26 results about "Linear solver" patented technology

A method of performing state estimation for a microgrid system includes: obtaining a general quantum state estimation model for swing-bus-contained microgrid systems; establishing a state estimation formulation through quantum language; assigning quantum registers used during a quantum state estimation iteration; generating a quantum-circuit-based state estimation solver for performing quantum phase estimation, controlled rotation, and inverse quantum phase estimation; generating a preconditioned quantum linear solver for an ill-conditioned state estimation iteration; iteratively optimizing voltage and residual vectors while iteratively updating preconditioned errors by the state estimation solver, the optimizing and updating iterations continuing until the linear solver reaches convergence; obtaining a quantum state estimation model for hierarchical-based microgrid systems including droop and / or secondary control modes; establishing an enhanced quantum state estimation framework including the state estimation solver and the linear solver; and generating an enhanced state estimation output for controlling one or more parameters of the microgrid system.

The invention relates to the technical field of unmanned aerial vehicle navigation, in particular to a low-complexity obstacle avoidance method and system for a quad-rotor unmanned aerial vehicle, and the method comprises the steps: representing the geometric shapes of the quad-rotor unmanned aerial vehicle and an obstacle as a union set of convex geometries; the obstacle avoidance requirement between the unmanned aerial vehicle and the obstacle can be converted into a mathematical problem that the intersection between two union sets is an empty set, and the implicit obstacle avoidance mathematical expression with the intersection being the empty set is converted into continuous differentiable explicit obstacle avoidance inequality constraints by further using the hyperplane separation theorem, so that efficient obstacle avoidance between the unmanned aerial vehicle and the obstacle is realized. According to the method, the separation hyperplane between the unmanned aerial vehicle and the obstacle is creatively and directly constructed, the constructed obstacle avoidance inequality is micro-continuous and can be directly adapted to a universal nonlinear solver, the efficiency of the unmanned aerial vehicle for rapidly planning the flight path is effectively improved, the accurate and real-time obstacle avoidance requirement of the unmanned aerial vehicle can be met, and the method is suitable for large-scale popularization and application. Practical technical support is provided for rapid flight path planning of the quad-rotor unmanned aerial vehicle.

The quantum Newton-Raphson load flow calculation method and system based on the subspace CKS linear algorithm are provided under the current limited quantum hardware resources, and combination of power system load flow calculation and the quantum calculation technology is achieved. Compared with a classical linear solver, the CKS quantum linear solver has an exponential acceleration effect, greatly optimizes the high dependency relationship of algorithm complexity on calculation precision, accelerates the solving speed of a linear system, and enhances the capability of solving the linear system.

The invention discloses a compression test method for LCD display screen production, and relates to the field of compression test, the method comprises the following steps: collecting LCD display screen information, building an LCD display screen digital twin model, using a digital twin cloud picture to analyze stress distribution, using a non-linear solver to analyze plastic deformation and interlayer stripping behaviors of a material, and obtaining a compression test result of the LCD display screen; positioning potential failure points according to an analysis result, predicting critical pressure values of the points, then setting mechanical pressure test contents according to simulation data obtained in the previous step, carrying out actual mechanical pressure test by using intelligent mechanical test equipment, and evaluating crack initiation probability according to a test result. The problem that the overall performance and the damage condition of the internal structure of the LCD display screen cannot be accurately evaluated due to the fact that an existing LCD display screen compression resistance testing method lacks comprehensive simulation on various pressure scenes is solved, and the compression resistance of the LCD display screen can be comprehensively and accurately evaluated.

The invention provides a quantum block coding discrete adiabatic evolution solving method for a direct current power flow equation, and the method mainly comprises the steps: designing Hamiltonian according to an admittance matrix of the direct current power flow equation and known node injection active power, and carrying out the post-processing of the Hamiltonian through an intrinsic separator, the improved block coding technology is embedded into a quantum discrete adiabatic linear solver, approximate Hamiltonian simulation is achieved through first-order approximation, and preparation of a quantum state solution bypassing complex Hamiltonian simulation and a power flow equation is achieved. According to the method, an improved block coding technology is introduced, and equivalent non-unitary operation on a quantum system in the discrete adiabatic evolution process is achieved; according to the method, the Hamiltonian containing information of a direct-current power flow equation solution is designed, the Hamiltonian is post-processed by introducing an intrinsic separation technology, the gap between a target eigenvalue and an adjacent eigenvalue is increased, the success rate of quantum discrete adiabatic evolution is increased, and the solving efficiency and precision are optimized.

