation rules for different types of beams based on specifications and standards, and marking overweight beams; and automatic recognition of the overweight beam is completed. According to the method, automatic recognition work of the overweight beam under the complex actual engineering condition is achieved.

Provided is a system and a method for scheduling. The method includes training a first scheduling policy based on a first weight and training a second scheduling policy based on a second weight that is different from the first weight, calculating a first evaluation result based on the first scheduling policy, calculating a second evaluation result based on the second scheduling policy, determining, by a processing circuit, a third scheduling policy based on inputting the first evaluation result and the second evaluation result into a policy-combination algorithm, calculating a third evaluation result based on the third scheduling policy, based on the third evaluation result, determining a third weight for the third scheduling policy by inverse reinforcement learning or by Bayesian optimization, training the third scheduling policy based on the third weight, and controlling a scheduling process based on the third scheduling policy.

The invention discloses a traffic network-power grid collaborative optimization operation method based on two-way different electricity prices. The object of the invention is collaborative optimization operation of a traffic network-power distribution network coupling network containing a fuel vehicle and an electric vehicle at the same time. According to the method, the supervision efficiency of electric vehicles running in different directions is improved by introducing a differential pricing mechanism, the total social cost is reduced, the complex nonlinear complementary problem of mixed user equalization is effectively solved based on the Frank-Wolfe algorithm, and collaborative optimization operation of a traffic network and power grid coupling system is achieved. The problem that in an existing coupling system, unified charging electricity price is carried out on electric vehicles running bidirectionally on the same road section, and misguidance is generated on driver route selection is solved, the accuracy of electricity price guiding traffic flow is guaranteed, and the hybrid user balance optimization control problem is constructed in combination with a convex combination algorithm; and high-efficiency solving of the problem can be ensured under the condition that the scale of the traffic network-power grid coupling network is relatively large.

The invention discloses a dispersion estimation method for overflow flow and overflow density of a trailing suction dredger, which comprises the following steps of: collecting real-time data during normal dredging and loading operation of the trailing suction dredger, and carrying out de-noising processing; respectively determining a state and an observation equation of an overflow subsystem 1 and a state and an observation equation of an overflow subsystem 2 according to a balance equation of the volume and the mass of a mud tank deposition model and a Wiener process model equation of the overflow flow and the overflow density of a mud-water mixture; a cascade observer of a CD-FPF-UKF combined algorithm is constructed to carry out dispersion estimation on the overflow flow and the overflow density; the observer 1 based on the CD-FPF algorithm estimates the overflow flow by using the state and observation equation of the overflow subsystem 1; and the observer 2 based on the UKF algorithm estimates the overflow density by using the state and observation equation of the overflow subsystem 2 and the overflow flow estimation result of the observer 1. The method has high estimation accuracy and short operation time under a large sampling time interval.

In some implementations, a device may receive a request for cryptographic transmission of payload data. The device may obtain the payload data for encryption. The device may encrypt the payload data, to generate encrypted payload data, using a first encryption key, wherein the first encryption key is configured such that the encrypted payload data is decryptable using a second encryption key that corresponds to the first encryption key. The device may generate tokenized data. The device may combine, using a combining algorithm of a set of combining algorithms, the encrypted payload data and the tokenized data to generate combined data, wherein the combined data is not directly decryptable using the second encryption key. The device may provide the combined data and an indicator of the combining algorithm as a response to the request.

The invention discloses an intelligent transient control method and system for a hybrid power assembly, and relates to the technical field of hybrid power engineering machinery, and the method comprises the steps: obtaining a historical working state data set of the hybrid power engineering machinery; training an improved unscented Kalman filtering algorithm by adopting a historical working state data set; the improved unscented Kalman filtering algorithm is a two-stage combined algorithm adopting a whale algorithm and a moss growth optimization algorithm, and a dispersion degree factor and a prior distribution factor with the minimum fitness function value in the unscented Kalman filtering are generated through iterative search; and on the basis of the required power and the working state of the whole machine at the current moment, a trained improved unscented Kalman filtering algorithm is adopted to predict the change of the transient output power of the power battery and the motor and the change of the transient output power of the engine so as to control the output power of the power battery, the motor and the engine. The dynamic response of the whole machine is improved, and adverse effects on an engine, a power battery and a motor are reduced.

