20 results about "Stochastic geometry" patented technology

The invention discloses an unmanned aerial vehicle transformer substation inspection path planning method and device, equipment and a medium. The method comprises the following steps: firstly, generating a grid map; dividing the substation inspection space into a plurality of sub-regions; establishing an electromagnetic exposure intensity model, and setting an electromagnetic exposure intensity safety threshold; randomly sampling a plurality of nodes in each divided sub-region, constructing a random geometric graph, and generating an initial inspection path by adopting an RRT algorithm; optimizing the generated initial inspection path by using a path pruning optimization algorithm and a gradient descent convex optimization algorithm, and smoothing the path into a continuous curve by using a B-spline curve fitting technology to obtain a final optimized inspection path; according to the invention, through an overall strategy of first region division and then path planning, random geometric graph tree building, path pruning optimization, gradient curve smoothing and key region guiding sampling mechanisms are fused, and the efficient, stable and high-environment-adaptability unmanned aerial vehicle three-dimensional path planning method for the substation complex scene is realized.

A double-lane millimeter wave vehicle networking safety transmission method, system, device and medium based on STAR-RIS, the method comprising: constructing a STAR-RIS assisted double-lane millimeter wave vehicle networking communication scene; based on the propagation characteristics of millimeter wave signals, combining the channel fading characteristics under the conditions of line-of-sight and non-line-of-sight transmission and the transmission and reflection functions of STAR-RIS, calculating the channel gain of the cascaded channel of the STAR-RIS assisted link; based on the random geometry theory, respectively calculating the probability density functions of the associated distances of the direct link, the STAR-RIS reflection link and the STAR-RIS transmission link; constructing a dynamic link association strategy supporting ternary selection; establishing a signal-to-interference-and-noise ratio model under three association modes; combining the physical layer security performance index definition, calculating the closed-form analytical expressions of the connection interruption probability and the secrecy interruption probability, and verifying the security gain of STAR-RIS; the present application has the advantages of effectively overcoming the half-space coverage blind area of the traditional reflective RIS, and improving the link connection reliability and physical layer safety transmission performance under the double-lane complex shielding environment.

The application discloses an RIS-assisted zero-forcing beamforming method based on a physical layer security technology, and the method comprises the following steps: constructing an RIS-assisted downlink MISO security transmission system model, constructing a passive eavesdropping user mathematical model based on random geometry, and constructing a legal user and eavesdropping user received signal-to-noise ratio expression; constructing a legal user received signal-to-noise ratio maximization optimization problem model, including determining optimization variables, an objective function and constraint conditions, and pre-designing a transmission beamforming vector based on a zero-forcing algorithm; constructing a joint optimization transmission beamforming and reflection beamforming vector algorithm, dividing the legal user received signal-to-noise ratio maximization optimization problem into two sub-problems for solving, and optimizing the reflection beamforming vector at the RIS and the transmission beamforming vector at the base station. The application jointly optimizes the transmission beamforming vector and the reflection beamforming vector, and realizes the optimization target of legal user received signal-to-noise ratio maximization.

The invention discloses a region-centered unmanned aerial vehicle coverage rate analysis method. The method comprises the following steps: constructing a region-centered unmanned aerial vehicle cooperative transmission model; fractional power control is carried out on the service unmanned aerial vehicle and the interference unmanned aerial vehicle; calculating the signal-to-interference ratio of the typical user based on the transmitting power of the service unmanned aerial vehicle and the interference unmanned aerial vehicle; based on the stochastic geometry theory, the coverage probability of typical users is obtained through service distance distribution, signal power distribution and interference distribution in combination with a Cauchy-Schwarz inequality and Gamma distribution approximation; the unmanned aerial vehicle density, the power control coefficient, the path loss index and the Nakagami fading parameter are set, the influence of the number of different service unmanned aerial vehicles, the power control coefficient and the channel condition on the coverage probability is analyzed, and simulation verification is carried out. According to the method, the technical problem of how to suppress the network interference of the unmanned aerial vehicle through power control in a complex interference scene is solved, and the network coverage rate of the unmanned aerial vehicle is calculated.

