69 results about "Random response" patented technology

The invention discloses a KCBMA algorithm-based windmill bridge system safety assessment method, which relates to the technical field of windmill bridge coupling systems, combines a Kepler optimization algorithm (KOA) with a convolutional neural network-bidirectional long-short-term memory network (CNN-Bi-LSTM-MA) under a multi-head attention mechanism, adaptively searches an optimal hyper-parameter combination of the CNN-Bi-LSTM-MA network through the KOA, and provides a safety assessment method for a windmill bridge system. Constructing a neural network prediction model with dynamic adaptive capacity; the Bi-LSTM unit performs modeling by fusing the randomness characteristics of wind load excitation and system parameters, so that a numerical model can effectively represent the randomness of a wind-vehicle-bridge system and predict the random response of the wind-vehicle-bridge system. According to the method, the dynamic interaction among the wind-vehicle-bridge structures is integrated into the neural network model, the modeling time is remarkably shortened by using the KOA, the modeling accuracy is improved, the calculation cost is reduced, and the system response is more accurately predicted.

The invention provides a bridge pier nonlinear earthquake random response analysis method based on a BWBN model, and belongs to the field of civil engineering structure random vibration analys.The method comprises the steps that discretization processing is conducted on a concrete bridge pier structure, and a finite element nonlinear analysis numerical model is constructed; constructing a BWBN model by combining linear and nonlinear differential equations, setting a hysteresis parameter value of the BWBN model, simulating by adopting an Euler-Bernoulli beam unit, and establishing a degraded beam finite element model; obtaining a unit hysteresis vector, constructing a system motion balance equation, solving an equivalent linearization coefficient, constructing a covariance matrix of random response of the concrete pier structure, performing random response analysis on the concrete pier structure, and exploring typical working conditions of random excitation. According to the method, the operation time is shortened, the calculation precision is improved, and meanwhile, the response characteristics of the reinforced concrete pier structure under nonlinear earthquake random excitation can be truly represented.

The invention discloses a V2G electric power data aggregation method and system based on local differential privacy. The method comprises the following steps: acquiring a signal of charging electric quantity of an electric vehicle and generating a charging data report; based on the privacy data in the collected data report, the charging pile adopts a stepped random response mechanism to disturb the charging starting time, and adopts Laplace noise to disturb the charging duration and the charging amount to obtain disturbed power utilization data; and aggregating the disturbed power consumption data to obtain a power consumption condition curve, and adjusting a power supply strategy according to the power consumption condition. According to the invention, sensitive information of a user is protected while power data analysis is carried out, and the security of real data is ensured.

The invention discloses an analysis and design-based topological optimization method for an ocean engineering structure under continuous iterative random excitation, which takes a dynamic response displacement root-mean-square at a specified key position of complex random excitation as a target function, and adopts a virtual excitation method to efficiently solve structural dynamic random response. In order to overcome the problem of huge calculation amount consumption of structural random response dynamics optimization repeated modal solution, a continuous iterative random dynamic response optimization strategy based on analysis and design is provided, and based on an adjoint method, the efficient optimization sensitivity of structural random dynamic response is deduced, and the optimization sensitivity of the structural random dynamic response is improved. An optimization algorithm based on a moving asymptote method is adopted to solve an optimization problem. Optimization examples show that the virtual excitation method based on analysis and design can obtain almost the same optimization design on the basis of having the remarkable calculation efficiency advantage as the traditional double-circulation virtual excitation method.

The invention discloses a complex equipment reliability optimization design method based on a random agent model, belongs to the field of complex equipment reliability optimization design, and effectively constructs a black box agent model containing the influence of unknown and uncontrollable input random parameters on the response of complex equipment. And reliability evaluation is carried out on the complex equipment component by combining a Monte Carlo method, and finally reliability optimization design is realized. The invention provides a complex equipment reliability optimization design method considering implicit input parameter uncertainty, which comprises the following steps of: representing a random field of random response of a complex equipment part through Carloam-Roseli expansion, and agenting the represented random field by combining polynomial chaos expansion and a kernel density estimation method; therefore, the random behavior reproduction of the complex equipment part response under the implicit random parameter influence is realized. The method can be used for searching the optimal design under the influence of unknown and uncontrollable random input parameters in the performance response of complex equipment.

