34 results about "Mathematical logic" patented technology

The invention discloses a business process multi-dimensional logic verification method and system based on a dynamic knowledge graph, and relates to the technical field of artificial intelligence and financial risk control. The method aims at solving the technical problems that a traditional rule engine cannot process unstructured data, and a large generative model has logic illusion and privacy risks. The method comprises the following steps: constructing a rule knowledge graph containing parameterized logic constraints (such as time sequence, mutual exclusion and numerical accumulation); converting the unstructured business operation record into a feature vector by using a locally deployed semantic model; performing global sequence alignment optimization by constructing a global semantic consistency objective function, mapping operation records to a theoretical decision path derived from a graph, and eliminating local matching ambiguity; and finally, on the basis of a mapping result, calling deterministic parameters in map edge attributes to execute strict mathematical logic verification (including complex workday calculation, mutual exclusiveness check and the like). According to the method, a'nerve-symbol 'dual architecture is adopted, accurate understanding of fuzzy semantics is achieved, logic verification certainty and data privacy security are guaranteed, and the method has a hidden process discovery capability.

A handwriting geometry recognition and calibration system by using neural network and mathematical feature includes: a pre-processor for pre-processing coordinate points of geometric figures from user's handwriting so as to get a plurality of sample points which expresses the geometric figures to be recognized; a neural network connected to the pre-processor for receiving the sample points of the geometric figure and recognizing the geometric figure so as to acquire a coarse class of the geometric figure; and an mathematical logic unit connected to the neural network for receiving recognition results from the neural network, including coarse classifications which are used in a secondary classification by using conventional mathematical recognition logics so as to determine an exact geometry shape of the geometric figure; then the geometric figure being calibrated so as to get a geometry with a regular shape.

The invention relates to a multi-unmanned aerial vehicle (UAV) search strategy optimization method based on genetic programming (GP), which is characterized in that under a distributed model predictive control (DMPC) framework, each UAV is guided by a target function to realize a search trajectory optimization process, and essentially, a search strategy is converted into a mathematical logic mapping relation. In a traditional method, objective function construction mainly depends on a design thought dominated by artificial experience, and the fixed search mode based on subjectivity has the limitations of insufficient environmental adaptability, weak strategy generalization ability and the like in a complex dynamic environment. In order to solve the problem, the invention provides a search strategy optimization method based on a genetic programming algorithm, and online dynamic evolution and parameter adaptive adjustment of a search strategy are realized by establishing a dynamic mapping model between a strategy parameter space and a search performance index.

The invention provides a large model correction method, and the method comprises the steps: obtaining a preset original learning material set for a large model; the algorithm and the original learning material set are corrected based on at least one of a pre-constructed geometric logic learning module, a mathematical logic learning module and an Agent instruction learning module, and the learning materials are corrected in more dimensions through one or more learning logics. The requirement of the current artificial intelligence field for the output accuracy of the large model is met, the trained large model can meet the requirement of iterative learning, and the method is more suitable. Meanwhile, through learning and correction of the Agent instruction learning module and other Promote modules, large model iteration can be carried out at each time, the processing logic or input requirements of external Agents are met, a plurality of external Agents are connected at the same time, specified internal and external circulation and sequential logic deduction are formed, the advantages of various Agents and external software are utilized, and the method is suitable for more multivariate output and the like.

This application proposes a problem classification method, a problem classification device, and a computer storage medium. The problem classification method includes: acquiring mathematical problem information; extracting mathematical features from the mathematical problem information, wherein the mathematical features include text features, formula features, and / or graphic features; performing logical reasoning on the mathematical features according to a preset mathematical logic chain; inputting the logical reasoning result into a multi-task output branch to determine the problem classification result of the mathematical problem information. This problem classification method achieves end-to-end multi-label classification of mathematical problems.

The invention discloses a dynamic optimization control method and system for operation of a waste heat boiler, and relates to the technical field of transmission security. According to the method, binary conversion operation is executed on real-time operation data of the waste heat boiler, and a plurality of plaintext arrays cut each time are determined based on the grouping length of a selected encryption algorithm; the method comprises the following steps: creating a reference chain table of each time of cutting in combination with an encrypted document, traversing a plaintext array of each time of cutting to determine all cycle numbers corresponding to each node in the reference chain table so as to determine a last node and a last subscript of each time of cutting, and dynamically cutting running plaintext data according to the last node and the last subscript. The dynamic plaintext data can be supplemented by characters 1 and 0 randomly based on the packet length, so that the data encrypted by the encryption key is dynamic and contains verification logic while the underlying mathematical logic and packet length requirements of the encryption algorithm are not damaged, and the data tampering difficulty is improved.

