62results about How to "Increase uncertainty" patented technology

The invention discloses a city planning information display method and system based on digital twinning, and relates to the technical field of city planning. Static data and dynamic data of a city are collected, a three-dimensional model of the city is constructed through the static data, and the dynamic data and the three-dimensional model are combined to construct a digital twinning model of the city; the method comprises the following steps: setting a random data generation pool to generate random data, importing the random data into a digital twinborn model, and monitoring and optimizing a chaos current situation in the digital twinborn model to obtain an optimization scheme; by constructing a public voting platform, public opinions are imported into city planning to obtain a final optimization scheme; according to the method, the digital twinborn model of the city is constructed, more random scenes are provided for city planning by using the random data generation pool, potential changes and uncertainty of the city are fully simulated, and in combination with public opinions, the perspectiveness and flexibility of the digital twinborn technology in the city planning are improved, and a new direction is brought to the city planning.

The invention discloses a hydroelectric generating set fault diagnosis method based on a chaos Kepler optimization algorithm, and belongs to the technical field of hydroelectric generating set fault diagnosis. A Tent chaos function is introduced to replace an initial population of a Kepler optimization algorithm (KOA), and by improving the uniformity and uncertainty of the population, the convergence speed of the KOA algorithm is increased, and the global search capability is improved. An improved Kepler optimization algorithm is adopted to optimize hyper-parameters of the BiLSTM, a BiLSTM prediction model CKOA-BiLSTM of the hydroelectric generating set is established, the robustness and generalization ability of an existing model are improved, and the model is made to be suitable for processing complex nonlinear fault signals of the hydroelectric generating set. The model shows the optimal diagnosis effect on recognition of complex fault types, and the research can be used as a beneficial supplement of an existing hydroelectric generating set state monitoring and fault diagnosis system.

The invention discloses a multi-modal state space integrated image segmentation method based on uncertainty estimation. The method comprises the following steps: acquiring image data and text data corresponding to the image data; a CLV-SSIF model is utilized, according to the image data and the text data, the image is segmented, the CLV-SSIF model comprises a multi-modal space integration assembly and a multi-expert uncertainty optimization assembly, and the multi-modal space integration assembly comprises an image encoder, a text encoder and a multi-modal interactive guide decoder; and the multi-expert uncertainty optimization component is used for generating an initial segmentation result of the image and generating expert uncertainty estimation by using the multi-expert hybrid model, and then optimizing the initial segmentation result according to the expert uncertainty estimation. According to the method, the accuracy of image segmentation is improved.

The invention discloses a flexible joint collaborative robot control method based on self-adaptive jump and application. The control method comprises the following steps: calculating a combined error; calculating a feed-forward compensation item and a feedback control item; adding a feedforward item and a feedback item for control; wherein the combined error comprises first-order to third-order errors; the self-adaptive jump control comprises a PID subitem and an RISE subitem, the RISE subitem comprises a self-adaptive sliding mode gain, and the self-adaptive sliding mode gain is related to a second-order error and a first-order differential of the second-order error. According to the method provided by the invention, the calculation complexity is reduced, and the real-time calculation capability of the system is improved, so that the control system can keep a relatively high response speed under a high-dynamic working condition; due to the self-adaptive jump design, the resistance of the system to uncertainty and external disturbance is improved, and the high-frequency flutter problem caused by the flexible joint is remarkably reduced; and the adjusting process of the control parameters is simplified, and the method is particularly suitable for rapid deployment of the multi-degree-of-freedom collaborative robot.

The utility model discloses a controllable flexible pressing device applied to microneedle patch skin surface drug delivery, and belongs to the technical field of drug delivery, the controllable flexible pressing device comprises a microneedle patch, an electrostatic adsorption membrane, a rigid support body, an air bag and a thin film pressure sensor, the microneedle patch is attached to the skin surface, and a needle head is downward; the electrostatic adsorption membrane is arranged above the microneedle patch; the rigid support body is arranged on the electrostatic adsorption membrane, and an air bag mounting cavity is formed in the middle of the rigid support body; the air bag is arranged in the air bag mounting cavity; and the thin film pressure sensor covers the air bag. The device is simple in structure and convenient to operate, the application direction, the change rate, the magnitude and the action time of force in the dosing process can be controlled, the penetration depth of the microneedle is influenced, and then the positive influence on the experimental result and the clinical effect is generated.

