50 results about "Bisection method" patented technology

The invention relates to a rapid visible time window calculation method for large-scale satellite group cooperation. The method comprises the following steps: establishing an analytic relationship between time and a satellite latitude argument based on a rapid analytic orbit model; calculating a rough moment when the sub-satellite point trajectory of the satellite intersects with the target declination circle; screening potential coverable circles in combination with satellite side sway and a field angle; for each circle, accurately calculating the positive side-looking moment of the satellite to the target by iterating the spherical geometrical relationship; and finally, by taking the moment as a reference, performing forward and backward recursion by using a high-precision model in combination with a dichotomy to determine accurate starting and ending moments of the visible window. According to the method, the defects that a tracking propagation method is high in calculation precision but high in calculation cost can be overcome, and the preprocessing efficiency of a ground or satellite-borne task planning system is improved; meanwhile, the problem of low precision in the prior art is solved, a solution is provided for satellite-borne window calculation of a large-scale satellite group cooperative task planning system, and online and high-precision calculation of single-satellite and satellite group visible windows during large-scale satellite group cooperation is realized.

The invention belongs to the field of magnetic target body positioning, and relates to a measuring line vertical gradient-based magnetic multi-target positioning and magnetic moment inversion method, which comprises the following steps of: obtaining a unit orthogonal primary function and a primary function coefficient corresponding to each component of magnetic anomaly gradient data vertical to a measuring line, and calculating an energy curved surface of the magnetic anomaly gradient data vertical to the measuring line; detecting a local energy peak value of the energy curved surface, obtaining an energy peak value ratio sequence, obtaining a target number and horizontal position estimation corresponding to the target according to an energy sudden change value in the energy ratio sequence, and calculating a target depth corresponding to a measuring line vertical magnetic anomaly gradient energy extreme value by using a dichotomy method, and constructing a linear equation set about the target magnetic moment by using the measuring line vertical magnetic anomaly gradient data and the unit orthogonal basis function, and obtaining target magnetic moment parameter estimation through a least square method. According to the invention, the anisotropy difference of the estimation precision of the horizontal position of the target is effectively reduced, and the problem of target detection omission caused by large difference between the target burial depth and the magnetic moment module value in multi-target positioning is improved.

The invention discloses a satellite planning and scheduling method, medium and equipment based on enhanced multi-population inheritance, and relates to the field of multi-satellite imaging task scheduling, and the method comprises the steps: constructing a constraint model and a target function of multi-satellite task scheduling; calculating the conflict degree of the visible time window of each satellite resource, and allocating the visible time window with the conflict degree of 0 to a task to complete scheduling preprocessing; generating satellite resources and visible time window initial solution individuals of satellite task scheduling by adopting a bisection method; a double-population genetic algorithm is adopted, one population is used for exploring a new allocation scheme, the other population is used for optimizing a task planning result under a specific allocation scheme, and population communication is carried out based on reinforcement learning; and performing task insertion based on time relaxation according to a multi-satellite task scheduling solution obtained by the double-population genetic algorithm, and if task insertion cannot be performed, performing task replacement to obtain a final scheduling scheme. According to the method, the problem of complex multi-satellite imaging scheduling can be solved.

The invention discloses a deep reinforcement learning power distribution network-micro-grid optimal scheduling method based on a dichotomy, and the method comprises the following steps: constructing a power distribution network-micro-grid system model which comprises a first scheduling model and a second scheduling model; training an intelligent agent by using a deep reinforcement learning algorithm, and searching an action space of the deep reinforcement learning algorithm by using a dichotomy during training; and performing real-time optimal scheduling on the power distribution network-micro-grid system model by using the trained intelligent agent. Compared with the existing method, the method provided by the invention has the advantages that the operation cost of the power distribution network system is reduced, the comprehensive benefit of the micro-grid is improved, and the cooperative operation efficiency of the power distribution network-micro-grid system is improved.

