171 results about "Real arithmetic" patented technology

The invention provides a lead screw precision milling closed-loop optimization and real-time control process based on multi-axis linkage, which comprises the following steps of: acquiring geometric parameters of a workpiece, material attributes and kinetic parameters of a machine tool, designing a cutter and clamp scheme, and setting initial processing parameters based on a cutting database; constructing a lead screw spiral groove high-precision curved surface model by using an NURBS curve, and optimizing a path through curvature adaptive discretization and quintic spline interpolation; an idle stroke path is iteratively optimized by adopting a real number coding genetic algorithm, and the total time of the path and the reversing frequency are shortened; multi-axis synchronous control is achieved through inverse kinematics solution, and the cutter inclination angle is dynamically adjusted in real time based on the contact angle; and virtual simulation and finite element analysis are utilized to predict cutting force, thermal deformation and interference risks. According to the method, the continuous and smooth multi-axis synchronization instruction is generated, the positioning error of each axis is effectively reduced, meanwhile, the cutter inclination angle is dynamically corrected through force feedback of the contact angle, cutting force fluctuation is effectively restrained, and it is ensured that the tooth surface roughness of the spiral groove meets the requirement.

The embodiment of the invention discloses a precision positioning acceleration method and device based on a low earth orbit satellite / LSTM neural network. The method comprises the steps that a terminal obtains a wide lane phase decimal deviation product, a narrow lane phase decimal deviation product and a first GNSS combination observation value which are generated by a server based on an LSTM method and are subjected to coding processing; determining a first GNSS wide lane real number ambiguity according to the first GNSS wide lane real number Based on a precise point positioning algorithm, determining initial GNSS ionosphere elimination combination real ambiguity and other parameters; performing inter-satellite single difference on the first GNSS wide-lane real number ambiguity, and obtaining the integer ambiguity by combining wide-lane phase decimal deviation product fixation; performing inter-satellite single difference on the initial GNSS ionosphere-free combination real ambiguity, determining a first GNSS narrow-lane real ambiguity by combining the wide-lane integer ambiguity, and fixing the first GNSS narrow-lane real ambiguity by using a narrow-lane phase decimal deviation product through a partial ambiguity fixing method to obtain the integer ambiguity of the narrow-lane phase decimal deviation product; and calculating a user coordinate fixed solution in combination with related parameters.

The present subject relates to a method for proving a statement describing a functionality of an electronic circuit, using a quantum computer and a proof assistant.The procedure comprises: encoding a current proof state into a vector of real numbers of a fixed length, where the current proof state defines a task to prove at least part of the statement; encoding the vector into a quantum state of a quantum system of the quantum computer; using the quantum state as an input quantum state by a quantum machine learning model to provide an output quantum state, the measurement of which constitutes a proof step for the defined task; measuring the output quantum state, thereby obtaining the proof step for the defined task; providing the proof step to the proof assistant; and receiving a next proof state from the proof assistant in response to the provision of the proof step.

The invention discloses a parameter serial and parallel mixed input complex multiplication implementation method, which is implemented by adopting a complex multiplier circuit, and the complex multiplier circuit comprises a serial input cache unit, a parallel input cache unit, a real number multiplication unit and a real number addition / subtraction unit. The method comprises the specific implementation steps that S1, serial input complex number parameters and parallel input complex number parameters are sequentially input from a serial input cache unit and a parallel input cache unit respectively; s2, the serial input complex parameters and the parallel input complex parameters are subjected to combined calculation through a real number multiplication unit and a real number addition / subtraction unit; and S3, outputting a real part and an imaginary part of a complex multiplication result in sequence in a serial mode. Compared with a traditional and optimized triple multiplier version complex multiplication operation circuit, only a small number of registers are additionally arranged, latch resources are conditionally selected, and the complex multiplication operation circuit has obvious advantages in hardware resource consumption.

The invention relates to the technical field of transformers, in particular to a transformer parameterization design method, device and equipment, and the method comprises the following steps: solidifying a transformer design standard and specification in an Excel worksheet, and defining a control parameter through a set compiling grammar; the control parameters comprise a real number type, an integer type, a character string type and a Boolean type; one writing grammar is set for each parameter type; exporting control parameters in the Excel worksheet as an XML (Extensible Markup Language) file; creating a notebook file in automatic design software, and importing the control parameters in the XML file; based on the imported control parameters, parametric modeling is carried out in automatic design software, and a three-dimensional model of the transformer is generated; and automatically generating a two-dimensional engineering drawing of the transformer according to the three-dimensional model. Standardization of links such as design, manufacturing, installation and operation of the transformer is effectively ensured, and therefore performance and reliability of the transformer are greatly improved.