The invention relates to a medical block chain data sharing method based on dual quality thresholds and federated learning, and belongs to the technical field of computers. The method comprises the following steps that: 1, a publishing node publishes a task and establishes a committee; 2, a participating node downloads global model parameters from the block chain, and local model training is carried out in combination with random response and a differential privacy technology; 3, the trained nodes upload local model parameters to the block chain, the committee elects mining nodes to download all transactions from the block chain and calculates the quality, and only nodes passing a quality threshold can participate in model aggregation and calculate contribution values as aggregation weights; 4, updating the reputation information of each node by the mining node, and packaging the reputation information and the global model parameters into a new block; and 5, other committee nodes verify the new block, the new block is chained after verification is passed, and the committee composition is adjusted at the same time. According to the method, the poisoning attack problem existing in federated learning can be resisted, meanwhile, data privacy is protected, and the influence of noise on model performance is reduced.

The invention belongs to the field of spinning electronics, and particularly relates to a method for constructing a magnetic golf version based on Skyrmion. A traditional golf plate is a classical statistical model for researching particle stochastic dynamics under ideal equal probability hypothesis, and an artificial spin network is introduced into an ultrathin ferromagnetic film, and is similar to a nanoscale magnetic golf plate. The result shows that when the external magnetic field oscillates at the lowest frequency of Skyrmion rotation, the output distribution presents standard Gaussian distribution, and the result of a traditional golf plate is reproduced. Random response of the magnetic golf plate can be achieved by adjusting the direction of the applied magnetic field and modifying the local geometry. It is notable that when a magnetic field of higher frequency is applied, the distribution deviates from the Gaussian distribution, which can be interpreted as a disruption of an equal probability hypothesis due to a phase gradient between adjacent skyrmions. The method provides a basis for understanding the random characteristics of the Skyrmion cluster and potential application of the Skyrmion cluster in future neural network calculation.

This application relates to the technical field of recommendation systems. This application discloses a general lossless privacy protection recommendation method, device, equipment and medium, which can protect user privacy in the recommendation system, improve the accuracy of prediction results, and improve the generality of the privacy protection recommendation method. The method includes receiving the first grouping information sent by the server; performing data exchange processing on all public keys in the first grouping information by using an item exchange mechanism based on random response to obtain target perturbed data; performing encoding processing on each element in the target perturbed data by using a common item marking mechanism based on PSI to obtain target encoding marks; sending the target encoding marks to the server; receiving the first information to be forwarded sent by the server, and performing parsing processing on the first information to be forwarded to obtain first inference data; performing inference processing on the first inference data by using the inverse process of the item exchange mechanism based on random response to obtain target recommended items.

The present application belongs to the field of privacy communication and communication security assurance, and discloses a two-way secure communication method based on a random response mechanism. The secure communication method checks whether the receiving user and the sending user are legal by sending and receiving pulse check signals between the sender and the receiver. It is a two-way secure communication method in which the sender and the receiver authenticate and approve each other, and the legality of the other party can be determined synchronously. Even if an eavesdropper or a forger accidentally passes an identity authentication, the communication security has enough fault tolerance space, and it is difficult for an illegal user to pass the authentication continuously for many times, so that the sender or the receiver will terminate the communication, thereby ensuring the security of information communication.

This invention discloses a robust design method for gas turbine performance based on multi-source stochastic response coordination, relating to the field of gas turbine performance design. The method sequentially performs three types of stochastic influence analysis: design model, manufacturing, and usage process, constructing probability density functions for core performance parameters respectively. Based on the task phase, it determines the risk levels and weights of various stochastic factors, fusing them to generate a comprehensive probability density function. With the goal of minimizing the dispersion and optimizing the expected value of the comprehensive probability density function, it combines the constraints of component thermodynamic state parameters to solve the optimization model, obtaining the optimal combination of performance parameters. This invention achieves multi-source stochastic coordinated quantification and characterization, improving the robustness of gas turbine performance, solving the problems of conservative design and poor adaptability to operating conditions in traditional methods, and enhancing its operational safety and reliability.

