28 results about "Numerical range" patented technology

The embodiment of the invention provides a model reinforcement learning method, device and equipment. The scheme comprises the following steps: in a sampling stage, using an inference engine and adopting a to-be-trained target model to generate an output sequence for an input sequence under a first strategy parameter, recording a first probability value of each lexical element in the output sequence, and calculating a dominant value of each lexical element, in a training stage, after a training engine is used for forward propagation to obtain a second probability value of each lexical element generated by a target model under a first strategy parameter, a first ratio of the second probability value to the first probability value of each lexical element can be calculated, and then the lexical elements with the first ratios within a preset numerical range are screened out to participate in calculation of a target function; and optimizing the target function to update the parameters of the target model.

The invention relates to a self-adaptive micro-liquid adding time intelligent optimization method, and belongs to the technical field of industrial process control. The method comprises the following steps: dynamically switching a rotating speed control mode according to a numerical range of an added target quantity, and calculating and outputting a target rotating speed instruction; pipeline pressure is monitored in real time, the pressure state is judged according to a graded pressure threshold system, a graded regulation and control strategy is executed, and a rotating speed fine adjustment instruction is generated; a time adjustment model is constructed based on the residual addition amount and the estimated actual flow, the addition time is dynamically estimated, and replanning of the target time and the rotating speed is triggered when the parameters are abnormal; and after adding is completed every time, operation data are automatically collected, mismatching items of the control parameters and the working conditions are analyzed and recognized through deviation traceability, and the rotating speed control parameters and the pressure regulation and control parameters are updated in a self-adaptive mode. According to the invention, intelligent optimization of the adding process is realized, and the adding precision and the system adaptability are effectively improved.

According to the method for training the target model based on reinforcement learning, the target model is used for executing tampering detection on an input image, and the method comprises the steps that a training sample is obtained, the training sample comprises a target image and boundary information of a plurality of truth value boxes, and the truth value boxes are borders of a part of images marked in the target image and comprising tampering content; and inputting the target image into the target model, and outputting boundary information of the plurality of prediction frames. And calculating the overall overlap ratio of the plurality of prediction frames and the plurality of true value frames. Determining a first reward score based on a preset piecewise function according to a numerical range of the overall overlap ratio; the function corresponding to each numerical range of the piecewise function is a constant function, and the value of the corresponding constant function is increased along with the improvement of the overall overlap ratio. And based on a reinforcement learning algorithm, according to the first reward score, updating the target model.

This invention provides a parameter prediction model prediction method, device, and medium based on gradient decision trees, belonging to the field of integrated circuit computer-aided design technology. The method includes: acquiring the topological features of the target network; wherein, the topological features include: fan-out number, number of resistor segments, and number of branches; inputting the topological features into a pre-trained prediction model to obtain the predicted value of total parasitic capacitance and the intermediate predicted value of total parasitic resistance; performing an inverse exponential transformation on the intermediate predicted value of total parasitic resistance to obtain the predicted value of total parasitic resistance. This invention, by performing a logarithmic transformation preprocessing on the target variable of total parasitic resistance and performing an inverse exponential transformation after prediction, can effectively compress the numerical range of total parasitic resistance and optimize the data distribution, thereby accurately restoring the true physical resistance value.

When an arithmetic control unit according to the present invention is to extract high-bit data larger than a bit width for output based on a decimal point position, from a cumulative memory of a fixed bit width in which a decimal point position and a division position are set, the cumulative memory storing a cumulative addition result of a multiply-accumulate operation result between input data and a kernel, in an arithmetic circuit that divides data into higher-order data and lower-order data on the basis of the division position and extracts and outputs the higher-order data and the lower-order data, the number of times that each of the higher-order data and the lower-order data exceed an upper limit and fall below a lower limit of a given numerical range is acquired from a counter, and on the basis of the acquired lower limit count for the lower-order side, and the upper limit count for the lower-order side or the upper limit count for the upper-order side, a decimal point position for calculating the next input data is determined and set in the arithmetic circuit, and on the basis of the lower limit count for the higher-order side, a data distribution of the higher-order data and the lower-order data, and a data distribution of the kernel, the division position for calculating the next input data is determined and set in the arithmetic circuit.