The present invention proposes a method, device and equipment for calculating line loss in a distribution network interval with distributed power access, comprising: collecting distribution network system data; establishing an objective function based on the distribution network system data to obtain an interval value of line loss of the distribution network system within a time period, wherein the constraints of the objective function include flow constraints and node power limit constraints; the node power limit constraints include load node power constraints, PV node voltage constraints and PV node reactive power constraints; the load node power constraints include interval constraints and power constraints, and the PV node refers to a node with a given active power P and voltage amplitude V; splitting the interval constraints by a bisection method, and replacing the equation containing the integral of the power constraint with the power constraint sum equation according to the segmentation result of the interval constraint; obtaining a linear programming of the line loss fluctuation interval based on the above constraints and the objective function, and solving the linear programming to obtain the distribution network interval line loss.

The present application relates to the technical field of satellite altimetry and ocean surveying and mapping, and in particular to a GNSS-R sea surface height measurement method based on variable step line segment intermediate frequency data processing, which can effectively improve the measurement accuracy and efficiency, comprising obtaining satellite-borne GNSS-R original intermediate frequency data, calculating mirror reflection points through a new variable step line segment (NVSLSM), generating a delay Doppler map (DDM), and performing sea surface height inversion. Compared with the prior art, the NVSLSM is used to process the mirror reflection points, the calculation time is increased by about 2.04 times and 1.47 times compared with the line segment bisection method and the QH method, and on the premise of ensuring the convergence accuracy, the stable solution can be reached through fewer iteration steps, thereby reducing the calculation cost per sample; in the delay Doppler map generation link, the overall calculation efficiency is increased by more than about 90%.

The present invention provides an active suspension control method, which includes the following steps: constructing a state space equation of the model according to the established dynamic model of the multi-variable non-linear active suspension to obtain an active suspension system model; linearizing the multi-variable non-linear links in the active suspension system model to obtain a corresponding quasi-linear system model of the active suspension; optimizing the quasi-linear system model of the active suspension by the Lagrange multiplier method, and solving by the bisection method to obtain the feedback gain K of the multi-variable non-linear active suspension and the feedback control law of the multi-variable non-linear active suspension. By adopting the above method, not only the non-linear problem of the inherent components is solved, but also the network non-linear problem is considered, improving the control accuracy and the stability of the system. At the same time, because the method is simple to reproduce, it is easy to implement in actual work.

The invention provides a low-altitude space-time grid division method, system and device, a medium and a program product. The low-altitude space-time grid division method comprises the steps that a low-altitude space domain is divided into a space domain plane dimension, a space domain height dimension and a time dimension; progressively dividing the spatial domain plane dimension into a plurality of plane hierarchies according to longitude and latitude directions; dividing the spatial domain height dimension into a plurality of height levels by adopting a recursive dichotomy; dividing natural days for the time dimension, and progressively dividing the natural days into a plurality of time levels; and dynamically selecting the plane hierarchy, and / or the height hierarchy, and / or the time hierarchy based on management and control requirements. According to the method, the optimal space-time precision grade can be intelligently matched according to the attributes and control requirements of a specific region, so that the differentiated control granularity requirements in a global range are efficiently and uniformly adapted. The characteristic integrating high efficiency, flexibility and uniformity provides indispensable underlying support for refined low-altitude management and control application requiring extremely low delay response and high concurrent processing capability.

The invention relates to a bending moment-curvature calculation and characteristic state recognition method and system for a UHPC composite beam and a storage medium, and the method comprises the steps: obtaining geometric parameters and material parameters of the UHPC composite beam, and building a nonlinear constitutive model of each material; unit layer division is carried out on the cross section of the UHPC composite beam, and an initial value of the curvature of the cross section is given; acquiring an approximate solution of the neutral axis by using a dichotomy, and acquiring an accurate solution of the neutral axis by using a Newton method based on the approximate solution of the neutral axis; calculating strain and stress of each unit layer based on plane section assumption, and judging whether the UHPC composite beam is damaged or not; if the UHPC composite beam is not damaged, calculating the bending moment value of the UHPC composite beam, identifying the current characteristic state and recording the curvature and the bending moment value, then updating the curvature of the cross section and recalculating the accurate solution of the neutral axis; and if the damage occurs, outputting a curve of the curvature-bending moment value of the cross section. According to the method, the requirements of calculation and analysis of the composite beam under the sagging moment and the hogging moment can be met.