The present application provides a large model calibration method. The method comprises: obtaining a preset original learning data set for a large model; and on the basis of at least one of a preconstructed geometric logic learning module, a preconstructed mathematical logic learning module, and a preconstructed agent instruction learning module, calibrating an algorithm and the original learning data set. Learning data is subjected to multi-dimensional calibration via one or more learning logics, meeting current requirements for output accuracy of large models in the field of artificial intelligence and enabling the trained large models to satisfy iterative learning demands, thus enhancing applicability. In addition, through learning and calibration of the agent instruction learning module and other promote modules, in each large model iteration, the processing logic or input requirements of external agents can be met, and a plurality of external agents can be interfaced to form designated internal and external loops and sequential logical inferences, leveraging the advantages of various agents and external software to support diverse outputs.

The invention discloses a text data processing method and system based on mathematical logic and propositional logic. The method comprises the steps of firstly obtaining text data and endowing the text data with weights to generate bottom layer data; thirdly, converting the natural language statement into an operable rule system entry by utilizing a pre-constructed mathematical logic and propositional logic framework, and generating a basic value; a logic item set, a positive control item and a negative control item which are input by a user are introduced into bottom layer data, and weight balancing processing is carried out. And finally, according to the matching degree of the items after weight balancing and the basic values of the items, scores are calculated, and the item with the highest score is selected as response data. According to the method, the response data are ensured to completely meet user requirements and system logic in the error-tolerant field, and the method has high accuracy and reliability.

This invention discloses a control method for UAV spraying operations on columnar or quasi-column structures, belonging to the field of UAV operation and surveying technology. Targeting the surface characteristics of different types of quasi-column structures, this invention constructs a complete mathematical logic system through three-dimensional data acquisition, optimal fitting of a reference cylinder, construction of a reference cylinder-assisted latitude and longitude positioning system, resampling of the reference cylinder's surface grid, unfolding the cylinder to a two-dimensional plane and completing pattern design, and point calculation for UAV spraying. This achieves precise projection transformation of the planar design pattern onto the structure's surface, providing industrial mathematical support for UAV spraying trajectory planning, attitude control, and parameter adjustment. This invention features high design accuracy, simple control logic, and good visual effects, effectively solving the problem of pattern deformation on curved surfaces of columnar or quasi-column structures. It is applicable to automated UAV spraying operations on various columnar or quasi-column structures such as TV towers, giant chimneys, angular TV towers, and water towers.

The invention relates to an intelligent contract formalized specification method and device, electronic equipment and a storage medium, and the method comprises the steps: determining a mathematical logic type and a statement type contained in a target code according to the target code of an intelligent contract, and determining a target logic expression of a Solidiity language corresponding to the mathematical logic type, according to the method, the formalized specification is expressed by adopting a behavior interface specification language, the accuracy of mathematical logic and the unique attribute of a Solidiity language can be fused, a target logic expression and a target statement specification are embedded into a target code in an annotation form, and it can be ensured that the formalized specification has necessary preciseness when describing the intelligent contract behavior, and the formalized specification can also be embedded into the target code in the annotation form. And the method can be closely combined with actual programming practice, and developers do not need to learn specific formalized languages, so that the efficiency of the developers for constructing the formalized specification framework for the smart contract is improved.

This invention belongs to the technical field of industrial control, and more specifically, relates to a data-driven modeling method based on DCS logic autonomous exploration. The method includes: collecting real-time data and preprocessing it, then calculating the time delay relationships of various influencing factors under different operating conditions; constructing a dictionary library, encapsulating the mathematical logic of basic algorithm blocks from the DCS algorithm block function library into basic units in the dictionary library, serving as the basic units for building the required model; using machine learning algorithms to train and explore mathematical model structures that match the dictionary library for various influencing factors and temperature changes; and executing deployment based on the DCS system and the generated mathematical model structure. This invention solves the problems that while neural network prediction models can make predictions, they cannot be directly converted into DCS logic execution structures; and that current mathematical modeling methods require manual selection of function structures, which cannot adapt to complex systems, often resulting in a disconnect from the DCS structure and hindering engineering implementation.

The application provides a mathematical description language large model establishment method, medium and system, belonging to the technical field of computer model, which first acquires corpus information through constructing a training data set, then carries out word segmentation and feature extraction on natural language description text, constructs an inexact description matrix, and carries out structured processing on standard mathematical description language text to form an accurate description matrix. On this basis, a display memory pool is established and training resources are pre-allocated, and a multi-level mathematical logic reasoning network model is constructed. Through contribution value evaluation and accuracy calculation, resource optimization allocation based on importance is realized, and a display memory pool management mechanism is adopted to ensure efficient use of resources. Through the quantitative evaluation mechanism and dynamic optimization strategy, the efficient training of the mathematical description language conversion model is realized, and the technical problem of low utilization of computing resources caused by unreasonable allocation of display memory in the training process of the mathematical description language large model in the prior art is solved.