The invention belongs to the technical field of digital economy monitoring, and particularly relates to a digital economy monitoring method based on a block chain technology, and the method comprises the following steps: 1, constructing a digital economy co-creation platform based on a block chain, and enabling the digital economy co-creation platform to comprise a plurality of participants and a supervisor; 2, a plurality of participants jointly generate values through resource integration in the value co-creation process based on the digital economic co-creation platform, and a value network structure is constructed based on a block chain; 3, in the value network structure, dividing a value co-creation process into a value resource selection stage, a value resource acquisition stage and a value win-win stage through analysis and function definition of a resource subject; and step 4, the supervisor supervises whether the establishment process of the digital economic co-creation platform and the value co-creation process of the plurality of participants based on the digital economic co-creation platform are abnormal in real time. According to the invention, all participants share innovative resources, and the resource sharing safety performance is high.

The invention discloses a regional ecological environment quality evaluation method based on neighborhood granular fuzzy c-means clustering, and belongs to the technical field of electrical digital data processing, and the method comprises the steps: calculating and reconstructing a remote sensing time sequence MODIS data set based on a cloud platform, standardizing ecological factors, dividing ecological factor remote sensing images into n categories based on neighborhood granular fuzzy c-means clustering, and obtaining a comprehensive remote sensing ecological index PRSEI based on the MODIS by using an improved entropy weight method, and obtaining mining area ecological environment quality changes in year intervals according to the PRSEI of the research area. According to the method, the entropy weight method and the neighborhood fuzzy c-means clustering algorithm are effectively fused, all remote sensing pixel information of all ecological factors is reserved, the process is clear, and complex system problems such as remote sensing ecology and the like can be better analyzed and solved.

The invention discloses an equipment trusted boot verification system, method and device and a chip, and belongs to the technical field of information security. The system comprises a main control chip used for reading firmware in a memory, calculating a target metric value of the firmware and sending the target metric value to a security chip; and the security chip is used for verifying the target metric value according to the reference metric value of the firmware. According to the method and the device, the firmware in the memory is read through the main control chip, the firmware does not need to be read by a security chip, various different external memories can be adapted, and the verification efficiency is improved; the main control chip calculates the target metric value of the firmware, the calculation speed is higher than that of a security chip, and the verification efficiency is further improved; besides, according to the cooperative mode of the main control chip and the security chip, the security chip does not need to read firmware from the memory in the verification process, so that a switch selection circuit between the security chip and the memory is reduced, and the overall cost is saved.

The invention relates to the technical field of voltage optimization control of a power system, in particular to a multi-agent self-discipline collaborative optimization method and system for multi-region reactive voltage control, and provides an optimal reactive voltage optimization decision method for establishing a data interaction model, setting a data interaction mode and researching a power distribution network. By optimizing distribution of reactive power, the active loss of the power distribution network is reduced, the economical efficiency of the power system is improved, and the service life of equipment is prolonged; by using a deep reinforcement learning algorithm, effective adjustment of voltage is realized, and node voltage is stabilized; a deep reinforcement learning method is adopted, so that the influence of model errors is reduced, the calculation speed and the real-time response capability are improved, and the calculation cost is reduced; through continuous interaction with actual power grid data, the intelligent agent can cope with the uncertainty of distributed new energy, energy storage and flexible load power generation and power utilization, and the stability and reliability of the system under various complex conditions are improved.

The invention relates to the technical field of image processing, and particularly discloses a virtual clothes changing system based on an AI algorithm, and the system comprises a preprocessing module which carries out the filling, size adjustment and normalization processing of a first image; obtaining a user portrait and obtaining a target image; the visual large model processing module is used for mapping the second clothing image, the noise image and the target image to a high-dimensional space; performing feature extraction on the second clothing image in the high-dimensional space to obtain a first feature; splicing the noise image and the target image in the high-dimensional space to obtain a standard image, and performing feature extraction on the standard image to obtain a second feature; fusing the first feature and the second feature, and obtaining a virtual fitting image; and the post-processing module is used for obtaining a fitting portrait and obtaining a virtual fitting effect image according to the fitting portrait and the user background. According to the method, various types of clothes can be stably tried on, and meanwhile, natural textures, wrinkles and actual lengths of the clothes in a real dressing state are presented.