The invention discloses a space target monitoring constellation configuration optimization method and system considering complex constraints, and belongs to the technical field of aerospace mission design and optimization. The method comprises the following steps: firstly, constructing a discrete orbit modal library meeting regression orbit dynamic resonance conditions; constructing generalized hybrid design variables consisting of integer indexes and real number fine tuning quantities on the basis of the library; establishing an optimization model taking the space volume coverage rate, the maximum revisit time and the system construction cost as targets and taking illumination, dynamics and maneuvering capability as constraints; performing rapid analysis and coarse screening on invalid links through track geometry; and finally, performing global optimization by using an improved non-dominated sorting genetic algorithm to obtain a Pareto optimal constellation configuration set. According to the method, accurate evaluation of the three-dimensional space target coverage efficiency is realized, the physical feasibility and long-term stability of a configuration scheme are ensured, and a high-dimensional multi-target optimization problem is efficiently solved.

The invention provides a multi-zone-area ordered charging scheduling method and system based on a simulated annealing genetic algorithm, and the method comprises the steps: generating an initial population through employing a real number coding mode, and enabling a population individual to represent a charging scheduling scheme; constructing a fitness function in the genetic algorithm by taking load balancing and network loss minimization as optimization targets; selecting individuals by adopting a roulette selection and elitism strategy, and reserving a plurality of individuals with the highest fitness to enter the next generation by adopting a self-adaptive crossover mutation operation; taking the optimal individual of the current population as an initial solution, and executing simulated annealing operation; after optimization of a preset number of iterations, an optimal charging scheduling scheme is output, and the load rate, the voltage and the charging pile state of each transformer area are monitored in real time; and when abnormality is detected, charging power distribution is dynamically adjusted, and the load of the overload area is transferred to the low-load area. Through fusion of simulated annealing and a genetic algorithm, multi-zone-area charging scheduling is optimized, load balancing and network loss minimization are realized, and the stability and dynamic adaptability of a power grid are improved.

The invention relates to the field of vehicle route planning, in particular to a dynamic multi-target vehicle route planning method and system based on prediction and recombination, and the method comprises the steps: building a mathematical model of dynamic multi-target vehicle route planning, initializing a population through real number coding, adjusting the population to meet a constraint, carrying out the iteration through a genetic algorithm, and obtaining a candidate solution set; a Pareto front set is obtained and clustered, and a clustering center is recorded as a special individual; and when environment change is detected, predicting individuals in a new environment by using a gray model or a least square support vector machine, and constructing a new population until an optimal solution set is output. According to the method, the convergence speed of the algorithm is high, the response to the environment change is more sensitive and timely, the dynamic multi-target vehicle routing problem is effectively solved, and the application effect and the economic benefit of the vehicle routing in the actual life are effectively promoted.

The invention provides a numerical control multi-target energy-saving optimization method and system and a storage medium, and the method comprises the steps: constructing a mixed integer linear programming model for multi-target flexible job shop scheduling, taking machine tool distribution, a machining sequence, tool distribution and a machining speed as decision variables, and taking total weighted tardiness and total energy consumption as optimization targets; a single-layer real number coding method is adopted, machine tool allocation, the machining sequence and the machining speed are coded in a one-dimensional real number sequence in a unified mode, an initial population is generated, the mixed integer linear programming model is solved through a multi-target optimization algorithm, and an algorithm optimal solution of the mixed integer linear programming model is obtained; decoding the optimal solution of the algorithm, distributing tools for each process, and generating a production plan table; and calculating the total weighted tardiness and the total energy consumption to obtain an algorithm energy-saving optimization scheduling scheme. According to the method, the dual-objective mixed integer linear programming model is constructed, and the innovative coding and decoding strategy and the dynamic optimization mechanism are combined, so that collaborative optimization of the production efficiency and the energy consumption is realized.

The invention provides a multi-component spectral feature selection method based on double-layer optimization, and aims to solve the problem of model performance reduction caused by high dimension, redundancy and noise interference in hyperspectral data. The method comprises the following steps: performing binary and real value vector double-layer coding on individuals, and randomly generating an initial population based on a fitness value; and then, calculating an importance score delta of each spectral variable in evolutionary iteration in combination with a filtering type Relief feature selection method so as to dynamically guide population optimization. A Gaussian function dynamic noise reduction method based on importance scores is designed in the optimization process, and interference noise existing in spectral variables is optimized and fitted through real number vectors; and finally, obtaining an optimal spectral feature subset through an environment selection strategy. According to the method, the data dimension can be effectively reduced, noisy and redundant spectral variables are eliminated, and the accuracy of the model is remarkably improved.