A client device is fabricated using a semiconductor fabrication process. One or more uncontrollable random physical processes in the semiconductor fabrication process can cause small differences between the client device and other client devices. When the client device is presented with a challenge from a server device, the client device generates a random response that depends on its physical properties. The server device stores this random response as a part of a virtual PUF circuitry storage device having other random responses from the other client devices. The server device uses the random response of the client device stored in the virtual PUF circuitry storage device for one or more encryption algorithms to encrypt information to be provided to the client device.

The application discloses a user preference prediction method for sensitive behavior data protection and relates to the technical field of big data analysis. The application introduces the localized differential privacy of random response in the construction of dynamic characteristics of preferences, protects the security of potential feature data of the preferences, fuses a time decay factor in the process of learning dynamic characteristics, optimizes the dependency relationship between features in different periods, and realizes user dynamic preference prediction under dynamic change and sensitive behavior protection, so that the application realizes the construction of a privacy protection mechanism for sensitive behavior of users and retains the availability of data, and improves the accuracy of future preference prediction.

The invention particularly relates to random response analysis of a wake flow type hybrid energy collector under fluctuating wind excitation, which comprises the following steps: on the basis of a simplified model that a static upstream bluff body is arranged in front of a main bluff body, and periodic vortex shedding wake flow force is utilized to excite vibration, establishing an equivalent electromechanical coupling dynamic model; a random phase is introduced into wake-induced vibration external excitation to represent random fluctuation of wake force under the fluctuating wind; after dimensionless and parameter scale re-calibration are carried out on the model, a multi-scale method is adopted to derive an amplitude-phase slow modulation equation set and first-order asymptotic analysis response expressions of displacement, voltage and current; further linearizing the slow-varying equation under a steady-state condition, solving a second-order statistic of amplitude and phase by combining a moment method and an Ischi differential rule, and determining steady-state moments of the output voltage and the output current and average output power according to the second-order statistic; and the output performance rapid evaluation and parameter design support of the wake flow type hybrid energy collector under random excitation are realized.

The invention relates to the technical field of data privacy protection, and provides a sketch-based low-frequency item frequency estimation method under local differential privacy, which comprises the following steps that: a user constructs a multi-layer sketch structure based on a local data set, and disturbs column coordinates of each layer of sketch by applying a generalized random response mechanism to meet local differential privacy constraints; the server receives disturbed row coordinate and column coordinate pairs uploaded by all users, aggregates the disturbed row coordinate and column coordinate pairs into a global multilayer sketch to construct a global multilayer sketch matrix, calibrates observation count of each layer of the global multilayer sketch matrix, estimates the real frequency of each layer of the global multilayer sketch matrix, and calculates the real frequency of each layer of the global multilayer sketch matrix based on the calibrated frequency estimation of each layer. And the query item is subjected to joint calculation to obtain global frequency estimation of the query item. According to the method, by introducing a local differential privacy mechanism and optimizing a sketch structure, the effect of remarkably improving the frequency estimation precision of the low-frequency data item while strictly protecting the individual privacy of the user is achieved.

This invention provides a local differential privacy collaborative sampling data collection method and system resistant to poisoning attacks, belonging to the field of information security and privacy protection technology. The scheme compares the single-dimensional probability distribution reported by the user terminal with the median probability distribution to identify and eliminate abnormal reported data, thereby effectively suppressing data poisoning attacks initiated by malicious user terminals. Subsequently, under the constraint of local differential privacy, combined with a generalized random response mechanism and a collaborative sampling strategy, multidimensional data is sampled differentially to achieve more accurate frequency estimation. The scheme of this invention improves the privacy protection strength and the accuracy of statistical results in multidimensional data collection without relying on a trusted third party.