The invention discloses a false data injection detection method and system based on a bidirectional long short-term memory network, and belongs to the field of distributed automation system and FDIA detection in a new energy power grid, and the method comprises the steps: constructing a new energy power grid load redistribution attack model based on local information; constructing a new energy power grid false data injection detection model based on a bidirectional long short-term memory network; taking the output of the constructed new energy power grid load redistribution attack model as the input of a false data injection detection model; acquiring data of a new energy power grid; new energy power grid data are incorporated into an IEEE node system to verify the adaptive capacity of the detection model after renewable energy integration; operating data of the power system are collected in real time, preprocessed and input into the verified false data injection detection model, whether the power system is abnormal or not is judged according to a detection result output by the false data injection detection model, and corresponding response measures are taken.

The invention discloses a side channel attack resistant binomial sampling circuit applied to a post quantum cryptography algorithm. The side channel attack resistant binomial sampling circuit comprises a random number generation unit, a binomial sampling unit and a control logic unit, the random number generation unit is used for generating a pseudo-random number according to input data; the pseudo random number comprises true data and false data; the binomial sampling unit is used for synchronously carrying out binomial sampling on true data and false data; and the control logic unit is used for controlling the random number generation unit and the binomial sampling unit to operate according to an external instruction. According to the side channel attack-resistant binomial sampling circuit applied to the post-quantum cryptographic algorithm, the analysis difficulty of an attacker is increased by generating a pseudo-random number, and meanwhile, the attacker is interfered by synchronously sampling true data and false data, so that the protection on the side channel attack is jointly realized, the security of a Kyber cryptographic system is effectively improved, and the security of the Kyber cryptographic system is improved. And the risk of side channel attack is reduced.

The invention discloses a method for simulating halogen plasma etching silicon or silicon dioxide through molecular dynamics. The method comprises the steps of modeling through a silicon or silicon dioxide substrate material, performing LAMMPS software initialization setting, performing plasma etching circulation, and performing data output and analysis processing. According to the method, a plasma-surface interaction mechanism is simulated on the atomic scale by using a molecular dynamics method, the property of a surface modification layer is analyzed, the simulated etching conditions are independent and controllable, plasma etching with different energies, incident angles and incident doses can be simulated, and the influence of a single variable on an etching result can be accurately analyzed; the method can accurately and quickly predict the effect of etching silicon or silicon dioxide by the halogen plasma under different incidence conditions, avoids high cost, complexity and uncertainty caused by experiments, and greatly shortens the development process of the process of etching silicon or silicon dioxide by the halogen plasma.

The invention discloses an anti-interference source code vulnerability detection method and device based on deep learning. The device comprises a neuron deviation abnormal degree calculation module, a neuron deviation abnormal degree regulation and control module and a real-time verification and parameter updating module. A deep learning network structure defense layer is added on a deep learning neural network model, an anti-interference source code vulnerability detection network model based on deep learning is constructed, the neuron suppression probability is adaptively adjusted, the neuron activation probability is dynamically adjusted, the source code detection effect of the model under the disturbance condition is enhanced, and the source code vulnerability detection efficiency is improved. And the omission ratio of model detection is reduced.

The invention discloses an uncertainty determination method and device for nuclear material analysis, a medium and a program product. The method includes: acquiring a first set and a second set; wherein the first set comprises isotope analysis results obtained by analyzing the nuclear material through a destructive analysis method; the second set comprises isotope analysis results obtained by analyzing the nuclear material through a non-destructive analysis method; determining a data deviation between the first set and the second set; determining a random error of the non-destructive analysis method based on the data deviation; determining a system error of the non-destructive analysis method based on the data deviation; and determining the uncertainty of the non-destructive analysis method for the content of the isotope in the nuclear material based on the system error and the random error.

The invention discloses an unmanned aerial vehicle cluster formation fault-tolerant method based on protopigeon chaos adaptive sliding mode control, and the method comprises the steps: 1, carrying out the kinematics modeling of an unmanned aerial vehicle, and determining the initial state of the unmanned aerial vehicle and a formation flight control system of wing aircrafts and lead aircrafts; 2, introducing a virtual reference unmanned aerial vehicle kinetic model, designing a tracking error, obtaining a dynamic tracking error equation, and ensuring the accuracy of a reference model; 3, designing a sliding mode surface function, and obtaining a reduced-order sliding mode kinematics equation by applying an adaptive sliding mode control technology; and the like. The method is easy to implement, the provided chaotic pigeon inspired mechanism can greatly optimize parameters in adaptive control and sliding mode control parameters, the control convergence speed is increased, and a robust solution is provided for solving the difficult problems that an unmanned aerial vehicle with communication faults cannot adapt to a complex environment and the like.