The invention discloses a probabilistic language three-way decision-making-based telecommunication potential customer evaluation method. The method comprises the steps of firstly grouping target information according to decision requirements, converting a real number data set into a probability language decision matrix, extracting probability language term set features and constructing an expectation-reliability score function; respectively obtaining subjective and objective weights of attributes through an analytic hierarchy process and a variable coefficient method, and solving a comprehensive weight by means of a cosine similarity maximization model; then, a relative loss function is constructed based on the score matrix, a comprehensive foreground value of the scheme is calculated, and (non) harmony indexes and net credibility indexes of the scheme are measured and calculated under each attribute in combination with attribute non-compensability and an ELCTRE thought; and finally, making a series of decision rules through the expectation relative loss function. According to the method, the telecommunication company can be assisted to efficiently classify and evaluate the users, scientific guidance is provided for decision making, and the accuracy of potential customer mining and management is improved.

Artificial-intelligence computer-implemented processes and machines predict whether personal data may be present in structured software based on metadata field(s) contained therein. Natural language processing preprocesses input strings corresponding to the metadata field(s) into normalized input sequence(s). Individual characters in the sequence(s) are embedded into fixed-dimension vectors of real numbers. Bidirectional LSTM(s) or other machine-learning algorithm(s) are utilized to generate forward and backward contextualization(s). Neural network output(s) are provided based on element-wise averaging or feed forwarding based on the contextualization(s) in order to predict whether one or more value fields corresponding to the metadata field(s) may contain personal data.

The invention discloses a field programmable gate array (FPGA) implementation method for Hermite matrix eigenvalue decomposition, which comprises the following steps of: performing real number processing on a Hermite matrix according to a corresponding relationship between the Hermite matrix and eigenvalues and eigenvectors; grouping the dimension real matrix obtained by the real number processing; calculating rotation matrixes of diagonal units and non-diagonal units; performing Jacobi rotation operation on the diagonal units and the non-diagonal units, and updating the feature vector matrix according to a rotation matrix; after a group of Jacobi rotation is completed, data exchange is carried out according to grouping of a parallel Jacobi algorithm; and multi-stage cleaning can be carried out according to actual requirements. According to the method, a parallel Jacobi algorithm is selected, a series of matrix rotation is adopted, the matrix is converted into a diagonal matrix, and therefore the eigenvalue and the eigenvector of the matrix are calculated. According to the method, the parallel computing advantages of the FPGA and the Jacobi algorithm are fully utilized, and the real-time performance of the algorithm is effectively improved.

A secret share value [y]=[δx2+ax] is obtained through secure computation using a secret share value [x] of a real number x, and a secret share value [func(x)]=[y(ζy+b)+cx] of an elementary function approximation value z=func(x) of the real number x is obtained and output through secure computation using secret share values [x] and [y]. Here, x, y, and z are real numbers, a, b, c, δ, and ζ are real number coefficients, and a secret share value of · is [·].

Disclosed is an operation method for executing an addition operation on quantized matrices. This operation method comprises the steps in which: an NPU matrix multiplication unit executes a matrix multiplication operation on a first matrix and a second matrix, wherein the first matrix has a size of R0*2C0 and is obtained by concatenating a first input tensor and a second input tensor, each of which is composed of quantized values and has a size of R0*C0, and the second matrix is obtained by concatenating a first diagonal matrix having a size of C0*C0 and having all main diagonal element values equal to integer N1 and a second diagonal matrix having a size of C0*C0 and having all main diagonal element values equal to integer N2; and an NPU vector processing unit calculates elements of a non-quantized tensor obtainable by adding the second input tensor to the first input tensor, by adding real number B to a product of real number R and a third matrix calculated by the matrix multiplication operation.

A method for detecting the cliques of evaluators in a decision-making process includes collecting a data matrix Sij to a computer system using an automatic input interface. The elements of the matrix Sij are the real numbers in a predefined range. Each of the elements of the matrix Sij represent a numerical evaluation provided by an evaluator j for an evaluated entity i. For each pair of evaluators j, where j1 and j2 (j1≠j2) from the data matrix Sij, calculating by the computer system the Pairwise Adjusted Distances EDj<sub2>1< / sub2>j<sub2>2< / sub2>. Applying by the computer system a nonlinear transformation to the Pairwise Adjusted Distances EDj<sub2>1< / sub2>j<sub2>2< / sub2>. Identifying cliques of evaluators by comparing by the computer system the transformed distancesEDj1⁢j2*to a robust lower threshold.