The application discloses a random geometry modeling three-dimensional data set generation method, device, medium and product, relates to the technical field of data set generation, and comprises the following steps: for any three-dimensional geometry under the current cycle number, randomly generating a depth, a space parameter and a size in a set numerical range, so as to generate an initial three-dimensional geometry in a three-dimensional scene; randomly generating a noise texture and a target energy value; applying the noise texture to the corresponding initial three-dimensional geometry respectively to obtain an initial three-dimensional scene; in the initial three-dimensional scene, setting a sunlight light source with the target energy value to obtain a target three-dimensional scene; rendering the target three-dimensional scene to obtain an image data group, adding the image data group into an initial data set to obtain a target data set, and performing the next cycle until a maximum cycle number is reached, so that a random geometry modeling three-dimensional data set is obtained. The application realizes the rapid generation of the random geometry modeling three-dimensional data set.

The invention discloses a satellite-ground fusion network cross-layer secure transmission method based on an optimal detection contact angle, and the method comprises the following steps: 1, collecting a plurality of parameters of a ground terminal, a service satellite and an eavesdropping satellite, and constructing a double-layer satellite satellite-ground fusion network model based on stochastic geometry; 2, constructing a signal model, and determining a reachable secrecy rate according to the signal model; 3, determining the security coverage probability and the average secrecy rate under different network layer information exchange degrees; and step 4, according to the optimal detection contact angle, dynamically adjusting an information exchange strategy of an inter-satellite link, informing related service satellites of an eavesdropping satellite range in which information needs to be acquired, implementing eavesdropping avoidance or resource scheduling by the service satellites in a known area, taking conservative security measures for an unknown area, and transmitting data to be transmitted. The method has the characteristics that the security performance of the physical layer is improved on the premise of not depending on the CSI of the eavesdropper, and the practicability and robustness of the security scheme are greatly improved.

The invention discloses an SPMA protocol priority threshold design method based on stochastic geometry and a queuing theory, and belongs to the technical field of SPMA protocol performance optimization. The method solves the problems that an existing method cannot obtain an optimal scheme capable of maximizing the channel utilization rate and guaranteeing priority scheduling, and is poor in flexibility and adaptability and high in test cost. The random geometry and the queuing theory are fused, the position distribution of a transmitter and a receiver and the arrival process of data packets with various priorities are obtained based on the random geometry, the distribution obeyed by the service time of the data packets is obtained through the queuing theory, and then the constraint relation between the priority threshold value and the data packet sending success rate is determined through mathematical derivation. Theoretical guidance is provided for priority threshold design, more channel access opportunities are provided for low priority on the premise that high-priority transmission performance is guaranteed, and dynamic balance between maximization of channel utilization rate and multi-priority scheduling is guaranteed. The method can be applied to the priority threshold design of the SPMA protocol.

The present invention is a method for generating random numbers using discrete randomized geometric graphs and cellular automaton mechanisms. Number generators often fail to provide unpredictable results which pass tests for statistical randomness. The present invention method increases unpredictability while meeting the tests for cryptographic random number generation.

This application provides a region-aware driven self-supervised image denoising method, system, apparatus, and medium, belonging to the field of image processing technology. The method includes: constructing an adaptive region-aware network framework, including an initial adaptive region-aware blind spot network, an adaptive hybrid scrambling branch, a non-scrambling branch, and a random geometric transformation pixel downsampling module; training the adaptive hybrid scrambling branch and the non-scrambling branch to generate a trained adaptive region-aware blind spot network; inputting a noisy image into the trained adaptive region-aware network to obtain a tested and verified adaptive region-aware blind spot network; and inputting the noisy image into the tested and verified adaptive region-aware blind spot network to obtain a denoised image. This achieves superior denoising performance.

This invention discloses a relay selection method and system for vehicle-to-vehicle multi-hop cooperative communication systems. It constructs a stochastic geometric model of the vehicle network and determines the location and size of candidate relay areas based on a no-relay probability threshold and the communication service quality of relay links. All candidate relay vehicles within the relay selection area are acquired to obtain a candidate relay set. A relay vehicle is selected from the candidate relay vehicles according to a relay selection strategy that guarantees the service quality between the source node and the relay vehicle. The source node sends messages to both the relay vehicle and the destination node. After decoding the message, the relay vehicle forwards it to the next relay vehicle or destination node based on its relative position to the destination node. When the distance between the relay vehicle and the destination node exceeds the communication range, the currently selected relay node is used as the source node after one hop, and this process is repeated until the message is forwarded to the destination node. This invention effectively reduces the number of relay hops, making communication more reliable and reducing latency.