The invention provides a quantum Newton-Raphson load flow calculation method and a quantum Newton-Raphson load flow calculation system based on a subspace variable component subalgorithm under current limited quantum hardware resources. Compared with a classical linear solver, the variable component sub linear solver has an exponential acceleration effect, realizes combination of a real quantum computer and a load flow calculation technology at the present stage, is matched with hardware resources of an existing limited NISQ computer, completes an experiment of a load flow calculation 16-node example in the real quantum computer, and has the advantages that the load flow calculation efficiency is improved, and the load flow calculation efficiency is improved. And the result is matched with a classical calculation result, and the error can be ignored. Besides, a random parameter configuration strategy and a dynamic learning strategy are introduced, so that the problem of low algorithm efficiency caused by falling into a local extremum is avoided, the solving speed of the linear system is accelerated, and the capability of solving the linear system is enhanced.

The invention discloses a reservoir group water supply optimization scheduling method, which comprises the following steps: equivalently transforming a reservoir group water supply optimization objective function and constraint conditions into a linear model, and simultaneously obtaining multi-reservoir group collaborative optimal water supply scheduling parameters by using a linear solver. The method has no special requirements on factors such as reservoir quantity, user quantity, water delivery line arrangement, and geographical environment of a basin or a region, is wide in application range, is convenient to calculate, is not influenced by a topological relation between reservoirs, and can effectively improve the working efficiency of water resource development, utilization and management.

The invention provides an urban hydrogen refueling station locating and sizing optimization method, system, equipment and medium, and belongs to the field of hydrogen energy industry infrastructure planning, and the method comprises the steps: converting traffic network data and hydrogen fuel cell vehicle data into a hydrogenation demand OD matrix through a graph theory, a double-constraint gravity model and a flow-demand conversion model; establishing a deviation demand capture objective function by taking capture of the maximum hydrogenation demand quantity as an objective; establishing an annual comprehensive cost objective function of the hydrogen refueling station by taking minimization of the annual comprehensive cost of the hydrogen refueling station as an objective; based on the objective function, a linear weighting method is adopted, and an urban hydrogen refueling station locating and sizing model captured based on the deviation demand is constructed; and calling a linear solver for solving to obtain a position and capacity scheme of the urban hydrogen refueling station. According to the method, the hydrogen demand deviation in the city is accurately captured, the site selection and capacity configuration of the hydrogen refueling station are optimized, the actual demand can be met, efficient utilization can be achieved on resource configuration, and efficient operation of the urban hydrogenation network is achieved.

The embodiment of the invention discloses a parameter training method of a variable component sub-linear solver and a related device. The method comprises the following steps: calculating the gradient of a quantum circuit in the variable component sub-linear solver under a variable parameter at the current moment; if the norm of the gradient at the current moment is greater than or equal to a preset closing precision standard, determining a Hessian approximation matrix at the current moment according to the variable parameter increment and the gradient increment of the current moment relative to the previous moment; determining a variable parameter of the next moment according to the variable parameter of the current moment, the gradient and the Hessian approximation matrix; and taking the variable parameter of the next moment as the variable parameter of the current moment, and executing the step of calculating the gradient of the quantum circuit under the variable parameter of the current moment. By adopting the embodiment of the invention, the parameter training efficiency of the variable component sub-linear solver can be improved while computer hardware resources are saved.

A subsurface representation may define subsurface configuration of a subsurface region. A grid connectivity graph for the subsurface representation may include (1) nodes that represent cells within the subsurface representation, and (2) edges between the nodes that represent connectivity between the cells within the subsurface representation. The grid connectivity graph may be filtered to remove edges that do not satisfy a connectivity criterion. The filtered grid connectivity graph may be used to compute a linear solver preconditioner that improves the performance of the subsurface simulation.

