12 results about "Relaxation algorithm" patented technology

The application discloses a method for designing and optimizing a VLCP system assisted by light reflection RIS under low signal-to-noise ratio, wherein the VLCP system comprises an intelligent wall adopting a smart surface RIS with mirror reflection, a transmitter and a user terminal equipped with a receiver with a liquid crystal smart surface, communication and positioning signals are integrated into the transmitter, the transmitter comprises an LED, and the method comprises the following steps: under low signal-to-noise ratio, taking asymptotic capacity as a communication metric constraint condition, taking a Cramer-Rao lower bound of positioning error as a positioning metric constraint condition, combining a positioning constraint satisfaction process based on a two-stage greedy algorithm and a communication performance maximization process based on a greedy strategy convex relaxation algorithm, optimizing elements of an RIS allocation matrix to maximize the asymptotic capacity, obtaining an optimal RIS allocation matrix, and completing the design and optimization of the VLCP system. In a low signal-to-noise ratio scene, the VLCP system of the application can significantly improve system performance by applying RIS.

The invention discloses a numerical weather forecast cold start error suppression method and device, and relates to the technical field of offshore wind power, and the suppression method comprises the steps: S1, collecting initial data through a marine meteorological sensor array, including sea wave height, period, wave direction and corresponding wind field initial observation data, and constructing a multi-dimensional data set after preprocessing; s2, on the basis of the data set and historical sea wave-wind field time series data, a physical mechanism and data driving combination method is adopted to construct a sea wave-wind field coupling model, and the nonlinear coupling relation between sea waves and the wind speed and the wind direction is quantified. According to the method, a physical mechanism and data driving fusion modeling is adopted, so that the meteorological rule conformity is guaranteed, the nonlinear coupling relationship is accurately captured, the limitation of a pure physical and pure data driving model is avoided, and the prediction core support is tamped; based on neural network mining time sequence and mode characteristics, a lattice point relaxation algorithm parameter strategy is dynamically adjusted, and the problem that traditional fixed parameters are poor in adaptability is solved.

The application relates to the technical field of satellite network communication, and particularly discloses a low-orbit integrated satellite network multi-task planning method and system, which comprises the following steps: a system model containing an integrated satellite, a data relay satellite, a ground station and a task set is constructed; based on the system model, an optimization problem with the target of maximizing the weighted task completion amount is established; a semi-positive definite relaxation algorithm is used to solve the task collection planning sub-problem, and a column generation algorithm is used to solve the task transmission planning sub-problem; the solving result of the task transmission planning sub-problem is fed back to the task collection planning sub-problem to update the task weight, and the steps of solving the task collection planning sub-problem and the task transmission planning sub-problem are iteratively executed until the convergence condition is met; for a complex scene where heterogeneous services coexist, an efficient global optimization solution is provided, the task benefit is maximized, a dynamic feedback iteration mechanism is introduced, and the overall coordination and adaptability of the system are enhanced.

The invention discloses a sum rate optimization method of an MA and RIS combined auxiliary NOMA uplink transmission system, which is suitable for an uplink transmission system consisting of a multi-antenna base station, an RIS and two communication users, and each communication user is provided with a single movable antenna. In order to effectively improve the transmission capability of the proposed system, the invention provides a sum rate optimization method of an MA and RIS combined auxiliary NOMA uplink transmission system. Specifically, the sum rate of the NOMA uplink transmission system is maximized by jointly optimizing a base station to receive a beam forming vector, an RIS phase shift matrix and an MA position. For the provided complex non-convex problem, a positive semidefinite relaxation algorithm is utilized to optimize receiving beam forming and an RIS phase shift matrix of a base station, a continuous convex approximation algorithm is utilized to optimize an MA position, and alternate iteration is carried out until a convergence condition is met. A simulation result shows that compared with a traditional fixed position antenna and RIS combined auxiliary NOMA uplink transmission scheme, the scheme provided by the invention remarkably improves the sum rate of an NOMA uplink transmission system.

The invention discloses a concealed wireless communication beam forming optimization method under limited character input, and belongs to the technical field of wireless communication. According to the method, a transmitting power and beam forming vector optimization strategy for jointly optimizing a transmitting end under different modulation modes is constructed, and a positive semidefinite relaxation algorithm is designed on the basis of utilizing lower bound approximation of an objective function: an initial non-convex objective function and a hidden constraint are equivalently converted into a convex form which is easier to process; and solving by using a CVX toolkit in MATLAB to obtain a design which enables the problem to be optimal in beam forming vector. Furthermore, in order to reduce the calculation complexity, the invention provides a low-complexity optimization strategy, and a simulation result shows that the method can remarkably reduce the calculation complexity while meeting the covert communication performance.

The invention relates to the technical field of tunnel engineering, in particular to a near-field dynamics simulation method and system for tunnel yielding support, and the method comprises the steps: dispersing a lining, a steel bar and a high polymer buffer layer model into space material points, distributing different material attributes for different materials, and generating a space coordinate matrix of the material points; a virtual boundary layer serving as a displacement boundary condition applying object is arranged on the outer wall of the lining; determining neighborhoods of the material points, and forming a neighborhood matrix of all the material points; setting a displacement boundary condition according to the large deformation grade; obtaining a compression constitutive model of the high polymer buffer layer, and calculating a micro-elastic modulus; adopting a self-adaptive dynamic relaxation algorithm to construct a near-field kinetic equation to iteratively solve the bond elongation of the material point; and calculating a global damage coefficient according to a comparison result of the key elongation and the critical elongation. According to the invention, crack initiation and development can be simulated on an engineering scale model, and a protection mechanism of an interlayer high polymer buffer layer for large deformation of soft rock is disclosed.