A method for analyzing the nonlinear random vibration and seismic vulnerability of bridge structures was developed. A near-fault random seismic motion model containing velocity pulses was established, and the model parameters and their probability distribution were identified, generating near-fault random seismic excitations. Based on the principle of probability conservation, the probability density integral equation for the bridge system under near-fault random seismic excitations was derived. A nonlinear finite element model of the bridge structure was established using the open-source software OpenSees. Using the direct probability integral method, the dynamic equations and the probability density integral equation for the bridge system under near-fault random seismic excitations were solved simultaneously, efficiently and accurately obtaining information such as the probability density function, mean, and standard deviation of the random response of the bridge structure. Finally, based on the definition of seismic vulnerability analysis, the equivalent extreme value mapping was combined with the direct probability integral method to conveniently calculate the dynamic reliability values of the bridge structure under different earthquake intensities, thereby obtaining the seismic vulnerability curve of the bridge structure.

The invention discloses an Internet of Things medical equipment fragmentation encryption system and method, and particularly relates to the technical field of fragmentation encryption, and the method comprises the steps: dividing medical equipment according to a use scene, and endowing data information of different scenes with different scene weights; calculating the priority of each piece of data information according to the information entropy and the scene weight; dynamically adjusting fragmentation parameters according to the network signals and the priority of each piece of data information; different fragmentation strategies can better adapt to different data information; the transmission process is smoother; a local differential privacy technology is used, a random response mechanism is used in extracted data information features, data information subjected to fragmentation disturbance is transmitted through multiple paths, scores of all the paths are calculated according to network signals, and fragmentation-path mapping is formed; different paths correspondingly upload the fragment data of different fragment parameters.

The invention provides a method for calculating photoresist state change time in PEB in real time. Comprising the following steps: a preposition step: uniformly or non-uniformly dividing a three-dimensional data structure of photoresist film information data which at least comprises spatial position information into a lattice tendency function and a state tendency function of a plurality of cells to confirm an overall tendency function of the three-dimensional data structure; circulating the steps L1-L2, wherein the step L1: in the process of simulating the PEB, sequentially confirming a cell, a reaction type and / or diffusion with state change by introducing an overall tendency function, a lattice tendency function and a state tendency function of a simulation random number r; forming a simulation result or triggering a boundary condition to form the simulation result; updating and forming an overall tendency function, a lattice tendency function and a state tendency function according to a simulation result; wherein 0 lt; rlt; 1; and step L2, calculating the time taum of the next state change by using a formula (1). The method has the beneficial technical effects that the random reaction diffusion phenomenon in the PEB process can be simulated at high precision from the molecular level and can be output in real time.

This invention discloses a structural topology optimization design method considering the uncertainty of multi-peak loads, belonging to the field of uncertain structural optimization design. It mainly includes three parts: establishing a multi-peak load uncertainty model, solving for the random response, and solving for the optimization formula. This invention describes load uncertainty using a Gaussian mixture model, solves for the Gaussian mixture model coefficients based on the EM algorithm, and establishes a multi-peak load distribution probability model. By decorrelating random variables, sparse grid technology is used to solve for the mean, standard deviation, and sensitivity of the response, thereby solving for the topology optimization model considering the multi-peak load uncertainty. This method addresses the problem of low structural product reliability that may occur in structural designs considering multi-peak load uncertainty by establishing an accurate probabilistic model of multi-peak load uncertainty. This method is simple and easy to implement, readily applicable in engineering, and can improve the design efficiency of structural designers considering complex load conditions.

The invention relates to privacy protection, in particular to an AMI network-oriented portrait perception adaptive privacy protection method, which comprises the following steps: quantifying the importance of users through a fuzzy comprehensive evaluation algorithm, and providing different protection levels for different users according to the importance, the higher the importance is, the higher the protection level is; distributing a privacy budget for each user according to the protection level of the user; based on the distribution privacy budget, adopting a square wave mechanism to disturb data of a numerical value type in the original data of the user; on the basis of distribution of privacy budget, calculating a theoretical mean square error of generalized random response and optimal unary coding, and selecting a mode with a relatively small error to disturb discrete type data in the original data of the user; and after the disturbed data and the privacy budget thereof are uploaded to the server, the server recovers the user data with the same privacy budget by adopting a hierarchical EMS algorithm. According to the method, the non-uniform transfer matrix and the virtual grid projection are constructed, so that seamless fusion of different privacy budgets and different discrete granularity data is realized.