The invention discloses a small deformation mechanical analysis system and method based on a reactor numerical calculation framework and related products, and relates to the technical field of nuclear reactor fuel performance analysis. On the basis of a reactor numerical development framework, a unified tangent modulus and stress data interface is constructed according to a finite element theory and mechanical constitutive models such as elasticity, plasticity and creep; a radial regression algorithm is used for calculating the plasticity / creep strain of a nonlinear material, consistent tangent modulus and stress data are updated and transmitted into a nonlinear solver, a small deformation mechanical analysis system of a reactor numerical development framework is formed, and theoretical model support is provided for a fuel performance analysis program based on small deformation.

The invention discloses a characteristic value-based quantum linear solver parameter design method and solving method, and the method comprises the following steps: designing Hamiltonian simulation time Ht = pi in a quantum phase estimation stage in a quantum linear solver, and enabling the number of quantum bits to be related to the maximum value and the minimum value of the absolute value of the characteristic value of a matrix in a linear equation set; the normalization constant of the controlled rotation stage in the quantum linear solver is designed to be related to the minimum value of the absolute value of the characteristic value of the matrix in the linear equation set, and meanwhile, solving is carried out based on the designed parameters, so that the solving precision of the quantum linear solver can be remarkably improved.

The present invention discloses a method for accurately solving the structural parameters of an optical system. The steps include: 1) Denote the N structural parameters of the optical system as x(x1,…,xN); Denote the aberration F defined by the optical system, and the aberration function as f; 2) According to the definition in step 1), transform the optical design problem of the optical system into solving a non-linear equation set F = f(x); 3) Calculate the aberration values F0 corresponding to the initial structural parameters x0; Then, in turn, add a step size to each of the N structural parameters, and recalculate the aberration values F* and the corresponding aberration increments ΔF; 4) Obtain a difference quotient matrix A according to each obtained ΔF; 5) Convert F = f(x) into a linear equation set AΔx = ΔF; 6) Solve AΔx = ΔF by a linear solver based on QR decomposition to obtain the values of the N structural parameters of the optical system. The present invention can obtain the structural parameters of the optical system with better numerical stability and higher accuracy.

This invention discloses a method, apparatus, and medium for solving variable quantum linear problems in subspaces. The method includes: determining the system of linear equations to be solved, constructing a variable quantum circuit and a Krylov subspace, and using the generalized minimum residual method and the variable quantum circuit to calculate an approximate solution of the system of linear equations to be solved in the subspace. This addresses the shortcomings of existing technologies and can reduce the time complexity and computational load of solving linear problems.

This application provides a nonlinear finite element accelerated solution system and method. The system includes: a physical information neural network model construction module configured to: acquire configuration points in the solution domain of the nonlinear partial differential equation to be solved; input the configuration points into a fully connected neural network to obtain a predicted solution; and obtain a physical information neural network model based on the predicted solution; an input module configured to: construct a finite element model of the nonlinear partial differential equation to be solved; transform the nonlinear partial differential equation to be solved into a system of nonlinear algebraic equations; and generate a predicted value vector based on the finite element model; and a solution module configured to: solve the system of nonlinear algebraic equations using a nonlinear solver to obtain the target solution. This addresses the problem that in current finite element methods for parameterized research scenarios, each time a new parameter value is input, a complete and computationally expensive nonlinear finite element solution process needs to be started independently, leading to repetitive calculations and low efficiency.

The invention is suitable for the technical field of load flow calculation, and provides an AC load flow equation Newton-Raphson calculation method based on an adiabatic quantum linear solver, and the method comprises the steps: initializing a real part and an imaginary part of each node voltage, and a counter; based on the current voltage value of each node, calculating an active power unbalance amount, a reactive power unbalance amount and a voltage amplitude unbalance amount of each node in the power network, and determining a current iteration error; judging whether the current iteration error is smaller than a preset convergence threshold value or not; if yes, outputting a final voltage result of each node; if not, constructing a correction equation of a Newton-Raphson method, and solving the correction equation by using an adiabatic quantum linear solver to obtain a voltage correction vector of each current node; updating a real part value and an imaginary part value of each node voltage, progressively increasing an iteration counter, and returning to the above steps to continue iterative calculation until a convergence threshold value is met; and completing accelerated solution of the alternating current power flow equation.