The present invention addresses the problem of calculating the root of a power function. An arithmetic device according to the present invention calculates a root Y of a power function (Y = AX, wherein A is a constant, and X is a prescribed numerical range). The arithmetic device comprises: an input unit into which input data indicating an exponent X is input; a first arithmetic circuit that executes a first arithmetic process on the basis of a linear approximation equation of a graph of a power function in a first numerical region of a numerical range of the exponent X; a second arithmetic circuit that executes a second arithmetic process on the basis of a linear approximation equation of a graph of a power function in a second numerical region of the numerical range, the second numerical region differing from the first numerical region; and a selector that outputs output data indicating the root Y calculated by the first arithmetic circuit when if exponent X indicated by the input data inputted into the input unit belongs to the first numerical region, and outputs output data indicating the root Y calculated by the second arithmetic circuit if the exponent X indicated by the input data inputted into the input unit belongs to the second numerical region.

This invention provides a quantization method for the EltwiseAdd operator in neural networks. The method quantizes the EltwiseAdd operator to obtain the EltwiseAddQuant operator, which can directly perform element-wise addition calculations using fixed-point input activation and directly output fixed-point results. The entire calculation process only involves fixed-point addition, avoiding floating-point multiplication and rounding operations. The method includes: S1. Recording the operator activation range; S2. Updating the numerical range of the EltwiseAdd operator activation and updating the EltwiseAdd quantization calculation method; S3. Performing the overall quantization. The advantages of quantizing the EltwiseAdd operator proposed in this invention include reduced computational resource consumption, faster computation speed, lower power consumption, enhanced compatibility, and improved memory efficiency. These advantages make quantization an effective means of model compression and acceleration, especially suitable for resource-constrained environments and applications requiring rapid response.

This disclosure relates to a codeword determination method, apparatus, and storage medium, including: generating a codeword based on a first precoding vector and a second precoding vector, wherein the first precoding vector and the second precoding vector are orthogonal, the codeword is used to precode data, and the difference between a first parameter of the first precoding vector and a second parameter of the second precoding vector is within a first numerical range. In the above embodiments, codewords are determined by the difference between the parameters of two orthogonally related precoding vectors, ensuring that the precoding vectors included in the generated codeword are orthogonal, providing a method for selecting precoding vectors with multiple orthogonal options, thereby ensuring the accuracy of the determined codeword, the accuracy of data precoding based on the codeword, and the reliability of communication.

This invention provides a computer program that can reduce the burden of creating lookup tables for determining the flux linkage of electromagnetic devices having windings. [Solution] A computer program that causes a computer to perform a process to create a lookup table for simulating the operation of an electromagnetic device having multiple windings, based on an analysis model of the electromagnetic device, wherein the program transforms the component axes of multiple currents flowing through each winding so as to broaden the numerical range in which the change in flux linkage for the currents flowing through each winding is gradual and narrow the numerical range in which the change in flux linkage is steep, performs a magnetic field analysis based on the analysis model for the multiple currents whose component axes have been transformed, and causes the computer to perform a process to associate the flux linkage calculated by the magnetic field analysis with the currents.

This application relates to a method, apparatus, and computer program product for determining cost data based on machine learning. The method includes: acquiring part data of a target part; constructing a feature vector corresponding to the target part using the part data; determining the similarity between the target part and historical parts by using the distance between the feature vector of the target part and the feature vectors of pre-stored historical parts; constructing learning data using the feature vectors of historical parts and historical cost data, and training a machine learning model using the learning data; and, when the similarity meets a preset numerical range, using the machine learning model to predict the cost using the feature vector of the target part, thereby obtaining the target cost data of the target part. This method can utilize historical parts that are moderately similar to the target part to construct learning data to train the machine learning model, ensuring the reliability of the model's prediction results and thus improving the accuracy of the target cost data.

The invention discloses a multi-scene diffusion calculation method for a chemical pollution source. The method comprises the following steps: (1) parameter input and verification: inputting pollution source parameters, meteorological parameters, calculation region parameters and pollutant types; performing numerical range, data type and logic consistency verification on the input parameters, filling default values when non-key parameters are missing, and prompting correction when the parameters are abnormal; (2) coordinate conversion and caching; (3) calculating diffusion parameters; (4) single-source concentration calculation; (5) multi-source concentration superposition; and (6) result output: outputting a calculation result in the forms of a data table, a scatter diagram and a JSON file. According to the method, multi-scene unified calculation can be provided, an instantaneous point source, a continuous point source, an instantaneous multi-point source and a moving line source are supported, dynamic weather, terrain and pollutant characteristic correction are introduced to improve precision, calculation logic is optimized, and emergency efficiency is ensured.