To provide an in-store showcase control system configured to automatically set a case address for each of a plurality of showcases installed in a store, without requiring an operator to randomly set serial numbers to the showcases in advance prior to shipping the showcases to the store.SOLUTION: In an in-store showcase control system 100, a control apparatus 20 is configured to transmit, to each of a plurality of showcases 10, an address setting command 31 to set a case address 30 for identifying each of the showcases 10, on the basis of random response delay time information 40 transmitted from each of the showcases 10 at timings based on response delay time of the response delay time information 40 generated randomly in each of the showcases 10.SELECTED DRAWING: Figure 3

The application discloses a kind of based on adaptive high-dimensional data local differential privacy protection method, using rough set theory and mutual information, the data of different relevance and sensitivity are clustered grouping, different grouping is used different random response probability, permanent random response and temporary random response are carried out.Local differential privacy processing data, using SNE method for dimension reduction and adaptive sampling gradient optimization in server end, with low-dimensional data joint probability distribution approximates the joint distribution of all attributes, according to the sampling strategy and the approximate joint distribution constitutes release dataset.The application solves the problem of high-dimensional data with dimension disaster and local differential privacy combination and maximum degree maintaining data relevance, and more reasonably allocates privacy budget according to the different data sensitivity to some extent, improves data availability and reduces communication cost.

This invention discloses a local differential privacy trajectory publishing algorithm oriented towards regions of interest, comprising the following steps: Step 1, extracting a set of safe regions from the original user trajectory; Step 2, traversing each trajectory point in the original user trajectory in chronological order, and further dividing the trajectory points falling into the safe regions to obtain discrete candidate domains and nearest candidate points; Step 3, performing distance-layered restricted random response within the discrete candidate domains to generate perturbation points, wherein the perturbation points and trajectory points not falling into any safe regions constitute the published trajectory. This invention features a finer-grained trade-off between privacy strength and trajectory availability.

This invention belongs to the field of power system demand-side management technology and discloses a probabilistic assessment method for load adjustability potential considering dual uncertainties. The method includes: constructing adjustability potential models for five load types: air conditioning, cold chain, energy storage, electric vehicles, and data centers; determining the random parameters of external influences on each load and quantifying their probability distribution based on historical data; introducing random execution variables for each load type to describe the uncertainty of execution behavior with probability distributions, thus obtaining a more realistic adjustability potential; performing random sampling calculations on the above models and parameters using the Monte Carlo method to aggregate and generate a total adjustability potential sample; and performing fitting analysis on the sample to obtain the probability function of the system's adjustability potential and conduct multi-dimensional evaluation. This invention achieves the quantification of load adjustability potential uncertainty through a three-layer probabilistic modeling of "physical behavior - random influence - random response," providing decision support for optimized power grid operation.

The present disclosure provides a random number generator and a random number generation method, which relate to the field of computer technology. The random number generator includes: a random number generation module, a data acquisition module, and a power supply module; the power supply module is used to supply power to the random number generation module and the data acquisition module; the random number generation module is used to generate a random digital pulse signal based on the random response delay and the random low-resistance state resistance value of the memristor; the data acquisition module is used to generate a random number sequence according to the random digital pulse signal. In this way, by simultaneously introducing the random response delay and the random low-resistance state resistance value of the memristor as entropy sources, the random resources of the memristor are fully utilized, the circuit structure is simplified, the circuit reliability, randomness, and random number rate are improved, and the application scenarios of the random number generator are expanded.