The present application relates to the technical field of satellite altimetry and ocean surveying and mapping, and in particular to a GNSS-R sea surface height measurement method based on variable step line segment intermediate frequency data processing, which can effectively improve the measurement accuracy and efficiency, comprising obtaining satellite-borne GNSS-R original intermediate frequency data, calculating mirror reflection points through a new variable step line segment (NVSLSM), generating a delay Doppler map (DDM), and performing sea surface height inversion. Compared with the prior art, the NVSLSM is used to process the mirror reflection points, the calculation time is increased by about 2.04 times and 1.47 times compared with the line segment bisection method and the QH method, and on the premise of ensuring the convergence accuracy, the stable solution can be reached through fewer iteration steps, thereby reducing the calculation cost per sample; in the delay Doppler map generation link, the overall calculation efficiency is increased by more than about 90%.

The present invention belongs to the technical field of ultra-large scale integrated circuit testing, and discloses a TSV test grouping method based on neural network. By combining a self-designed neural network and a loss function, test constraints are written into the loss function, and the gradient descent method is used to continuously optimize the weights to solve the specific test grouping scheme under a fixed number of test groups; and an improved bisection method is used to solve the minimum number of test groups, improving the robustness of the grouping algorithm. Experimental analysis proves that the method proposed by the present invention performs excellently in terms of grouping accuracy and running efficiency under an irregular TSV layout.

The invention provides an anisotropic large-scale structure attitude adjustment trajectory planning method which specifically comprises the following steps: firstly, carrying out dynamic modeling on an attitude adjustment mechanism by adopting a Newton-Euler method so as to calculate driving force of each shaft of a positioner during attitude adjustment of a large-scale structure; dividing the attitude adjustment track into an acceleration section, a constant speed section and a deceleration section, fitting the attitude adjustment track by using a quartic polynomial, and calculating track parameters of the large structure in different directions; and finally, constructing a positioner driving force and speed constraint model, and performing attitude adjustment duration search by adopting a dichotomy, thereby improving the efficiency of attitude adjustment of the large-scale structure. According to the method, different time parameters (the proportion of a constant-speed section) are adopted for planning the motion trails of the large-scale structure in different directions, the performance of a servo control system can be brought into full play, and therefore the attitude adjustment efficiency of the large-scale structure is improved.

The invention relates to the technical field of hydraulics and river dynamics, and discloses a river channel scouring coarsening parameter determination method, device and equipment and a storage medium, in the calculation process, the target water flow condition is determined by adjusting the initial parameter, and the dynamic change of the water flow condition in the actual scouring process can be reflected. Furthermore, relevant parameters under different particle sizes can be accurately estimated through a dichotomy and a linear interpolation method, so that relatively accurate initial accumulative gradation is obtained. Furthermore, a bed sand gradation coarsening calculation method in the preset bed load scouring process is utilized to adjust the initial accumulative gradation, and the influence of the bed load on the bed sand gradation in the scouring process is considered, so that the calculation result is more in line with the bed sand change condition in the actual scouring process. Finally, the target river channel scouring coarsening parameter set is determined by comparing the target accumulative gradation with the preset threshold value, the accuracy of river channel scouring coarsening calculation is remarkably improved, and errors in actual engineering are reduced.

This invention presents a power system risk assessment and reactive power optimization method and system based on Inductively Coupled Logic Optimization (IGDT). It establishes a deterministic reactive power optimization model with the objective of minimizing the linear weighted average of system network losses, voltage deviations, and operating costs, and solves this model to obtain a baseline optimal solution. For the uncertainty of renewable energy output and load power, IGDT is used for modeling, constructing a robust optimization model with the objective of maximizing the range of uncertainty fluctuations. Finally, the optimal solution is obtained by iteratively solving the IGDT robust optimization model using a bisection method. This invention effectively quantifies the voltage exceedance risk immunity level and system performance, providing dispatchers with clear and quantitative decision-making basis. It eliminates the need to rely on the probability distribution of uncertain variables, significantly reducing computational complexity. Simultaneously, it considers system economy and security, improves the robustness and flexibility of grid operation under high-proportion renewable energy integration, provides an optimal dispatch strategy to minimize risks, and achieves optimized operation under controllable risks.