This invention provides a method for testing the vibration response of wind tunnel equipment, belonging to the field of wind tunnel technology. The invention involves installing multiple triaxial accelerometers at the main structural nodes of the wind tunnel equipment and establishing a vibration response game-theoretic optimization model. A vibration signal enhancement model is used to process the original vibration signal, constructing a micro-amplitude vibration feature matrix, a signal superposition weight matrix, and a spurious vibration index matrix for signal analysis. A comprehensive vibration evaluation index is calculated using a vibration response evaluation function, and corresponding optimization strategies are adopted to adjust the input size parameters according to different numerical ranges, achieving adaptive signal processing and temperature compensation. Finally, a test report is output, containing vibration response data, spurious signal identification results, and structural safety assessment conclusions. This invention solves the technical problem in existing technologies where it is impossible to accurately distinguish between the actual structural vibration of wind tunnel equipment and spurious vibration signals caused by temperature changes.

A betting amount proportion display system for roulette calculates and obtains a substantial betting point of game results respectively through a game processing unit, and performs a numerical range classification on numerical values of the points of the game results, so that the points are arranged from small to large numerical values and classified to belong to range groups Pi, i=one of 1, 2, . . . , N, N is greater than or equal to 3. The roulette image displays the game results arranged in a ring, and the roulette image displays bars at positions adjacent to the game results, the bars correspondingly show the points of the adjacent game results, so that betting amounts of the points are displayed proportionally, a length of each bar correspondingly shows the range group Pi, i=1, 2, . . . , N the points are classified to belong to.

The invention discloses a high-precision softmax hardware implementation method, and belongs to the field of neural network hardware acceleration. According to the method, hardware storage and computing resource consumption are reduced by increasing memory access times and two lookup tables; non-spilling the exponent result by subtracting the maximum of the calculated vector elements; by utilizing the format characteristics of floating-point numbers, the index and mantissa parts are processed separately, the numerical range of an input lookup table is reduced, and a high-precision softmax hardware implementation result with an absolute error controlled within 3e-5 can be achieved by using a small number of lookup table storage resources; the processing efficiency is improved by avoiding data conflicts through pipeline parallelism.

The invention relates to a fast phase unwrapping method combining DeBruijn and a half-cycle Gray code. The fast phase unwrapping method comprises the following steps: step 1, generating four phase shift patterns, and a sum; step 2, generating a DeBruijn pattern with a period of T and a DeBruijn pattern with a period of T / 2, and generating a Gray code pattern with a period of T / 2 at the same time; step 3, determining a projection pattern as,..., and projecting the projection pattern to a plane; step 4, calculating a normal fourth-step phase shift; step 5, obtaining a wrapped phase; step 6, searching a corresponding position in the original code element list to respectively obtain a phase order sum; and step 7, defining boundary conditions of phase intervals, introducing a tiny correction value, and selecting and calculating absolute phases of all the intervals through a formula according to a numerical range wrapping the phases. The method has the beneficial effects that the problem of edge jump is solved, and the unwrapping time is shortened.

The invention discloses an underground data center energy efficiency grade determination method based on multi-index evaluation. The invention provides a comprehensive evaluation method integrating multiple energy efficiency evaluation indexes for solving the problem of multi-dimensional index difference of an underground data center in energy efficiency evaluation. Firstly, a system comprising five key energy efficiency evaluation indexes including PUE, pPUE, PLF, CLF and WUE is constructed, and a standard range and a good and bad threshold value of each index are determined. In view of the difference between the dimension and the numerical range of each index, the numerical value of each index is converted into a unified score by adopting a mathematical conversion method. The conversion method comprises but is not limited to a linear interpolation method, and a weight is set for each index to ensure the scientificity of an evaluation result. Finally, according to the converted score and weight, the energy efficiency level of the underground data center is obtained through comprehensive calculation, the limitation of traditional single index evaluation is solved, and the overall energy efficiency performance of the underground data center is scientifically reflected.

The invention relates to the technical field of forging data processing, in particular to a forging process parameter automatic writing method and system.The method comprises the steps that in response to target process parameters generated by a client side, local process parameters stored by execution equipment at the current moment are obtained; judging whether the parameter items of the same category between the target process parameters and the local process parameters are the same or not; in response to different parameter items of at least one category between the target process parameters and the local process parameters, judging whether each parameter item of the target process parameters is within a preset numerical range or not; and in response to the condition that each parameter item of the target process parameter is within a preset numerical range, updating a local process parameter stored by the execution equipment at the current moment according to the target process parameter. According to the method, the problem that whether the written process parameters are reasonable or not is misjudged possibly due to huge difference of different parameter dimensions is solved.

