56 results about "Mathematical relation" patented technology

The invention relates to the technical field of offshore wind power, and discloses a bearing performance degradation evaluation method for an offshore wind power foundation structure, which effectively solves the problem of neglecting corrosion heterogeneity in the prior art by acquiring initial three-dimensional geometric point cloud data and historical service data and constructing a first finite element model. The model better fits the actual structure state; the local damage evolution and cumulative effect are simulated by means of a second finite element model, meanwhile, material degradation evaluation is combined, the interaction of three key factors including corrosion thinning, local damage and material mechanical property degradation is comprehensively considered, and the defect that the multi-factor coupling influence is not fully solved in the prior art is overcome; the extreme environment load condition is introduced to construct the third finite element model, the performance degradation law of the structure in the extreme environment can be analyzed, and then the reliability and applicability of evaluation are improved by establishing a mathematical relation model and predicting the full life cycle bearing performance.

Systems and methods for machine-learned generation of data insight summaries are provided. A computing system can obtain numerical time series data comprising a plurality of numerical values associated with a plurality of times. The computing system can identify, based on the numerical time series data, one or more first mathematical relationships in the numerical time series data. The computing system can generate, based at least in part on the mathematical relationships, a first input context comprising first natural language data indicative of the mathematical relationships. The computing system can provide the first input context to a first machine-learned sequence processing model. The first machine-learned sequence processing model can generate, based at least in part on the first input context, one or more outputs describing the one or more first mathematical relationships. The computing system can output the one or more outputs.

The invention discloses a novel structure construction method using a gradient triple-period minimal surface lattice. The novel structure construction method comprises the following steps: defining a mathematical relationship of an entity part of a TPMS lattice according to a selected scene; the standard TPMS lattice in the original cube is deformed and matched into the pyramid space, a transition structure is formed, and a final TPMS distortion structure is output; connecting the upper-layer small unit lattices with the lower-layer large unit lattices by the TPMS twisted structure to generate gradient lattices without geometric defects; the gradient between different unit numbers is controlled by controlling the size of the top plane of the pyramid; the size of the transition area is adjusted, the transformation completion distance of the substructure is changed, and then the elastic modulus is adjusted and controlled; the number of layers of the base structure in the transition area is increased, and the buffering distance of structure transformation is prolonged. The problems that in the prior art, a gradient lattice transition area has geometric defects, the adjustable range of elastic modulus is small, and stress is concentrated are solved, and the stability and durability of the structure are improved.

The present invention belongs to the technical field of autonomous driving. Disclosed are a method and apparatus for evaluating the compliance of autonomous driving. A specific embodiment of the method comprises: acquiring current traveling data generated by an autonomous driving target vehicle during traveling; acquiring parsing processing corresponding to a preset compliance engine system configuration file; and on the basis of a parsing result, calling a mathematical function library to perform compliance evaluation on the current traveling data, so as to generate a compliance evaluation result. In the present embodiment, a legal language can be converted into logical descriptions and mathematical equivalence relations; and software codes of an embedded language are generated on the basis of the logic and mathematical relations, current traveling data of a target vehicle is then evaluated on the basis of the software codes, and a compliance evaluation result is automatically generated. Thus, the compliance of autonomous driving can be automatically evaluated on the basis of the current traveling data of the target vehicle, and the solution meets the requirements of autonomous driving of the target vehicle, and is also applicable to different scenarios, thereby improving the application universality of the solution.

The invention relates to a scene modeling-based primary school mathematics application question intelligent solving guiding method and system. The method comprises the steps of obtaining a question description text of a question; the question description text is used for representing the content of the question; based on the question description text, analyzing condition parameters of the questions to obtain a question description feature map; graph nodes in the question description feature graph are subject texts and object texts of the questions, and connecting edges among the graph nodes are constructed based on relation texts of the questions; determining a scene type of the question based on a preset scene template library and the question description feature map, and obtaining a comprehensive representation vector of the question based on the scene type; the comprehensive representation vector comprises a scene type, a basic mathematical relationship template and a problem description feature map; and based on the comprehensive representation vector, predicting the solving difficulty of the question, and based on the solving difficulty, generating a question solving guide scheme of the question. By adopting the method, the problem solving guide efficiency can be improved.