A data storage encryption method, device and electronic device relate to the field of data processing. In the method, respond to the encryption request of the user, and obtain the data to be encrypted; use the preset public key to encrypt the data to be encrypted to obtain the basic encrypted data; determine the encryption node for responding to the encryption request among multiple spare nodes; obtain the node public key corresponding to each encryption node; use each node public key to perform secondary encryption on the basic encrypted data to obtain multiple target encrypted data; interleave and send the target encrypted data to each encryption node for storage, wherein the first encryption node does not receive the first encrypted data, the first encryption node receives the second encrypted data, the first encryption node is any one of the multiple encryption nodes, the first encrypted data is encrypted by the first node public key corresponding to the first encryption node, the second encrypted data is encrypted by the second node public key corresponding to the second encryption node, and the second encryption node is any one of the multiple encryption nodes except the first encryption node. Implementing the technical solution provided by the present application reduces the probability of data being leaked when the node is attacked when it is stored in the node.

The invention provides a low-delay wave beam direction finding technology realized based on an FPGA. The low-delay wave beam direction finding technology comprises the following steps: establishing a wave beam direction finding simulation mathematical model according to a wave beam direction finding algorithm in combination with specific hardware parameters and indexes and feature information of a to-be-detected flight target; converting the established wave beam direction finding simulation mathematical model into an FPGA program; the method comprises the following steps: establishing a hardware test platform, and programming an FPGA (Field Programmable Gate Array) program into an FPGA baseband board; and performing operation according to the direction testing process to complete direction testing. Compared with the prior art, the delay caused by direction finding is greatly reduced by virtue of the strong parallel processing capability of the FPGA chip and the high-speed clock, and meanwhile, the resolution of direction discrimination is improved. Through application of the FPGA and accurate mathematical modeling, the method has significant advantages in the aspects of direction finding precision, real-time performance, system expansibility, anti-interference capability and the like, and can effectively cope with complex flight target direction finding tasks. Therefore, the technology has wide application prospects in the fields of aerospace, military reconnaissance, unmanned aerial vehicles and the like.

The invention discloses a hypersonic deformation aircraft pose sliding mode control method based on ISAC, and belongs to the technical field of deformation aircraft control, and the method comprises the following steps: building a longitudinal pose model of a hypersonic deformation aircraft, and building a linear variable parameter system after sampling and interpolation; designing a sliding mode surface based on the joint tracking error of the relative height and the relative speed, and designing a corresponding novel adaptive sliding mode reaching law; constructing an ISAC model, and solving a time-varying reaching law gain coefficient through the ISAC model; taking the weighted fusion action of the three-branch Actor module as a time-varying reaching law gain coefficient, and solving an adaptive sliding mode reaching law; solving a sliding mode surface s; and sliding mode control input is obtained based on a modeled linear variable parameter system. By adopting the method, the pose control precision and the anti-interference capability of the hypersonic deformation aircraft are improved, and the system stability under multiple constraints such as flight safety boundaries and control constraints is ensured.

The invention belongs to the technical field of trajectory prediction, and particularly relates to a ship trajectory prediction method based on TP2LSTM. The method comprises the following steps: step 1, acquiring historical trajectory data of a target ship; wherein the historical trajectory data comprises the information of trajectory points of the target ship at the first N moments, and the information of each trajectory point comprises the longitude, the latitude, the course to the ground and the navigational speed; and 2, inputting the historical trajectory data into a ship trajectory prediction model, and predicting to obtain trajectory data of the target ship at a future moment. According to the method provided by the invention, long-term and complex features hidden in the trajectory data can be extracted in space and time, so that the problem of insufficient consideration of multi-variable dynamic feature correlation is solved.