The application discloses a kind of based on numerical range multi-converter system stability evaluation method.Method includes: whether the open loop stability condition is satisfied by the equivalent admittance matrix of the admittance matrix transfer function of the converter side of multi-converter system;The numerical range of the equivalent admittance matrix of the admittance matrix transfer function of the network side and the converter side of multi-converter system is established;When meeting the open loop stability condition, then whether the closed loop stability condition is satisfied by the numerical range of multi-converter system, if meeting, then evaluate multi-converter system stability.The application is based on numerical range analysis framework, without global modeling, can realize the fast evaluation of small signal stability of multi-converter system.The application shows stronger criterion applicability and engineering reliability in large-scale, high proportion converter access power system, provides more effective technical means and theoretical basis for the design, planning, operation and control of multi-converter power system.

The invention provides a parameter adjustment method, a parameter adjustment system and a computer readable storage medium, the parameter adjustment method is applied to a terminal device, the terminal device is in communication connection with a cloud server, and the method comprises the following steps: when the terminal device is started, loading a locally stored first parameter set; initiating a parameter request to a cloud server to obtain a second parameter set, and updating a locally stored first parameter set according to the parameter set; a pre-stored default parameter set is searched in the terminal equipment, and when the pre-stored default parameter set is searched, the multiple parameter values in the default parameter set are verified based on the numerical value range of the multiple parameters in the second parameter set, and verification results of the multiple parameters are obtained; and the parameter values of the corresponding parameters in the default parameter set are adjusted based on the verification results of the parameters to obtain the adjusted default parameter set, so that the target operation parameter set is formed, the parameter adjustment process is simplified, and the updating period is shortened.

The invention provides a data processing method and device, equipment, a storage medium and a program product, which can be applied to the technical field of financial science and technology. The method comprises the steps that in response to a data processing request, screening is conducted in a preset configuration model library based on a received data conversion identifier, a configuration model set is obtained, the data conversion identifier indicates application features of received first data, and the configuration model set comprises a plurality of configuration models; different configuration models correspond to different measurement unit conversion rules; traversing the configuration model set based on the numerical range of the first data until a configuration model corresponding to the first data is obtained; the configuration model corresponding to the first data is called to process the first data based on the measurement unit conversion rule to obtain second data, and the measurement unit of the second data is different from that of the first data.

The embodiment of the invention provides an implementation method of a reciprocal square root hardware accelerator, which belongs to the technical field of calculation and specifically comprises the following steps of: judging a numerical range to which an input integer belongs based on a first threshold value and a second threshold value; if the input integer is greater than a first threshold value, the large number processing path directly outputs a corresponding pre-stored constant result by querying a large number constant ROM; if the input integer is smaller than or equal to a second threshold value, the decimal processing path directly outputs an accurate square root reciprocal result by querying a decimal accurate reciprocal ROM; if the input integer is between the second threshold value and the first threshold value, the intermediate value processing path starts a core calculation process, and the reciprocal root bisection is calculated through a bit-by-bit recovery extraction unit, a compression type multi-lookup table structure and a nonlinear error correction unit; and integrating and outputting a reciprocal square root result obtained by the large number processing path, the decimal processing path and the core calculation process. Through the scheme disclosed by the invention, the calculation efficiency and accuracy are improved.

The invention discloses an automatic index verification and anomaly detection method based on an object model and a server, and relates to the technical field of computer internet, and the method comprises the steps: extracting key features reflecting data features and trends from source data; based on a preset object model, performing index relation analysis on the extracted key features reflecting the data features and trends; the numerical range of the data is verified by adopting an automatic script and applying a boundary value analysis and equivalence class division method; judging based on a verification result; when abnormity exists, abnormal index marking is carried out, and abnormal early warning information is generated; if not, analyzing and predicting whether potential abnormity exists or not through a pattern recognition algorithm; generating a potential abnormity early warning report when potential abnormity exists through analysis and prediction; and outputting a normal data result when no potential abnormity exists in analysis and prediction. The verification efficiency of various indexes can be improved, and the labor cost is reduced; and the accuracy and reliability of data decision and analysis can be improved.