The invention discloses a dynamic SQL (Structured Query Language) optimization method based on consanguinity dependency, and relates to the technical field of database query optimization. The method comprises the following steps: analyzing all indexes in a database, and dividing the indexes into atomic indexes and composite indexes; a blood relationship dependency tree is constructed according to the mathematical relationship between the indexes, each node represents one index, and each directed edge represents the dependency relationship; receiving a to-be-queried index set, and recursively searching all dependent target atomic indexes based on the graph structure; grouping the target atomic indexes according to data sources, and generating corresponding SQL query statements; and executing the SQL statement, and calculating a final query index result after obtaining an atomic index value. According to the invention, through unified management of the index dependence structure, repeated calculation across indexes is eliminated, the query performance is improved, the resource consumption is reduced, and the index development and maintenance efficiency is improved.

The present application provides data compression for neural networks. Systems and methods for generating representative values for a data set determine a first common value by first compressing a portion of values in the data set and a second common value by further compressing a subset of the portion of values. The representative value is generated by taking a difference between the first common value and the second common value, where the representative value corresponds to a mathematical relationship between the first and second common values and each value within the subset of the portion of values. The representative value requires less storage than the first and second common values.

The embodiments of the present application disclose a method and device for estimating the six-degree-of-freedom pose of a target based on binocular vision and particle swarm optimization, which relates to the field of computer vision. The method comprises: obtaining a binocular image of a target; the binocular image includes at least the rotation matrix, displacement vector, and geometric features of the target; decomposing the rotation matrix into a rotation vector and a rotation angle by a rotation matrix decomposition method, uniformly sampling the rotation vector and the rotation angle in six degrees of freedom to obtain a data point set; establishing a mathematical relationship between the rotation matrix and the displacement vector based on the geometric properties of the geometric features and the data point set; and performing target pose estimation on the binocular image of the target by designing an objective function and applying an optimization algorithm to obtain a pose estimation result. The present application solves the problems of low accuracy, poor versatility, and poor robustness existing in the related art.

The invention provides a power distribution network disturbance identification method and system based on multiple time scales, and the method comprises the following steps: S1, achieving the standardized processing and noise characteristic modeling of measurement data through building a mathematical relation among node voltage, a phase angle and a measurement quantity, and reflecting a system topological structure and parameter sensitivity through a Jacobian matrix; s2, firstly, based on the step S1, capturing dynamic feature changes in different time ranges; extracting features through feature engineering, optimizing a feature set by adopting a recursive feature elimination method, and improving the accuracy and stability of the model; s3, after the classification framework preliminarily confirms that a traditional event belongs to a large class, training and verifying feature data extracted in the previous step by adopting an XGBoost algorithm, realizing high-precision identification of multiple classes of disturbance events through hyper-parameter optimization and cross validation, and outputting an event class and a confidence result; according to the technical scheme, intelligent analysis of the operation state of the power distribution network and accurate identification of abnormal events can be realized.

The present application relates to a kind of improved radiation transmission model mangrove chlorophyll estimation method, comprising: the measured data of the tree height, crown width and leaf area index of mangrove are collected;Mathematical relationship between leaf area index and tree height, crown width is constructed;Simulated spectral data is generated as training set using improved radiation transmission model;The sensitive feature screening of mangrove functional traits is carried out;Random forest inversion model based on physical constraint is constructed;The present application estimates the chlorophyll content of mangrove using the random forest inversion model based on physical constraint.The beneficial effects of the present application are: the present application can effectively improve the precision of chlorophyll inversion, provide scientific basis for the fine inversion of mangrove chlorophyll, provide data support and decision-making reference for the protection and scientific management of mangrove.