The present application relates to a kind of based on edge cache adaptive downlink non-orthogonal multiple access transmission method and system, BS is adaptively selected transmission mode according to user local cache hit situation, in three kinds of mode between mute transmission, single-user transmission and NOMA transmission, flexible switching, reduce redundant data transmission from source and improve spectral efficiency;When two users all need to receive data, user can adaptively carry out interference cancellation according to whether the content required by the other party is cached, realize the optimization of cache-aided interference suppression and signal decoding.At the same time, the present application constructs large-scale cellular network model based on random geometry theory, system analyzes the probability of user successfully obtaining content under different cache states and transmission modes, reveals the influence mechanism of cache state, power allocation and decoding mode on system performance;And carry out performance comparison and parameter optimization under multi-reference scheme, realize the maximization of system downlink throughput by jointly optimizing power allocation factor and time allocation factor.

The invention provides a region perception driven self-supervised image noise reduction method, system and device, and a medium, and belongs to the technical field of image processing, and the method comprises the steps: constructing a self-adaptive region perception network framework, comprising an initial adaptive region sensing blind spot network, an adaptive hybrid scrambling branch, a non-scrambling branch and a random geometric transformation pixel downsampling module; training the self-adaptive hybrid scrambling branches and the non-scrambling branches to generate a trained self-adaptive region sensing blind spot network; inputting a noise-containing image into the trained adaptive region sensing network to obtain an adaptive region sensing blind spot network after test verification; and inputting a noise-containing image into the self-adaptive region perception blind spot network after test verification to obtain a de-noised image. And a better denoising effect is obtained.

The application discloses a kind of leather surface flaw detection grading method and system based on AI vision, specifically includes: step 1: collection leather surface image data and divide leather surface analysis area, generate spatial position mark and texture feature vector;Step 2: construct random geometric model including spatial intensity parameter set, spatial interaction parameter set and flaw grade state variable set;Step 3: construct grading condition adaptive proposal distribution and generate sample candidate parameter set;Step 4: introduce grade consistency potential function to construct target probability distribution;Step 5: execute Markov chain Monte Carlo acceptance determination to generate parameter update result;Step 6: generate flaw spatial distribution state;Step 7: generate flaw grading determination result and output leather overall grading result.The application introduces random geometric constraint, realizes accurate grading.

This invention relates to the field of geometric modeling technology for marine pile foundation engineering structures, and provides a method for modeling stochastic geometric defects in tubular structures based on a node-layered continuous construction. The method includes the following steps: establishing a finite element geometric model of the tubular structure to be analyzed; constructing nodes and element meshes; dividing the nodes involved in geometric updates into node layer sets; establishing a mapping relationship between node spatial coordinates and parameter spatial coordinates; based on externally input stochastic geometric defect field data, performing two-dimensional interpolation calculations on the node parameter coordinates in the parameter space to obtain the target defect values ​​on the outer and inner surfaces; calculating a continuous construction relationship; geometrically updating the spatial coordinate information of the nodes; and generating a finite element model of stochastic geometric defects. This invention, by no longer treating finite element nodes as independent discrete update objects, provides a geometric basis for the continuous construction of defect geometry in the thickness direction through this layered structure.

The application discloses a rate analysis method of an intelligent metasurface system based on random geometry distribution, and comprises the following steps: constructing an initial optimization problem, in which a robustness problem of a distributed intelligent metasurface system under the influence of an initial mobile user is constructed; a receiver receives superimposed signals from multiple reflection links, and a determination formula of an initial reachable rate of the system is given; and the determination formula is further converted into an upper limit solution according to the Jesse inequality and a probability density function; the time intensity of vertical switching and beam selection caused by user movement is obtained; the total time overhead is further obtained; and an expression of a final area traversal reachable rate is obtained. The application is applied to an actual random distribution intelligent metasurface assisted communication system, an expression of an area spectrum rate limit is given, and the system performance can be effectively evaluated.