The application discloses a method for removing electroplating process wires by laser, comprising the following steps: step (1), according to the state of the existing process wires after electroplating, designing reasonable half-cut laser processing path and hot-pressing laser processing path; step (2), according to the half-cut laser path, cutting the metal layer of the process wires by laser, and basically not damaging the underlying substrate; step (3), according to the hot-pressing laser processing path, using the thermal effect of laser to heat the process wires, and then reducing the adhesion between the process wires and the substrate, and meanwhile, a certain positive pressure blowing or / and negative pressure suction is used to make the process wires separate from the substrate. The method does not need traditional manual picking to remove the process wires, does not need secondary etching, has no protective material coating process, and can adopt laser direct stripping to remove the process wires; the method is accurate in positioning, has no burr on the edge, has no side etching, is good in consistency, is high in processing efficiency, is low in cost, and is simple in operation, and is low in skill requirement for employees.

The invention is suitable for the technical field of information security, and provides a data sharing method, device and equipment based on broadcast encryption and a storage medium, and the method comprises the steps: determining a data provider and a data receiver set; determining a transmission path set based on the data receiver set by using an intelligent contract; the data provider encrypts the to-be-shared data based on the main public key to obtain a ciphertext, and generates a ring signature based on the ciphertext, the data receiver set and a first private key of the data provider; the data provider encrypts the to-be-transmitted data based on the second public key of each target relay node in the target transmission path to obtain target encrypted to-be-transmitted data; decrypting and transmitting the target encrypted data to be transmitted based on the second private key of each target relay node until the target data receiver receives the data to be transmitted; and the target data receiver obtains the to-be-shared data based on the corresponding first private key and the to-be-transmitted data, so that the security of data sharing is improved.

The embodiment of the invention discloses a virtual object control method and device, a terminal and a storage medium, and relates to the field of application programs supporting virtual environments. Comprising the steps that under the condition that a first virtual object meets a swallowing condition, the first virtual object in a swallowing state is displayed in a virtual environment, and the swallowing state refers to the state that the first virtual object swallow a second virtual object in the virtual environment; in the swallowing state, responding to a control operation on a third virtual object, and controlling the third virtual object to execute a swallowing prevention action; under the condition that the first virtual object is in the swallowing completion state, displaying the first virtual object after the swallowing gain is obtained in the virtual environment; and in response to a control operation on the third virtual object, controlling the third virtual object to attack to obtain the first virtual object after the phagocytizing gain. By adopting the method provided by the embodiment of the invention, the uncertainty in the game process is increased, and the experience of players is improved.

The present invention discloses an electronic medical record management system and method based on cloud computing, which relates to the technical field of medical informatics, and includes a front-end module, a management gateway, a cloud account server, a cloud encryption server, a cloud storage server, etc. The random characteristics of the account login time are used to construct an account login time matrix, and the values ​​of two data among five login time data are randomly extracted to construct a random key matrix; based on the operation of Unicode encoding values, the text information to be encrypted is encrypted through the random key matrix to achieve the first layer of privacy protection; through the superposition of two-level account passwords, the random key matrix is ​​encrypted to obtain an encryption key matrix to achieve the second layer of privacy protection; based on cloud computing, real-time storage and synchronization of cloud data are realized, and the storage load is balanced through scientific and dynamic regulation of data storage volume; by setting primary accounts and secondary accounts, information sharing requests and authorization mechanisms, cross-institutional data sharing is supported.

The invention discloses an ECU unauthorized swiping prevention method, device and equipment based on dynamic baud rate communication and a medium. The method comprises the steps that after a data flashing instruction is received, an upper computer is in communication connection with an ECU based on a first baud rate; after the upper computer is successfully connected with the ECU, the upper computer and the ECU carry out baud rate negotiation to obtain a successfully negotiated second baud rate; and the upper computer performs security access and data flashing on the ECU based on the second baud rate. According to the method and the device, the Baud rate of CAN communication is negotiated before data flashing is performed on the ECU by using the CAN bus, and if the communication Baud rate of the ECU cannot be determined by the upper computer, external personnel cannot violently crack a security access algorithm of the ECU through an exhaustion method and the like, so that the security of the ECU is greatly improved, and the situation that the ECU is stolen after entering the market can be effectively avoided.