This invention presents a method for establishing large deformation viscoelastic constitutive relations based on Prony technology. It addresses the problems of existing viscoelastic constitutive models lacking universality, and the complexity and programming difficulties associated with their mathematical relationships. The invention includes: decomposing the stress tensor into the sum of the deviatoric stress tensor and the mean stress; decomposing the strain tensor into the sum of the deviatoric strain tensor and the mean strain; and providing a convolutional expression for the deviatoric stress tensor and the mean stress. The increment of the deviatoric stress tensor is expressed as a function of the deviatoric strain increment, and the increment of the mean stress is expressed as a function of the mean strain increment. The tensor form of the incremental constitutive relation is written in matrix form. This method has been programmed, and the numerical results obtained from the program agree well with the experimental results in specimen-level experiments on solid rocket motor propellant grains.

The invention relates to a dual-mode control method and system suitable for a network construction type energy storage converter, and the method comprises the steps: building a power and virtual impedance dynamic mapping model, and achieving the dynamic mapping between the power and virtual impedance through building a mathematical relation model between the power and virtual impedance; a state prediction and compensation mechanism is introduced, a feedforward compensation link based on a system state prediction algorithm is designed, transient behaviors possibly occurring in the switching process are subjected to prospective suppression, a self-adaptive virtual impedance adjustment strategy is designed, and dual-mode seamless switching control is achieved. According to the invention, efficient and stable switching of the energy storage converter in the island and grid-connected operation states is ensured. Key technical support is provided for a smart power grid, and the flexibility and reliability of a power system are remarkably improved.

The invention discloses a method for determining a theoretical basis for online monitoring of machining size deviation of a micro-boring small deep hole, and relates to the technical field of machining and monitoring of the micro-boring small deep hole. The method comprises the following steps: extracting specific numerical values of a tool nose flutter amplitude, a boring force average value and a tool nose abrasion loss of a micro-boring tool under the same working condition, then establishing a quantitative relation between the tool nose flutter amplitude and the boring force average value, and establishing a mathematical relation between the tool nose abrasion loss and the boring force average value; and finally, by taking the equivalent boring force as an intermediate value, establishing a mathematical relationship between the tool nose fluttering amplitude and the tool nose abrasion loss, and requiring that the sum of the tool nose fluttering amplitude value and the tool nose abrasion loss value does not exceed the limit value of the machining size deviation value of the deep small hole. Therefore, the upper limit values of the tool nose flutter amplitude and the tool nose abrasion loss are reversely solved according to the limit value of the deviation value of the machining size of the deep small hole, final experimental correction is conducted, and finally the determination method of the basis is formed.

The invention discloses an arbitrary thread form hexahedral mesh modeling method based on parameterization control, and relates to the technical field of bolt modeling. Decomposing the tooth profile of the complete pitch cycle corresponding to the target tooth angle into a plurality of feature line segments, converting the curve profile corresponding to each feature line segment into a solvable geometrical relationship, and determining a mathematical relationship of any point coordinate on the profile corresponding to each feature line segment; integrating the mathematical relationships corresponding to the feature lines to obtain an external thread curve formula of the target thread angle; parameterizing an external thread curve formula of the target thread angle through an equation driving curve function in SOLIDWORKS software to obtain an external thread profile curve of the target thread angle bolt; and based on the external thread profile curve of the target thread angle bolt, drawing a two-dimensional plane grid of the bolt, and further obtaining a three-dimensional thread hexahedral grid of the target thread angle bolt. By means of the method, modeling of any thread form can be achieved, and the application range of finite element analysis is greatly expanded.

The invention relates to the technical field of wind tunnel tests, and discloses a flutter wind tunnel test pulse response generation method and system oriented to turbulence excitation, and the method comprises the steps: model construction: constructing a mixed Transform generative model through combining a convolution sampling method and a depth feature extraction method, establishing a mathematical relationship between a turbulent flow response signal and a pulse response signal in the structural dynamics system through a hybrid Transform generative model; model training: preprocessing the data by adopting different normalization modes according to a model training effect; optimizing the model by adopting a loss function mixed by mean square error of a time domain and a frequency domain through a plurality of training optimization methods; and signal generation: taking the measured turbulence response signal as input, and generating a corresponding pulse response signal. According to the invention, turbulence response signals dynamically collected in a wind tunnel can be directly converted into pulse response signals.