The invention discloses a robustness verification method and system based on a source code pre-training model and a storage medium. The method comprises the steps of obtaining a model and extracting code data features to obtain a token sequence; performing slicing processing on the token sequence; sampling token sequence slices and recombining to obtain a random token sequence; designing a classification loss function and finely adjusting the large pre-training model; taking the random token sequence as the input of a large pre-training model to obtain a classification label predicted by the model; calculating self-confident degree of classification according to classification labels obtained by multiple times of model prediction, and obtaining output prediction of the large pre-training model; constructing a new token sequence based on the editing distance; and calculating the robust radius according to the boundary of the confidence value of the predicted label and a dichotomy. According to the method, the problem that the robustness is difficult to guarantee due to the fact that an existing random smoothing method is difficult to perform unified modeling due to complex disturbance in a source code scene in an existing method and a large pre-training language model cannot perform fine processing on various features is solved.

This application proposes an encoding method for holographic computation. The method includes: classifying different types of curves based on the morphological distribution of etched lines; calculating the coordinates of discrete points on the etched lines; dividing the index intervals of different curves according to their feature points using Newton's iteration method; and fitting the arc by finding the optimal solution of the set of feature point coordinates that can be fitted using a bisection method. The curves are closed curves, spiral curves, or non-spiral curves. This encoding method significantly reduces the amount of data required for etched line coordinates, achieving encoding with a small data volume, and the calculation process is simple. High-precision encoding can be achieved by setting the encoding precision.

This invention provides an adaptive HP filtering method based on convex optimization of the spectral characteristic function. The method includes converting the numerical value of the fluctuation term coefficient λ in the HP filtering method into the value of the trend term spectral characteristic function, and calculating the trend term spectral characteristic function value using a downward convexity discrimination method based on binary tree traversal. Based on the continuous monotonicity property of the trend term spectral characteristic function value, the selection of the value of λ is transformed into a convex optimization problem of the trend term spectral characteristic function value, and the optimal λ is quickly solved using a bisection method, ultimately obtaining the optimal λ value. Adaptive HP filtering is then performed based on the optimal λ value. This invention effectively achieves adaptive selection of the HP filtering parameter λ and significantly reduces computational complexity, realizing fast adaptive filtering.

This invention, belonging to the field of mechanical processing, proposes a supervised learning-based streak threshold segmentation method. First, laser streak images are acquired and positioned, and a dataset is generated. The training results are used as a classifier. A boundary threshold is determined through a bisection method, and the optimal threshold is evaluated based on the second-order moment, achieving rapid and accurate segmentation of laser streaks from the surrounding background. This method addresses the difficulty of image processing under the influence of various significant and complex background noises, enabling accurate segmentation of laser streaks from the surrounding background in complex industrial environments. Furthermore, by adding a penalty factor to the loss function of a deep neural network, high classification accuracy is achieved for only the C1 type.

The application discloses a speed planning method, device, storage medium and computer program, and the method comprises the following steps: acquiring actual displacement and planned displacement of a system in a previous motion period, and judging whether the actual displacement is equal to the planned displacement; if the actual displacement is equal to the planned displacement, using actual terminal speed and actual terminal acceleration of the previous motion period as starting speed and starting acceleration of a current motion period; if the actual displacement is not equal to the planned displacement, using a speed planning model of the previous motion period and combining a bisection method to approach planned terminal speed and planned terminal acceleration of the previous motion period as starting speed and starting acceleration of the current motion period under the condition that a difference between the actual displacement and the planned displacement of the system in the previous motion period is not more than a preset difference. Based on the foregoing steps, the system can adopt more suitable starting speed and starting acceleration for speed planning in the current motion period, so that the actual speed curve of the system is smoother, vibration of a machine tool is avoided, and the quality of a processed product is ensured.

The present invention discloses a method for determining the critical desorption pressure of a coalbed methane reservoir based on mid- to late-stage production data, comprising: assuming that the water saturation of the reservoir is stable and the desorption zone expands at a uniform rate in the mid- to late-stage coalbed methane development, linearizing the mid- to late-stage gas production equation, analyzing the linear relationship between #imgabs0# and the number of production days t using a graphical method, and obtaining a gas production data analysis equation; linearizing the mid- to late-stage water production equation, analyzing the linear relationship between #imgabs1# and the number of production days t using a graphical method, and obtaining a water production data analysis equation; and jointly solving the gas and water production data analysis equations, iteratively solving the critical desorption pressure of the coalbed methane reservoir using a bisection method. The present invention inverts the critical desorption pressure based on mid- to late-stage coalbed methane production data, providing a simple and highly adaptable production data analysis method that facilitates the formulation of coalbed methane development plans and capacity forecasting.