The embodiment of the invention discloses a Helmholtz equation quantum solving method and an electromagnetic wave characteristic determination method and device, and the method comprises the steps: carrying out the series expansion of a solution and a source item of a Helmholtz equation according to a selected primary function, and discretizing a computational domain of the Helmholtz equation into grid points; substituting the solution and the series form of the source item into a margin function corresponding to the Helmholtz equation, and applying a weighted margin method at each network point to obtain a large linear equation set of which the dimension is consistent with the number of grid points; solving a linear equation set through a quantum linear solver to obtain a solution coefficient of the primary function, wherein the linear equation set is obtained by applying a weighted margin method to all grid points; and substituting the solution coefficient of the primary function into the series form of the solution to obtain the solution. By adopting the embodiment of the invention, the hardware resources of the computer can be saved, and the solving speed of the Helmholtz equation can be improved.

The invention relates to a smart building group power cooperative operation method based on an EPEC framework. The method comprises the following steps: acquiring equipment data of each building in a smart building group; constructing a boundary updating model, and obtaining boundary data of each building; constructing a double-layer optimization model of a cluster operator, and converting the double-layer optimization model into an MPEC model based on a KKT condition; performing linearization processing on a nonlinear equation set in the MPEC model based on a large M method and a strong dual theorem; and an EPEC solving framework is constructed, and solving of the linearized MPEC model is realized through double-layer iteration. According to the solving framework provided by the invention, the building group cooperative operation solving can be realized under the condition that only boundary information communication is carried out among buildings, the solving framework does not need to transmit actual data information to the cluster by the buildings, and the leakage risk of sensitive data in the buildings can be effectively reduced; according to the method, the solving process is simplified, the solving difficulty is reduced, and a commercial linear solver such as Cplex can be used for solving.

The invention discloses an optimal scheduling method for a coal dressing power supply system. The method comprises the following steps: acquiring power flow and material flow parameters, importing and defining decision variables; establishing a coal preparation plant multi-equipment multi-working-condition power consumption model, and establishing a coal preparation plant power supply system double-layer low-carbon optimization scheduling model in combination with a tidal current-coal flow-water flow-medium flow coupling relationship; importing a day-ahead production plan and day-ahead wind-photovoltaic prediction output, and initializing a time period parameter t = 1; a linear solver is called to solve the upper-layer model, and scheduling plans of the stock of the coal bunkers, the transportation volume of belt conveyors among the coal bunkers, the production volume of workshops and the power flow are solved; solving the lower-layer model by using a particle swarm optimization algorithm, and solving the operation speed of the front-end transportation equipment of the processing equipment; exporting a solution result of the lower-layer model and feeding back the solution result to the upper-layer model, updating the production capacity of each workshop, judging whether a time period is greater than or equal to 96 or not, if so, generating a final scheduling scheme, and if not, circularly executing the steps until time period conditions are met.

The invention relates to the technical field of computer-aided engineering and building information models, and discloses a fire-fighting installation BIM model and three-dimensional scanning intelligent acceptance and verification method, which comprises the following steps: constructing a discretization rigidity constraint model reflecting pipe network mechanical response, converting the space position difference between the actually measured pipe network center track and the design model into a displacement load vector; resolving the reverse elastic equilibrium equation by using a finite element linear solver to obtain internal force distribution and node torque response in a pipe network matching state; according to the method, a reverse mapping mechanism of geometric deviation and mechanical load is established, traditional geometric comparison is upgraded to assembly stress calculation, flexible adaptation and forced assembly are distinguished, and engineering potential safety hazards caused by hidden stress concentration are avoided.

The invention discloses a method and a device for adiabatic quantum calculation of a linear equation set based on block coding. The method comprises the following steps: acquiring the linear equation set Ax = b; constructing a time-dependent Hamiltonian H (f (s)) of adiabatic evolution, wherein the eigenstate of the initial Hamiltonian H (0) is expressed as bgt; the eigenstate of the target Hamiltonian H (1) is expressed as A-1bgt; ; a discrete adiabatic evolution quantum circuit is constructed, the discrete adiabatic evolution quantum circuit has an evolution operator UH (f (s)) corresponding to the time-dependent Hamiltonian H (f (s)), the evolution operator UH (f (s)) continuously acts on the discrete adiabatic evolution quantum circuit, and the initial quantum state corresponds to the eigenstate bgt of the adiabatic evolution initial Hamiltonian H (0); the final quantum state corresponds to the eigenstate A-1bgt of the adiabatic evolution target Hamiltonian H (1); . Compared with the prior art, the invention provides a specific implementation method for a quantum circuit of Hamiltonian gauge block coding, construction of a discrete adiabatic quantum linear solver can be realized based on the block coding, and solving of a linear equation set is completed.