The invention discloses a finite iteration learning control method based on a neural network, which is used for solving the technical problem of realizing accurate tracking control of a magnetic control shape memory alloy actuator within a finite iteration number. The method comprises the following steps: 1) utilizing a neural network to approach a nonlinear function in a control law, improving the adaptability and learning ability of a controller, and realizing accurate tracking control of a magnetic control shape memory alloy actuator in finite iteration; and 2) based on a compression mapping principle and a Lipschitz condition, deriving a mathematical relationship between a tracking error and an upper bound of the number of iterations, giving a sufficient condition for system convergence, and providing a theoretical basis for controller design. Compared with the prior art, the method has better adaptability and convergence speed, is particularly suitable for precision control in a complex industrial process, and has a wide application prospect.

The present invention discloses a 3D printing control method and system based on multi-nozzle flow data. The method comprises: obtaining historical flow data and historical printing plans for multiple nozzles of the same caliber for a target 3D printing device; the historical flow data includes flow data for multiple different printing materials; fitting and analyzing the historical flow data and historical printing plans based on a dynamic programming algorithm to obtain a mathematical relationship model between the flow rate and time of the target 3D printing device; obtaining real-time flow data and real-time printing material type of the target nozzle; and determining whether the target 3D printing device has an abnormal printing speed based on the mathematical relationship model, the real-time flow data, and the real-time printing material type. This method can efficiently and accurately monitor the printing speed of a 3D printing device and determine abnormalities, thereby improving monitoring accuracy and printing stability.

The present invention provides a method, device and equipment for predicting the performance degradation of an air spring based on structural characteristics, and relates to the technical field of air springs. The method comprises: obtaining the dynamic stiffness and structural parameters of the air spring to be evaluated; inputting the dynamic stiffness and structural parameters into an air spring performance degradation model to obtain fatigue loading parameters output by the air spring performance degradation model; wherein the air spring performance degradation model is a pre-constructed model of the mathematical relationship between the fatigue loading parameters of the air spring and the dynamic stiffness of the air spring; based on the fatigue loading parameters, the fatigue life of the air spring to be evaluated is determined. This method can pre-estimate the fatigue characteristics of the air spring according to the actual application scenarios of the vehicle in the early stages of vehicle design, thereby helping to design stable and reliable air springs, improve product reliability, and shorten the development cycle, so that companies do not need to undergo many experiments to design air springs, saving development costs.

The invention relates to the technical field of scientific simulation, in particular to a finite element model parameter optimization method and system based on an intelligent algorithm, equipment and a medium, a traditional manual iterative optimization process is converted into an automatic process through parametric modeling and automatic generation of a Python macro command, the manual operation time is remarkably shortened, and the efficiency is improved. And meanwhile, seamless connection from parameterized modeling of the finite element model to optimization result output is realized, so that the dependence on a user algorithm and programming capability is reduced, and full-process automation is realized. Secondly, multi-objective optimization and nonlinear constraint are supported, common non-convex and high-dimensional optimization problems in engineering can be flexibly processed, and the limitation of a traditional gradient algorithm on the continuity of an objective function is broken through; the response surface agent model replaces high-time-consuming finite element calculation through chaos polynomial expansion, a black box problem is converted into an explicit mathematical relationship, the dependence of an optimization algorithm on actual simulation is reduced, and the iteration efficiency is improved.

The application provides a space environment data and navigation time-frequency field data correlation analysis method, adopts a graph machine learning method, extracts space environment index abnormal moment data and navigation time-frequency field abnormal moment data respectively, and corresponds according to corresponding time. The application aims to predict navigation field data changes through space environment data, but because different data structures are not the same, simple mathematical relationships and regression learning cannot be used. Different structures of data are regarded as nodes, the nodes continue to contain sub-nodes, the relationship between nodes is learned, the above difficulties can be overcome and effective correlation rules and relationships can still be obtained. The model quantity of the application is small, the model applicability is wide, and the correlation between numbers is processed by a natural language processing method.