The embodiment of the invention provides a modulation method, a storage medium, an electronic device and a computer program product, and the method comprises the steps: shifting a first data sequence, and carrying out the addition operation of the first data sequence and the shifted first data sequence, and obtaining a second data sequence; multiplying each data element of the second data sequence by a negative real number, and sequentially inserting between every two adjacent data elements of the first data sequence to obtain a third data sequence; and transmitting the third data sequence. Through the embodiment of the invention, the problem that the low PAPR requirement of the communication system in the related technology cannot be met is solved, and the effect of reducing the PAPR of the communication system is achieved.

A structure model includes a first encoder that converts a compound structure representation to a real number vector and a first decoder that estimates the compound structure representation from the real number vector resulting from the conversion by the first encoder. A structure-property relationship model includes a second encoder that converts, to a real number vector, an extended vector including, as components, the real number vector generated by the first encoder and a target value vector including target values of one or more physical property values and a second decoder that estimates the extended vector from the real number vector generated by the second encoder.

The invention provides a metadata structure, a data processing method and a storage medium. The metadata structure is a structured data object on a computer readable medium, can be read and written by a computer program, and adopts a framework of three parts: a basic index part, which is used for uniquely identifying educational resources and supporting retrieval, and at least comprises a unique identification field and a resource classification / retrieval attribute field; the core attainment vector part is used for quantitatively representing an educational resource childbearing target for intelligent calculation and comprises an N-dimensional attainment vector, the dimension key is c01 to cN, and the value of each dimension is a real number in a preset numerical value interval; and the association application part is used for constructing an inter-resource relationship and learning evidence agreement which at least comprises a field for describing a resource dependency relationship and a rule field which is executable by a computer and is used for extracting evidence from learning interaction data. According to the scheme, structuralization and computability of the attestation information are realized.

This invention discloses a flexible scheduling method, system, and application for UPMS (Upright Manufacturing System) workshops based on an improved differential evolution algorithm. The method includes: establishing an independent parallel machine scheduling model with sequentially dependent mold-changing time as the objective of minimizing the maximum completion time; using real-valued vector encoding and decoding it into a scheduling scheme through the maximum position value rule; performing mutation and crossover operations of the differential evolution algorithm on the generated test vectors, with optimizations including load balancing optimization based on destruction and reconstruction and mold-changing optimization based on sequential smoothing; finally, updating the population and outputting the optimal scheduling scheme. This invention significantly reduces sequentially dependent mold-changing time, achieves dual optimization of load balancing and mold-changing cost, and improves solution accuracy and efficiency, making it particularly suitable for discrete manufacturing workshops such as textile printing and dyeing, and injection molding.

The application discloses a kind of workshop cutter scheduling rule generation methods based on genetic algorithm, belong to data processing technical field, comprising: constructing scheduling model;According to machine priority heuristic rule, obtain each machine priority;According to the heuristic rule of initial tooling tool number and the heuristic rule of tool change tool number, each machine is allocated tool;The tool allocation combination of each machine processing task set is output;Machine number, initial tooling tool number and tool change tool number are respectively carried out real number coding;Using machine priority heuristic rule, initial tooling tool number heuristic rule and tool change tool number heuristic rule form initial population;Initial population is evolved, and the optimal population individual for the weighted sum of minimizing maximum completion time and minimizing tool change frequency is obtained.The workshop cutter scheduling rule generation method based on genetic algorithm solves the problem that existing optimization tool configuration mode scheduling optimization is not high.

A data compression device determines, based on a significant figure of each of a plurality of real numbers, a step size that is a value capable of dividing without remainder each of the plurality of real numbers. The data compression device acquires integers by dividing each of the plurality of real numbers by the step size.

The present invention discloses a method for detecting anomalies in automobile resistance welding based on multi-channel feature integration. The method collects process data of automobile resistance welding that meets welding quality standards and organizes it into a real number matrix; performs multi-channel feature expansion on the real number matrix based on mean value, standard deviation, skewness, kurtosis and negative entropy; performs standardization processing on the extended feature vectors by calculating the mean value and standard deviation of each row vector in an extended feature matrix formed by merging all extended feature vectors; performs singular value decomposition on the standardized extended feature matrix, and then obtains a feature integration matrix and an upper limit of a normal variation range of automobile resistance welding; for the latest process data of automobile resistance welding, similarly obtains the standardized extended feature vector, combines the feature integration matrix to obtain a score vector, and then obtains an anomaly detection index, and determines whether welding quality anomalies occur by comparing with the upper limit; the advantage is that the entire process does not involve complex calculations and the required computing load is very small.