A method and device for optimizing train departure path and timetable cooperatively, the method comprising: constructing a space-time state network for describing the operation of a train bottom; based on the space-time state network, constructing a train departure path and timetable cooperative optimization model; wherein the train departure path and timetable cooperative optimization model comprises a model for minimizing the space-time state path cost of the train bottom leaving a section and corresponding constraint conditions; using a Lagrange relaxation algorithm to transform the train departure path and timetable cooperative optimization model, and using a dynamic programming algorithm to solve the model to obtain an optimal train departure path and timetable. Through the method and device provided in the embodiment of the application, the train operation cost can be effectively reduced while the travel time of passengers is shortened, and the method can be used for assisting actual transportation production and improving the overall quality of train operation plans in departure time periods.

The invention discloses an underground pipeline scattered wave separation imaging method and system and a medium, and relates to the cross technical field of geophysical exploration and digital signal processing, and the method comprises the steps: obtaining and preprocessing original seismic data, taking an obtained two-dimensional time-space domain seismic record as an input, and constructing a scattered wave sparse dictionary based on discrete shear wave transformation; establishing an objective function based on morphological component analysis, performing iterative solution by using a block coordinate relaxation algorithm, and alternately updating a scattering wave sparse coefficient and an interference wave sparse coefficient until a convergence condition is met; reconstructing a pure scattered wave field through shear wave inverse transformation according to the finally obtained scattered wave sparse coefficient; performing migration imaging on the pure scattered wave field to obtain a spatial position image of the underground pipeline; according to the separation imaging method, a complete pipeline scattering form can be identified and captured under a strong noise background.

This invention relates to a multi-dimensional confidence-based point-line fusion SLAM method and system for visually degraded environments, belonging to the fields of computer vision and robot navigation technology. The invention constructs a nonlinear mapping function based on two-dimensional image entropy, dynamically adjusts the gradient threshold and Gaussian smoothing parameters of the line feature extraction algorithm, and introduces a sudden illumination safety mode to enhance adaptability to extreme environments. It performs photometric consistency verification on point features after optical flow tracking, performs region growing on line features using the aforementioned adaptive parameters, and proposes a hierarchical non-convex relaxation algorithm guided by dual weights of geometric residuals and pixel gradients for noise-resistant fitting. It establishes a linear inverse mapping mechanism between front-end feature confidence and back-end optimization information matrix, dynamically adjusting residual weights according to feature quality. In motion-blurred and illumination-changing environments, it can effectively extract high-quality features and perform tight-coupling optimization, improving the positioning accuracy and speed of the SLAM system in weak-texture and drastically changing illumination environments.

The application discloses a covert wireless communication beamforming optimization method under limited character input and belongs to the technical field of wireless communication.The application constructs a joint optimization strategy of the transmission power and the beamforming vector optimization strategy of the transmission end under different modulation modes, designs a semi-positive definite relaxation algorithm on the basis of using the lower bound approximation of the objective function, equivalently converts the initial non-convex objective function and the covert constraint into a more easily handled convex form, solves by using the CVX tool package in MATLAB, and obtains the design of the optimal beamforming vector of the problem.Further, in order to reduce the calculation complexity, the application proposes a low-complexity optimization strategy, and simulation results show that the method can significantly reduce the calculation complexity while meeting the performance of covert communication.

The present application relates to the technical field of power system operation control, and specifically to a parallel accelerated solution method for post-disaster restoration of a power system based on quantum computing, including: step 1: establishing a model for post-disaster restoration; step 2: according to the quantum proxy Lagrangian relaxation algorithm, decomposing an original optimization problem into node subproblems; and step 3: solving the model for post-disaster restoration, updating Lagrange multipliers and penalty factors in iteration, achieving an optimal solution under the interaction of quantum computing and classical computing, and accelerating the acquisition of a restoration plan to guide a safe operation of the power system. The present application decomposes a problem into subproblems and divides the subproblems into discrete and continuous parts for solution, reducing the difficulty. The effects of parallel computing and quantum-embedding accelerated computing are realized without complete optimization for a relaxed problem, ensuring better convergence.

The invention provides an unmanned aerial vehicle communication and sensing integrated beamforming and trajectory design method and system, and relates to the technical field of unmanned aerial vehicle communication and sensing integration, and the method comprises the steps: building an unmanned aerial vehicle communication and sensing integrated scene model with the minimization of the total power consumption of an unmanned aerial vehicle task period as a target; decomposing the unmanned aerial vehicle communication perception integrated scene model to obtain an unmanned aerial vehicle beam forming design sub-model and an unmanned aerial vehicle trajectory design sub-model; constructing an alternating optimization framework, wherein the alternating optimization framework specifically comprises a semi-definite relaxation algorithm and a continuous convex approximation algorithm; according to the unmanned aerial vehicle trajectory parameters, solving the unmanned aerial vehicle beam forming design sub-model through a semi-definite relaxation algorithm to obtain communication beam forming parameters and a sensing signal covariance matrix; solving the unmanned aerial vehicle trajectory design sub-model through a continuous convex approximation algorithm to obtain updated unmanned aerial vehicle trajectory parameters; repeating calculation until a convergence condition is reached, and outputting an optimal strategy; and executing the optimal strategy.