The invention provides a discrete memristor design method and circuit implementation based on a tangent function, and belongs to the field of circuit design, and the method comprises the steps: building a discretization iteration mathematical model of a high-frequency discrete grounding memristor, and the model is used for describing the mathematical relationship among an input voltage, a memristor current and a state variable under the AC voltage input; based on the discretization iteration mathematical model, a modular circuit frame used for achieving the model is constructed, and the modular circuit frame comprises a discrete sampling and iteration module, a memory-conductance function synthesis module and a current generation module; according to a modular circuit framework, a tangent function module and an absolute value function module are determined to construct a memristor function synthesis module, a discrete sampling and iteration module and a current generation module are matched, and circuit design of the discrete memristor based on the tangent function is completed through connection of corresponding circuit elements. The function of the high-frequency discrete grounding memristor is effectively realized, and the adaptability and the stability of the memristor in a complex circuit environment are improved.

The invention belongs to the technical field of aircraft performance design, and particularly relates to a load range model research method for a transport aircraft, which comprises the following steps of: firstly, constructing a weight parameter model for aircraft load range evaluation by combining a typical mission profile according to the maximum takeoff weight of a transport aircraft and aircraft weight statistical data; then developing a flight distance performance model for load range evaluation based on the specific range parameter of each task section of the transport plane; and finally, inputting data of different load conditions of the transport aircraft by taking the load voyage calculation model as a carrier, and calculating a corresponding voyage result and an operation efficiency result. In this way, construction of a transport aircraft load range model and evaluation of a load range result are achieved. Through an overall weight model, a mission profile model and a flight performance model of the transport aircraft, a set of mathematical relationship between key design parameters and core capability indexes of the transport aircraft is established, and the mathematical relationship is used for evaluating voyage and operation efficiency results under different load conditions. The method is visual and clear, and the calculation process is convenient.

The present application relates to the technical field of commercial vehicles, and specifically provides a robustness optimization method for a commercial vehicle suspension system, comprising the following steps: establishing a power assembly coordinate system, a power assembly mass matrix and a stiffness matrix, and constructing an expression of system natural frequency and decoupling rate; performing a transmission path analysis, and establishing a mathematical relationship between suspension design parameters and an in-vehicle target point; analyzing the sensitivity of an objective function to variables, and determining design variables and parameter variables; using an interval model to represent design variables, using a probability model to represent parameter variables, and constructing an interval-probability model to describe the uncertainty of suspension system variables; using Monte Carlo random number simulation technology to perform multi-objective robustness optimization; and performing Monte Carlo analysis on the optimization results, and evaluating the robustness of the suspension system. Based on the transmission path analysis method, the response of the suspension system and the in-vehicle target point of interest is linked, and vibration isolation and noise reduction at the vehicle level is achieved.

The invention relates to the field of computer vision and image processing, in particular to a Mediape-based hand space 3D (three-dimensional) key point resolving method, which comprises the following steps of: establishing a mathematical relationship between a hand key point space 3D coordinate and a hand key point 3D coordinate; introducing a camera projection constraint relation, and establishing a correlation model between the 2D coordinate of the hand key point and the 3D coordinate of the hand key point space; and based on the correlation model and the mathematical relationship, combining the 2D coordinates of the hand key points and the 3D coordinate data of the hand key points, and solving the spatial 3D coordinates of the hand key points. According to the method, calculation is simple, degree-of-freedom redundancy is reduced, constraint is tighter, error accumulation caused by error transmission of step-by-step optimization is avoided, the solution stability is high, and the problem that space 3D coordinates cannot be output in existing MediaPipe hand key point detection is solved.

The invention relates to a mangrove forest chlorophyll estimation method for improving a radiation transfer model. The mangrove forest chlorophyll estimation method comprises the following steps: collecting actually measured data of tree height, crown breadth and leaf area index of a mangrove forest; constructing a mathematical relationship among the leaf area index, the tree height and the crown breadth; using the improved radiation transmission model to generate simulated spectrum data as a training set; screening sensitive characteristics of mangrove forest functional traits; constructing a random forest inversion model based on physical constraints; and estimating the chlorophyll content of the mangrove forest by adopting the physical constraint-based random forest inversion model. The method has the advantages that the chlorophyll inversion precision can be effectively improved, a scientific basis is provided for fine inversion of mangrove forest chlorophyll, and data support and decision reference are provided for protection, restoration and scientific management of mangrove forests.