The invention provides a modulation method, a communication node and a storage medium. The modulation method comprises the following steps: modulating a first data sequence to obtain a second data sequence; and for every two adjacent elements of the second data sequence, respectively obtaining a real number item of one element and an imaginary number item of the other element, carrying out addition and phase rotation operation on the real number item and the imaginary number item, and inserting data obtained by the addition and phase rotation operation between the two adjacent elements, and obtaining a third data sequence.

This invention provides a hybrid coding and genetic operation method and system for optimizing the layout of pipe supports and hangers. The method includes: S1, determining the pipe segments to be optimized and combining the optimized pipe segments to form an optimization range; S2, selecting an appropriate optimization mode according to engineering requirements and design stage; S3, performing coding operations for each optimized pipe segment, and the combination of codes for all pipe segments forms a complete chromosome coding structure for the optimization range; S4, generating an initial parent population based on the chromosome coding structure, and performing genetic operations through crossover and mutation to generate offspring individuals; S5, decoding the offspring individuals, performing simulation analysis, screening and constructing a new generation population; S6, repeating the evolutionary process until a preset termination condition is met. This invention uses real number coding combined with integer coding, and introduces natural number index coding to establish a mapping relationship with the coding, and designs matching chromosome crossover and mutation operation rules to achieve efficient genetic operations on the coded chromosomes.

This invention provides a script generation method, apparatus, electronic device, and readable storage medium. The method includes: acquiring at least one initial script idea element described in natural language; inputting the initial script idea element into a pre-trained semantic encoding model, converting the initial script idea element into a first idea vector in a d-dimensional real vector space, where d is a positive integer; wherein all real vectors output by the semantic encoding model together constitute a script idea latent space for representing the semantic distribution relationship of the initial script idea element; performing spatial operations on at least one first idea vector within the script idea latent space to obtain a second idea vector, the second idea vector being used to represent a script concept; inputting the second idea vector into a cross-modal projector, converting the second idea vector into a conditional vector matching the word embedding dimension of a pre-trained large language model; inputting the conditional vector as a generation condition into the large language model, outputting script idea text corresponding to the script concept, the script idea text including at least one of the following: story synopsis, character biographies, and key scene description information.

According to the method, a target function of three-direction equivalent zero offset and real number deflection matrixes of the strapdown three-axis magnetometer is constructed, an overdetermined equation set related to the Euler angle of the strapdown three-axis magnetometer is constructed, the solving problem of the target function and the overdetermined equation set is converted into a constraint optimization problem, a sequential quadratic programming algorithm is adopted for solving, a telescopic factor is introduced, and the Euler angle of the strapdown three-axis magnetometer is obtained. And calculating a correction value of the magnetic gradient tensor measured by the strapdown three-axis cross magnetic array, and completing self-calibration of the strapdown three-axis cross magnetic array under the condition that the reference magnetic field is unknown. According to the method, all parameters of the strapdown three-axis cross magnetic array measurement model can be automatically and accurately calibrated under the condition that a reference magnetic field vector model is not provided, a calibration link of alignment errors does not exist, and a high-precision three-axis magnetometer or a scalar magnetometer does not need to be used for measuring the reference magnetic field vector model in the calibration process. The method does not have an iterative process and mathematical approximation, so that an iterative calculation initial value does not need to be provided, and the calibration algorithm is rapid and high in precision.

An example system includes a processor that can receive a number of complex packed tensors, wherein each of the complex packed tensors include real numbers encoded as imaginary parts of complex numbers. The processor can execute a single instruction, multiple data (SIMD) operation on the complex packed tensors using an integrated circuit of real and complex packed tensors in a complex domain to generate a result.

The application discloses a mechanical arm fuzzy PID control method based on quantum pigeon group optimization, first motion trajectory planning is carried out, and a mechanical arm is controlled to move according to the planned motion trajectory through a fuzzy PID controller; a QAPIO algorithm is used to optimize fuzzy PID control parameters, and each pigeon can be used as a PID control parameter of each joint of the mechanical arm. The QAPIO algorithm of the application modifies a compass operator update equation, a probability density function in quantum representation of real number coding and a quantum rotation gate in the original algorithm, so that the algorithm has a continuous updating capability, can continuously update an optimal value, improves global optimization capability, avoids premature local optimization, and solves the problem that the original algorithm is prone to falling into a [0, 0,..., 0, 0]T point, causing the optimization algorithm to fail. The application effectively realizes optimization of fuzzy PID controller parameters of the mechanical arm, and has good practicability.