The application discloses a kind of composite briquette adding phase geometric structure and space distribution optimization method, adopt ellipsoid equation to simultaneously describe round ball type, whisker type, sheet type filling method, realize the optimization design of different geometric shapes;Specific steps are as follows:1, give the relevant condition of briquette;2, establish the r-θ2D section analysis model of briquette;3, given the discrete geometric number of adding phase;4, generate corresponding ellipse in model using random algorithm;5, determine whether the ellipse generated in 4 has problem, if there is problem, repeat 4;6, repeat steps 4, 5, generate M sets of data containing random geometry, space distribution;7, carry out mesh division;8, use numerical analysis method and solve in parallel, obtain M groups of key variables;9, based on the result in 8, using genetic algorithm and other optimization means, evaluate the pros and cons of M groups of design, then generate M groups of data again in combination with steps 4-6;10, repeat steps 4-9 until the optimization algorithm convergence condition is reached;11, output optimization result.

The invention provides a composite material finite element model construction method based on a random adaptive distribution algorithm, and belongs to the technical field of finite element modeling. Aiming at the random distribution characteristic of the SMC composite material, generating a random geometric model of the sheet material in a specified range through a random distribution algorithm; the distribution characteristics are adjusted by combining an adaptive optimization algorithm so as to meet the target volume fraction; geometric interference between the sheets is eliminated through a collision detection algorithm based on a separation axis theorem, so that an interference-free geometric model is generated; and finally, carrying out finite element mesh generation and material attribute definition, and constructing an accurate finite element model. According to the method, the mesostructure of the SMC composite material can be truly represented, and the modeling efficiency and the precision of mechanical property prediction can be improved, so that technical support is provided for design and optimization of the SMC composite material.

The invention provides a robot motion planning method and device inspired by a human brain scene semantic collaboration mechanism, and relates to the technical field of robot motion planning. The method comprises the following steps: based on a robot intelligent operation platform, carrying out data acquisition on a motion task of a robot to obtain a motion initial position, a motion target position, an obstacle position and map environment information; on the basis of a sensing road section selector, a path section collision probability is predicted according to the motion starting position, the motion target position, the obstacle position and map environment information, and a safe random geometric graph is obtained; according to the secure random geometric diagram, performing heuristic value calculation through a global correction heuristic device to obtain a node heuristic value of the secure random geometric diagram; and according to the node heuristic value and the safe random geometric diagram, path searching is carried out through a micromodule, and a robot motion planning path is obtained. The robot motion planning method is an efficient and flexible robot motion planning method combining a graph neural network planner and a scene semantic collaboration mechanism.

This invention discloses a method for three-dimensional fine modeling and stability probability evaluation of complex rock mass blocks, comprising three steps: first, three-dimensional modeling of complex blocks based on three-dimensional laser scanning, integrating real high-precision terrain and random boundaries; second, introducing full-space stereographic projection for kinematic mobility prediction, inputting the extracted random geometric parameters into a rigid body limit equilibrium vector model considering water-rock coupling effects such as pore water pressure reduction, and calculating the probability distribution of the safety factor; and third, based on a multi-source collaborative support inversion model of target reliability, dynamically calculating and outputting the probability distribution of anchor cable reinforcement force required to maintain the target's stable state. This invention overcomes the inherent defects of traditional deterministic analysis and simplified probabilistic models, and overcomes the shortcomings of existing technologies that often use fixed attitude parameters and are difficult to detect potential risks.

The invention discloses a method for analyzing cellular network performance under strong electromagnetic pulse attack, and relates to the technical field of wireless communication network performance analysis. The network performance analysis method utilizes a stochastic geometry theory to analyze cellular network coverage probability and regional spectrum efficiency under strong electromagnetic pulse attack. Considering the condition that the strong electromagnetic pulse attack range is limited and part of base stations in the attack area are randomly damaged; constructing a spatial distribution model of cellular network surviving base stations under strong electromagnetic pulse attack based on a stochastic geometry theory; defining an influence area and an influence radius of the strong electromagnetic pulse attack; deriving an estimation formula of the network coverage probability and the regional spectrum efficiency, and calculating the coverage probability and the regional spectrum efficiency of the cellular network in the strong electromagnetic pulse influence region under different base station damage probabilities; the specific influence of the initial distribution density of the base station and the strong electromagnetic pulse attack radius on the influence radius and the specific influence of the damage probability of the base station on the network coverage performance and the regional spectrum efficiency can be determined.