An edge device feature engineering application is provided. An industrial gateway device supports an interactive feature engineering tool that guides a user through an intuitive process to configure data analysis for a key performance indicator (KPI) of interest. A feature engineering interface presents an interactive model view that displays available data points organized hierarchically according to a plant, machine, machine attribute, or other element. A user can select data points from the model view that have an impact on the KPI of interest. The interface also allows the user to define an executable script that defines a mathematical relationship between the selected data points and the KPI. The configuration produces an output model that defines a reduced set of data points to collect and analyze, along with the executable script, to evaluate the relationship of the KPI's status to the reduced data point values.

The invention discloses a gravity dam deformation monitoring method based on intelligent analysis. In the service process of a dam, deformation monitoring data are usually complex, non-stable and non-linear time sequences, and a simple and clear mathematical relationship is often difficult to establish. According to the method, hyper-parameters are optimized by using a northern eagle optimization algorithm, wherein the hyper-parameters comprise an initial learning rate, a BiLSTM neuron number, a key value number of a self-attention mechanism and a regularization parameter; the optimal hyper-parameter combination is applied to a CNN-BiLSTM-Attention model, and a concrete dam deformation prediction model is formed. The method has excellent prediction precision and long-term prediction performance, and a new method is provided for high-precision prediction of dam deformation.

The application discloses a kind of MIMO ATI SAR two-dimensional ocean current measurement system parameter design methods based on genetic algorithm, comprising: the observation geometry of MIMO ATI SAR system is established, the sea surface flow field measurement system index, interference phase expression and sea surface two-dimensional velocity vector expression are determined;According to the sea surface two-dimensional velocity vector expression, the geometric configuration parameters that influence velocity vector error are determined, and the mathematical relationship between geometric configuration parameters and velocity vector error is established;Determine the MIMO ATI SAR system parameters that influence velocity vector error, establish the mathematical relationship between MIMO ATI SAR system parameters and velocity vector error;Based on the mathematical relationship between geometric configuration parameters and velocity vector error, and the mathematical relationship between MIMO ATI SAR system parameters and velocity vector error, establish the sea surface two-dimensional velocity vector error objective function;Based on genetic algorithm, the sea surface two-dimensional velocity vector error objective function is solved, and the optimal geometric configuration parameters of MIMO ATI SAR system and optimal MIMO ATI SAR system parameters are obtained.

The present application belongs to the field of geophysical exploration, and particularly relates to a method for calculating acoustic curve by using elastic parameters of drilling core to constrain, which comprises the following steps: step 1, obtaining logging resistivity curve of drilling in a study area; step 2, obtaining core samples of different lithology at each depth of the drilling; step 3, measuring elastic parameters of the core samples, including acoustic velocity and resistivity; step 4, establishing mathematical relationship of resistivity and acoustic velocity parameters of different strata and different lithology; step 5, establishing geological model of the drilling according to logging results of the drilling; and step 6, calculating acoustic velocity curve of the drilling based on the geological model of the drilling and the fitted mathematical relationship. The method can obtain accurate stratum acoustic curve by calculating pseudo-acoustic curve through the constraint of elastic parameters of drilling core.

The invention discloses a magnetic field source positioning method and system based on a power transmission line magnetic gradient tensor, and the method comprises the steps: constructing a magnetic gradient tensor model at any point M of a space based on the characteristic that the change rate of a space magnetic field of a long and straight current-carrying wire in the axial direction is zero, and solving a characteristic value, a characteristic vector and a spectrum norm of the magnetic gradient tensor model. And establishing a mathematical relationship between the distance from the power transmission line to the point M and a magnetic gradient tensor spectrum norm, and determining a lead direction and a geometrical relationship between a direction vector from the lead to the point M and two non-zero feature vectors of the magnetic gradient tensor, thereby realizing magnetic field source positioning. The method is efficient in calculation and high in positioning precision, can effectively suppress geomagnetic field interference, is suitable for wire positioning and tracking in unmanned aerial vehicle power inspection, and has good engineering application value.