The invention discloses a load side resource market declaration behavior simulation method and system, and the method comprises the steps: building a load side resource market declaration behavior simulation model which comprises a user quotation model and a user quantity reporting model; various deduction scenes are set in a control variable mode, simulation parameters of the various deduction scenes are input into the load side resource market declaration behavior simulation model, and declaration prices and declaration amounts of all users under different control variables of the various deduction scenes are generated; a centralized clearing mode is adopted to form load side resource clearing results under various deduction scenes; and evaluating load side resource clearing results in various deduction scenes by using set evaluation indexes to analyze the influence of various parameters of user behavior changes in the future on market clearing results. According to the method, the declaration behavior and clearing result simulation of large-scale load side resources participating in the electricity market are realized, and a reliable basis is provided for analyzing load resource quotation and predicting market clearing electricity price.

The present invention relates to a generative sequence recommendation model and construction method for recommendation fairness, the method comprising: injecting random noise into user interaction behavior to obtain a damaged interaction representation that obeys a Gaussian distribution, then designing a sequence denoising model in the reverse restoration process, and using a dynamic routing mechanism to mine multiple interest representations in user historical interaction behaviors, and performing two-stage training in combination with user-side modeling to complete denoising; imitating the forward noise addition process to make the project representation noisy and then use it to iteratively reversely reconstruct the generated project. Compared with the traditional sequence recommendation model, the present invention, on the one hand, constructs a generative recommendation paradigm based on a diffusion model, and models uncertainty and alleviates noise by learning the statistical laws of data and generating new data based on it; on the other hand, it avoids the influence of factors such as user sensitive characteristics that may lead to discrimination or unequal treatment on the recommendation effect, and further promotes the diversity of the generative sequence recommendation model by improving the fairness of the recommendation.

The present invention relates to a method for identifying bird nests in substations based on deep learning, comprising: building and training a recognition model: acquiring a sample image, processing the sample image by using a first feature extraction algorithm, and obtaining a sample feature map; inputting the sample feature map into a recognition model, wherein the recognition model performs several convolution operations on the sample feature map, and obtains several feature maps of different scales, and generates several anchor frames in the several feature maps; using a quantum particle swarm algorithm, determining the ratio value and confidence threshold of positive samples to negative samples; dividing the several anchor frames into positive samples and negative samples according to the confidence threshold; updating the recognition model according to the several positive samples and negative samples; acquiring an image to be inspected; processing the image to be inspected by using a first feature extraction algorithm, and obtaining a first feature map; inputting the first feature map into the recognition model, and obtaining a first recognition result and the confidence of the first recognition result.

The invention relates to the technical field of medical instruments, in particular to a gynecological tumor sampler which comprises a hose, the hose is provided with a sampling needle assembly and a power assembly, the sampling needle assembly comprises a shell, a fixing plate is arranged in the shell, the fixing plate is communicated with a sampling needle, and a limiting groove is formed in the shell; the power assembly comprises a piston plate, one side of the piston plate is connected with a piston rod, the other side of the piston plate is connected with a push rod, the piston rod is provided with a handle assembly, a connecting rod and a fixing plate are arranged in the shell, gear rings are connected to the outer side walls of the piston plate and the connecting rod, and the fixing plate and the piston plate are meshed with the connecting rod. A monitoring assembly is installed on the shell and is in signal connection with a controller, and the controller gives a prompt according to distance data monitored by the monitoring assembly in real time. The angle and depth of the sampling needle can be easily adjusted by medical staff so as to adapt to tumors at different positions and in different forms, the sampling accuracy is greatly improved, and the safety and efficiency in the operation process are remarkably improved.

The application discloses a kind of hydrorefining catalyst activation methods of hydrocarbon oil.The method includes the process of reduction to hydrorefining catalyst of hydrocarbon oil, wherein, the hydrorefining catalyst includes alumina carrier, metal molybdenum, organic nickel and organic metal auxiliary agent, the metal auxiliary agent is at least one or several of zinc, copper, magnesium, gallium, with the weight of final hydrogenation catalyst as basis, the mass content of organic nickel is 0.1% to 4.0%, preferably 0.2% to 3.0%, further preferably 0.5% to 2.0%, with the metal auxiliary agent element as basis, the mass content of organic metal auxiliary agent is 0.05% to 2.5%, preferably 0.1% to 2.0%, further preferably 0.2% to 1.5%.The method has the advantages of time-saving and high efficiency, without adding sulfidation agent, and more simple and convenient to switch raw materials.