This invention relates to the field of radar signal processing technology, and particularly to an MTD filter design method based on particle swarm optimization, comprising the following steps: S1: Obtaining the Doppler center frequency range and normalized half-width based on the radar type and clutter type to obtain constraints, and obtaining filter information based on the constraints and the global pilot vector matrix; S2: Designing a fitness function based on a nonlinear function and a hard-coded threshold; S3: Designing the filter based on the fitness function, and iteratively updating the filter using a main lobe width bisection method to obtain the optimal filter. This invention achieves optimized design by constructing linear and nonlinear multi-parameter fitness functions, while satisfying the requirements for stopband attenuation, null depth, and clutter bandwidth. Furthermore, it uses a bisection method for iterative optimization of the main lobe width, achieving high robustness under different clutter environments, improving the design efficiency of the MTD filter, reducing main lobe broadening, and lowering filter gain loss.

The application is a kind of closed-loop dynamic optimization-based generation method of fixed porosity heterogeneous honeycomb structure. It includes: setting the macroscopic design parameters of the target plate; taking the total number of random seed points as the only variable to initialize the binary search interval; in the optimization iteration, based on the current point number, boundary mirror image anti-distortion and Voronoi partition are performed, effective common edges are extracted and equally offset to generate continuous entities without broken walls; finally, the actual porosity is calculated, and the seed point interval is updated by using the bisection method in a closed loop until the error converges. The application realizes the precise control of macroscopic porosity and the high disorder of microscopic force transmission path under the premise of complying with the wall thickness limit of additive manufacturing, and provides a high-quality geometric model for impact-resistant protection design.

The system comprises an identification module and a comparison module, the identification module is used for new energy controller electromechanical model parameter identification, the parameter identification is based on hardware-in-the-loop measured data, and the comparison module is used for comparing the hardware-in-the-loop measured data with the hardware-in-the-loop measured data. The value of the drop impedance in the identification model is automatically modified by writing a binary search optimization algorithm until the drop voltage identification precision requirement is met, and an optimal identification result is automatically output; the comparison module is used for performing new energy electromechanical transient modeling test, verifying the correctness of a drop impedance identification result in the identification module, automatically performing electromechanical transient simulation by setting different test working conditions, and automatically performing error analysis on each simulation result and a hardware-in-loop test result; according to the method, traditional manual testing work is replaced, parameter identification and electromechanical transient modeling testing can be automatically carried out, result data are automatically stored, and the precision and collection efficiency of a new energy electromechanical simulation model are greatly improved.

A method, system, device and computer-readable storage medium for solving a bridge model, which relates to the field of engineering structure tests, includes determining a first function value based on the target parameters of a target bridge damper and a preset lower bound of spring displacement, where the target parameters include target total displacement, displacement of the damping section at the previous moment, step size, damping coefficient, reference velocity and spring stiffness; determining a second function value based on the target parameters and a preset upper bound of spring displacement; determining spring displacement based on the bisection method, target parameters, first function value and second function value, and determining the nonlinear damping force based on the spring displacement and spring stiffness; constructing a balance equation based on the mass matrix, proportional damping matrix, stiffness matrix, nodal acceleration, nodal velocity, nodal displacement and nonlinear damping force; performing modal decomposition on the balance equation to obtain modal equations of each order, and solving the modal equations of each order based on the explicit integration method to obtain modal displacements of each order. This application improves the efficiency of solving the bridge model.

The invention discloses a crowned blade dynamic modeling and response calculation method considering stick-slip motion, which comprises the following steps of: 1, establishing a dynamic model of a crowned blade system under two-dimensional rub-impact motion by combining first-order bending vibration of the crowned blade in the x direction and the y direction; 2, combining normal and tangential relative motion between adjacent blade crowns, establishing a viscous-sliding-separation boundary condition, and determining collision force and friction force at different rub-impact stages; and step 3, capturing key points of viscosity-sliding conversion between adjacent blade crowns by adopting a dichotomy method, and establishing a crown blade response calculation method considering the stick-sliding motion according to a differential equation numerical solution to predict vibration responses of the crown blade under different key parameters. According to the method, the dynamic modeling precision of the shrouded blade system and the response prediction precision of the shrouded blade are improved.