The application discloses a kind of LCD display screen production with compression test method, it is related to compression test field, first, the information of LCD display screen is collected, and the digital twin model of LCD display screen is constructed, then stress distribution is analyzed using digital twin cloud chart, and the plastic deformation and interlayer peeling behavior of material are analyzed using nonlinear solver, potential failure points are located according to the analysis result, and the critical pressure value of these points is predicted, then the mechanical pressure test content is set according to the simulation data obtained in the previous step, and actual mechanical pressure test is carried out using intelligent mechanical test equipment, crack initiation probability is evaluated according to test result, and the result is fed back to digital twin model for further model calibration, the problem that existing LCD display screen compression test method lacks comprehensive simulation of multiple pressure scenarios, leading to inability to accurately evaluate overall performance and internal structure damage, the compression performance of LCD display screen can be comprehensively and accurately evaluated.

The application discloses a hybrid algorithm based on a classical discontinuous finite element and a variational quantum linear solver, relates to the technical field of quantum-classical hybrid computing crossover, and comprises the following steps: adopting a discontinuous finite element method to perform spatial dispersion on fluid control equations, using a high-order basis function to describe internal solution of a unit and exchanging unit interface information through numerical flux to form a semi-discrete form of a common differential equation group; adopting an implicit time advancing format on the semi-discrete common differential equation group to convert the physical quantity updating problem of the current time step into a solving task of a high-dimensional sparse linear equation group; applying a generalized minimum residual method on the high-dimensional sparse linear equation group on a classical computing platform, constructing a set of orthogonal basis vectors of a Krylov subspace through an Arnoldi process, and projecting the original equation group to the low-dimensional subspace to obtain a dense linear system with reduced dimension; and constructing a variational quantum solving process of an adaptive noise-containing medium-scale quantum processor based on the low-dimensional dense linear system.

This invention discloses an optimized scheduling method for a coal preparation power supply system, comprising the following steps: acquiring power flow and material flow parameters and importing and defining decision variables; establishing a multi-equipment, multi-condition power consumption model for the coal preparation plant, and combining the coupling relationship of power flow-coal flow-water flow-medium flow to establish a two-layer low-carbon optimized scheduling model for the coal preparation plant power supply system; importing the day-ahead production plan and the day-ahead wind and solar power forecast output, and initializing the time period parameter t=1; calling a linear solver to solve the upper-level model, solving for the coal bunker inventory, the transport capacity of the belt conveyor between coal bunkers, the production volume of the workshop, and the scheduling plan of the power flow; using the particle swarm optimization algorithm to solve the lower-level model, solving for the operating speed of the front-end transport equipment of the processing equipment; exporting the solution results of the lower-level model and feeding them back to the upper-level model, updating the production capacity of each workshop, and determining whether the time period is greater than or equal to 96. If it is, the final scheduling scheme is generated; otherwise, the above steps are repeated until the time period condition is met.

A system and method is provided for solving systems of binary-valued linear equations using a quantum information processing (QIP) system. The present disclosure describes solving linear systems modulo 2 on a quantum computer. An exemplary method includes defining a quantum circuit implementing matrix-vector products with a number of gates proportional to the number of non-zero entries in the coefficient matrix and then deriving a variational cost function that may be optimized to produce a solution to the given system. Compared to other quantum linear solvers, the present disclosure may work on matrices of any size and rank.

The application discloses a kind of solving method and device of quadratic nonlinear equations based on quantum circuit, method includes: obtaining target linear equation group, target linear equation group is determined according to initial quadratic nonlinear equation group conversion, constructs the quantum circuit corresponding to quantum linear solver, runs quantum circuit and measures, to solve target linear equation group, based on the solution of the solved target linear equation group, determine the solution of initial quadratic nonlinear equation group, using the relevant characteristics of quantum, realize a kind of can satisfy quadratic nonlinear equation solving technique, reduce the complexity and difficulty of solution.