The invention relates to the technical field of intelligent monitoring, in particular to an intelligent grouting defect identification method and system for earth and rockfill dam engineering. The method comprises the specific implementation steps that firstly, multi-modal data of the earth and rockfill dam are collected, then the multi-modal data are synchronized and aligned, and a structured multi-modal data set is formed; thirdly, layering and parallel processing are carried out on the data set through a grouting defect feature quantification model, grouting anomaly feature vectors of multi-modal data are fused in a feature fusion layer, space mutual verification is carried out, and a grouting defect quantification vector representing anomaly is obtained through quantification in a specific numerical range; and finally, on the basis of a defect physical field inversion model, taking the grouting defect quantization vector as input, solving the physical attribute of a defect area through iteration by utilizing a physical information neural network and physical law constraints, and calculating a deviation value between the physical attribute of the defect area and the physical attribute of a normal grouting body. And identifying the type of the defect by utilizing a multi-physics coupling diagnosis method according to the deviation value.

The invention provides a method for extracting a transfer function according to a three-dimensional model of a hydraulic element. The method comprises the following steps: step 1, acquiring a numerical range of concerned parameters under a normal working condition; step 2; switching a simulation solution type of the flow field analysis software into a transient state, and adding a step model for a monitored input parameter; step 3, acquiring a Pout value corresponding to the Pin with the step signal; step 4, carrying out data identification on the Pin and Pout value time domain data with the step signal; and 5, obtaining a final identification result, and further obtaining a transfer function.

This invention proposes a dynamic light scattering particle size inversion method and system based on FPGA. The method involves calculating the autocorrelation of scattered light signals within a periodic range to obtain multiple sets of non-consistent autocorrelation functions. The cumulative mean of these autocorrelation functions is then calculated. The functions are subsequently normalized to obtain a normalized autocorrelation function. Data from the decay segment of the function is extracted from the normalized autocorrelation function, and a quadratic polynomial is fitted to the data to calculate a quadratic matrix constructed with the correlation time. The corresponding diffusion coefficient is obtained by solving the matrix. Finally, the corresponding scattering particle size is obtained through inversion using Einstein-Stokes formulas. By normalizing and logarithmic processing, the numerical range is reduced, enabling the FPGA chip to meet the computational range of dynamic light scattering particle size measurement, thus eliminating the FPGA's dependence on a host computer and improving the efficiency of dynamic light scattering particle size measurement.

The present disclosure relates to codeword determination methods and apparatuses, and a storage medium. A method comprises: generating a codeword on the basis of a first precoding vector and a second precoding vector, the first precoding vector and the second precoding vector having an orthogonal relationship, the codeword being used for precoding data, and the difference value between a first parameter of the first precoding vector and a second parameter of the second precoding vector being within a first numerical range. The described embodiment determines codewords by means of using a difference value relationship between parameters of two precoding vectors that have an orthogonal relationship, ensures that there is an orthogonal relationship between precoding vectors comprised in the generated codewords, and provides a method based on precoding vectors having a plurality of selectable orthogonal modes, thereby ensuring accuracy of determined codewords, ensuring accuracy of precoding data on the basis of codewords, and ensuring communication reliability.

The invention belongs to the technical field of data processing, and particularly relates to a teaching course recommendation method and system based on big data, and the method comprises the steps: obtaining the first recommendability of a target course according to the user number of the target course and the coordinate distribution range of a learning record; obtaining second recommendability of the target course according to the linear change of the user number of the target course included in the learning record along with time and the correlation between the course title of the target course and the news title; according to the activeness of the user and the learning state of the user embodied by the learning record of each user, obtaining a recommendation coefficient of each user; and performing global recommendation and personalized recommendation on the user based on the numerical range of the recommendation coefficient of the user. According to the invention, the accuracy and real-time performance of course recommendation of the education platform are improved.

The invention provides an instruction execution method and device, electronic equipment and a computer program product, and is applied to a processor core, the processor core maintains a renaming mapping table, table items of the renaming mapping table are configured to store physical register numbers or immediate numerical values, and status bits are set for indicating types of table item storage contents. The method mainly comprises the following steps of: dynamically detecting whether the result of a first instruction is an immediate data conforming to a preset numerical range after execution is completed, and directly writing the immediate data into a renaming mapping table, so that a second instruction with data correlation can obtain the immediate data from the mapping table as a source operand at the earliest renaming stage. The fixed path that in a traditional scheme, a consumer instruction must wait for a producer instruction to write back a physical register file to obtain the operand is broken through, the operand ready time is advanced from execution to renaming, and the performance of a processor can be improved.