The invention relates to a URL duplicate removal method and system for dynamic website XSS vulnerability detection, and the method comprises the steps: firstly, extracting URL features, JavaScript behavior features, form structure features and DOM structure features of a website page; secondly, splicing the extracted features into a multi-dimensional feature vector, and calculating the multi-dimensional cosine similarity of any two URL pages by adopting a cosine similarity algorithm; thirdly, determining an optimal similarity threshold value through a bisection method in combination with artificial label data or a website sample set; and finally, removing the URLs exceeding the threshold value based on the optimal similarity threshold value. According to the method, structural feature extraction and a multi-dimensional similarity measurement mechanism are fused, so that good self-adaptability is achieved, the discrimination capability and processing efficiency of a Web crawler system can be effectively improved, the repeated capture proportion is reduced, and the overall performance of vulnerability detection and page analysis tasks is improved. Experimental results show that compared with a traditional method, the method has the advantages that repeated URLs can be recognized and removed more accurately, and the misjudgment rate is remarkably reduced.

The invention discloses a moving plate three-laser-head cooperative machining path zoning planning method which comprises the following specific steps: dividing a cutting area along a Y direction by using a layered dichotomy so as to divide the cutting area into three areas; the three areas divided in the first step all take the shortest dynamic operation time as an optimization target, and according to inherent parameters of current equipment, a machining track with the shortest dynamic motion time in each area is obtained through solving; and taking the minimum value in the maximum values of the processing time of the three cutting areas, and continuously iteratively updating in the partition search until the partition search is completed and the path partition planning is synchronously completed. According to the method, through a complete search strategy for the regions, the shortest processing time is taken as a path optimization target in the partitions, and an automatic track interruption mechanism is integrated, so that accurate and efficient acquisition of the processing tracks of the three regions is realized, and the equipment processing efficiency is improved.

This invention relates to the field of heat exchanger optimization design technology, specifically an optimization design method for a spiral tube heat exchanger. The method includes: obtaining the heat exchanger's process operating conditions and structural parameters; establishing a calculation model for heat transfer and flow resistance in the tube and shell sides; using a bisection method to iteratively calculate the outlet temperature of the tube and shell side medium; calculating the corresponding pressure drop; constructing a multi-sub-objective function that characterizes heat transfer performance, flow resistance, entropy production characteristics, and manufacturing cost; and using a differential evolution algorithm framework to optimize the system, conducting multiple iterations with structural parameters as variables. In each generation, modeling, temperature calculation, pressure drop calculation, and objective function evaluation are repeatedly performed for each candidate parameter combination within the population. After convergence, the optimal parameter combination is selected as the design scheme. This invention achieves coupled temperature calculation and full-process iterative optimization, adapting to multi-dimensional design requirements.

The invention relates to a drilling fluid leakage layer searching and positioning method based on a bisection method. The drilling fluid leakage layer searching and positioning method comprises the steps that monitoring temperature data of a plurality of monitoring points with different depths set in a shaft are collected; according to the monitoring temperature data of a plurality of monitoring points with different depths, the potential leakage layer position of the drilling fluid leakage layer is preliminarily determined based on the gradient change of the temperature value along with the depth of the shaft; setting an initial search range for further fine search according to the position of the potential leakage layer; executing the following iterative processing until iteration reaches a stop condition; and based on a set strategy, determining a fine leakage layer position assumed by one iteration as a final drilling fluid leakage layer positioning position.

A method for calculating a downhole card for an oil and gas well (10) includes setting a damping factor to an initial value, calculating a downhole card using the initial load value, and determining whether the difference between a true load value and an effective load value is within a desired error tolerance. If not, the method can also include setting a new damping factor to a value equal at a mid-point between the initial damping factor and a damping factor bound, recalculating the downhole card using the new damping factor, and determining whether the difference between a new true load value and a new effective load value is within a desired error tolerance. If not, the method can also include setting the new damping factor to a value equal at a mid-point between the previous damping factor and a damping factor bound.