The invention discloses a multivariable time point process analysis method based on two-dimensional local differential privacy, and relates to the technical field of federated learning and privacy protection. The method comprises the following steps: setting a total privacy budget on a client side and distributing the budget as a time and type dimension budget; a delta t-SAHRP-LDP order-preserving perturbation mechanism is adopted in the time dimension, interval scale adaptive noise adding, minimum right lower bound constraint and dynamic anchor point resetting are combined, and a time sequence after perturbation is generated; and generating a disturbed type sequence in the type dimension by adopting a random response mechanism. A client uploads an intermediate representation and an alignment scale based on disturbance data, and a server establishes a cross-end alignment and neighborhood relationship only according to the intermediate representation and the alignment scale, generates extension and neighborhood context features and returns the extension and neighborhood context features. And the client performs prediction and training in combination with the local real representation and the cross-end context. According to the method, on the premise of not exposing an original sequence, the leakage risk of sensitive time rhythm and type distribution is effectively reduced, and meanwhile, the accuracy of event prediction is improved by utilizing cross-client collaborative information.

The present invention discloses a method, device and medium for constructing a link prediction model that satisfies local differential privacy based on a personalized sampling random response graph structure perturbation algorithm. The method belongs to the field of data security and solves the problems of graph structure edge density expansion when a random response mechanism is directly used, which cannot retain important community features on the graph, as well as privacy leakage during the model learning process. The method designs two rounds of interaction between users and collectors. In the first round of interaction, the user end uses personalized sampling technology and a random response mechanism to perturb the link relationship between other users and sends it to the collector. The collector aggregates the link relationships sent by all users and uses a community discovery algorithm to divide the communities to which the users belong. In the second round of interaction, the user end performs personalized sampling random response based on the community division results and then sends the perturbed link relationship to the collector. The collector aggregates the link relationships sent by all users to obtain the final graph adjacency matrix. The present invention is suitable for graph privacy protection scenarios.

The invention discloses a multi-time scale response analysis method and device based on flexible resource random characteristics. The method comprises the following steps: acquiring flexible resource random response characteristics; establishing a flexible resource multi-time scale response model based on flexible resource random response characteristics; based on the flexible resource multi-time scale response model, a random response surface method is used to calculate a power grid electric energy quality index after the power grid node accesses the flexible resource; and analyzing the influence of the accessed flexible resources on the power quality of the power grid based on the calculated power quality index of the power grid, and optimizing a scheduling strategy of the flexible resources. The method optimizes the efficiency of the flexible resources participating in the power quality adjustment, and provides support for the precise regulation and control of the flexible resources and the safe and stable operation of a power grid.

The invention discloses a local differential privacy protection mechanism supporting data authenticity verification, and relates to the technical field of data privacy protection, and the mechanism comprises the steps: obtaining a to-be-noised data set, and converting the to-be-noised data set into a binary bit vector form through a Bloom filter; mapping the data into a binary bit vector B with the length of k through a bloom filter by using h hash functions; and performing permanent random response noise addition processing on the binary bit vector B to generate a binary report B'with the length of k, and replacing the original data of the data holder with the generated binary report B '. Differential privacy and digital signature technologies are combined, the requirement of privacy protection of the data holder is met, meanwhile, the requirement of the data receiver for confirming the authenticity of the data is met, and the requirements of the data holder and the data receiver can be further met.

The invention relates to the technical field of train control, and provides a rail transit application-oriented inquiry-response type distance measurement method and device and a medium, and an inquiry machine and a response machine are respectively arranged at a vehicle-mounted radar terminal and a trackside radar terminal; the method comprises the following steps: an interrogator and a responder calculate respective signal processing fixed time delays; the interrogator transmits an interrogation signal to the responder; the responder receives the inquiry signal and generates and transmits a response signal after the first correlation peak is detected; a responder signal processing fixed time delay and a random delay time delay are added into the response signal; and the interrogator receives the response signal, and after a second correlation peak is detected, the measurement distance is calculated based on the moment corresponding to the correlation peak of the response signal, the interrogator signal processing fixed time delay, the responder signal processing fixed time delay and the random response time delay. According to the invention, continuous, real-time and high-precision distance measurement can be realized, the distance measurement is not influenced by the environment, the driving safety capability of the train is improved, and the accident occurrence probability is reduced.