The application discloses an automatic planning method and device for a walking route of a land controllable seismic source, and belongs to the field of physical exploration. The application introduces a TSP idea, and finally obtains a seismic source vehicle driving route which is short in path, less in barrier crossing, less in driving restriction, and in line with the driving operation habit of a driver through steps of constructing a map, setting relevant parameters and weight ratios, and solving the walking route of the land controllable seismic source by using a TNH combination algorithm. The application combines the advantages of a two-approximation algorithm, a Heuristic algorithm and an NSGA_II algorithm to propose the TNH combination algorithm for solving the walking route of the land controllable seismic source, so that the automatic planning of the walking route of the controllable seismic source is realized, the operation efficiency is accelerated, the accuracy of operation results is improved, the calculated route is more in line with the demand of field construction, and the exploration operation is further developed intelligently. The application is applied to the field of physical exploration to plan the walking route of the controllable seismic source.

The invention belongs to the technical field of wind turbine generators, and particularly provides a wind turbine generator fault early warning method and system based on an optimized deep belief network, and the method comprises the steps: obtaining SCADA data based on a data collection and monitoring control SCADA system installed in a wind field; wherein the SCADA data comprises wind field surrounding environment parameters and wind turbine generator component performance parameters; carrying out abnormal value detection on the SCADA data by utilizing a KNN-box graph combination algorithm; performing parameter optimization on the deep belief network DBN in combination with a sparrow search algorithm SSA and a particle swarm optimization algorithm PSO, and constructing an SSA-PSO-DBN-based wind turbine generator fault early warning model; based on the wind turbine generator set fault early warning model, early warning of the wind turbine generator set fault is completed. The algorithm provided by the invention has relatively high precision in judgment of the running state of the wind turbine generator, can further reduce the risk of misjudgment, and can realize early warning of the fault of the wind turbine generator at the same time.

The present application provides a method and system for building change detection based on multi-source real-scene three-dimensional models. The method includes: obtaining the triangulation topology data of two-phase real-scene three-dimensional models within the area to be detected, and performing preprocessing and standardization processing; using plane-elevation hierarchical registration technology for automatic registration to achieve coordinate unification without manual intervention; using spatial index difference calculation to identify the three-dimensional change areas of the two-phase real-scene three-dimensional models, and optimizing the three-dimensional change areas by using a multi-scale dilation-erosion combination algorithm; using three-dimensional feature dual-channel filtering for the optimized three-dimensional change areas to verify real building changes; generating four-dimensional spatio-temporal results and outputting a visualization model including elevation change values, material types, and three-dimensional reconstruction parameters. The present application overcomes the machine-readable problem of subtle changes in buildings in large-scale real-scene models, and provides a highly reliable three-dimensional quantitative analysis tool for urban illegal construction monitoring and urban safety management.

The invention relates to a method for improving inertial navigation / satellite integrated positioning precision, which comprises the following steps of: 1, measuring a relative distance between satellite navigation and inertial navigation, and transmitting the relative distance to equipment for storage; 2, measuring the relative distance between the inertial navigation and the measurement point, and transmitting to equipment for storage; 3, accessing a synchronization signal PPS to ensure that the type of the synchronization signal is effective; 4, latching the longitude, latitude and height of the current inertial navigation when the inertial navigation software receives the PPS signal; 5, after inertial navigation software receives the PPS signal, a first frame of satellite navigation positioning message is received, the current satellite navigation position is stored, satellite navigation rod arm compensation is carried out to the inertial navigation installation position, and then the inertial navigation positions in the step 4 are used for jointly calculating the quantity measurement of the Kalman filtering algorithm; 6, updating the Kalman filtering algorithm after the measurement is updated; 7, after the step 6 is carried out for a certain time, when inertial navigation outputs the position outwards, measuring point rod arm compensation is carried out, a compensation process is completed, and the step 4 to the step 7 are executed repeatedly in the follow-up process. The method can improve the precision of the measurement point position output by the inertial navigation / satellite combination algorithm.

The present application relates to the technical field of communication security, and in particular to a security authentication method, system and electronic device, comprising: sending an algorithm support list, a hybrid key exchange parameter and a first random number, a first certificate request to a second terminal, so that the second terminal generates a second handshake key and a ciphertext; determining a first handshake key and verifying a target first certificate chain sent by the second terminal using the first handshake key to obtain an authentication result, the present application performs authentication based on the hybrid key exchange parameter, so that the terminal has security against quantum attacks, reduces the leakage of plaintext parameters in the initial handshake message in the whole identity authentication process, uses different encryption processing for subsequent messages, reduces the risk of identity authentication key leakage, and improves the security of identity authentication. Meanwhile, the algorithm selection list is sent in the form of a combination algorithm, which can effectively reduce the algorithm selection matching time of the second terminal and improve the identity authentication efficiency.

A network element (NE), such as an access and mobility management function (AMF) or a radio access node, and a user equipment (UE) which use a combined integrity and encryption (CIE) algorithm to prov