The invention discloses a multifunctional interdisciplinary playing card teaching appliance and a storage piece, and relates to the field of card teaching, and the multifunctional interdisciplinary playing card teaching appliance comprises a plurality of first cards, at least two four-color sunshine music score symbol areas which are arranged on the surfaces of the first cards and are located at the left upper corners and the right lower corners of the surfaces of the first cards, and at least two music rhythm symbol areas which are located at the left lower corners and the right lower corners of the surfaces of the first cards. According to the multifunctional interdisciplinary playing card teaching appliance and the storage piece, through various card teaching modes, music rhythm, mathematical logic and artistic design are fused, so that students can improve artistic literacy, logical thinking and collaboration ability in games, music is not abstracted any more, mathematics is not dull any more, and art is not isolated any more; the learning becomes an exploration, growth is stained with sunlight temperature, each child can find light belonging to the child in card teaching, the learning seems like sunlight, knowledge is rooted in games, rhythm and logic dance is achieved, and rationality and creativity are made to be at the same time.

The invention discloses a structure response rapid prediction method based on a physical coding graph network. The method comprises the following steps: constructing the physical coding graph network; inputting the physical parameters of the target structure into a physical coding graph network for coding; message passing is carried out on the coded physical parameters, message passing comprises node mapping and edge mapping which are carried out in sequence, and data flow of message passing conforms to mathematical logic; and decoding results of node mapping and edge mapping to obtain a displacement prediction result and an internal force prediction result. According to the invention, through constructing the physical coding graph network, multi-working-condition structure response rapid prediction is realized; the encoding, message passing and decoding processes are matched with complex structure parameters, accurate prediction of displacement and internal force is completed through node mapping and edge mapping in a labor division mode, the problem of repeated calculation of a traditional method is solved, the digital twinning real-time interaction requirement is met, rapid iterative design and real-time performance evaluation are efficiently supported, and a better solution is provided for structural engineering calculation.

The invention provides an English word and mathematical logic interaction device, and belongs to the technical field of English word teaching, the English word and mathematical logic interaction device comprises a main body, the main body comprises a central processing unit, a storage unit, an input module, an output module and a communication module; the central processing unit is electrically connected with the storage unit, the input module, the output module and the communication module through the PCB, a word analysis engine is arranged in the central processing unit, and a direct data channel is established between the analysis engine and the storage unit; a partition structure is arranged in the storage unit and comprises a system storage area and a morpheme logical data special storage area, the input module integrates a physical key group and a touch component, and the output module comprises a display panel and an audio playing component. According to the invention, the problem that the vocabulary reasoning ability and memory efficiency cannot be improved because the essence that English words are combined according to a specific logic rule is neglected in the existing novelty word teaching technology is solved.

The invention discloses a hardware acceleration system for anomaly detection of an isolated forest algorithm based on an FPGA (Field Programmable Gate Array), and belongs to the technical field of electronic information. The hardware acceleration system for anomaly detection of the isolated forest algorithm based on the FPGA comprises an algorithm implementation module, a read-write module, a register module and a mathematical calculation module, the algorithm implementation module is used for building trees and forests in an isolated forest algorithm, calculating and recording abnormal scores and judging; the read-write module is mainly used for interacting with an external system, reading and writing data, and reading, writing and processing complex data by using a plurality of interfaces; the register module is used for storing the generated tree, forest and calculation data; and the mathematical calculation module is used for assisting the algorithm implementation module to package and integrate complex mathematical logic and functions. The system is innovated in hardware and algorithm aspects, so that the system is lower in cost and wider in application scene and range.

The invention relates to the technical field of data processing, in particular to a visual education quality evaluation report making method, which comprises the following steps: aiming at education quality evaluation dimension options, analyzing mutual influence and association relationships among dimensions, constructing a dimension association relationship model, and checking required dimensions by a user according to evaluation key points and targets and reference displayed association information; external data are imported, the data are input manually, and the system processes duplicated data and conflict data according to an optimized data association rule in combination with the dimension association relationship model; a user selects a calculation formula from a formula library, a system automatically extracts corresponding data and calculates according to a preset mathematical logic and algorithm rule, and a result is temporarily stored and associated with a corresponding dimension to serve as a basis for subsequent display and report generation; the system calculates the index value of each dimension according to the setting, and displays the progress and related prompts; generating graphic display content according to a calculation result and a template reserved area, and automatically optimizing and updating and displaying in real time; and the system converts the generated file for downloading and storing.

The embodiments of the present application relate to the field of digital twin technology, and in particular to a method for constructing a digital twin system, the method comprising: performing digital twin modeling on a number of entity objects in the same target space to obtain a digital twin model corresponding to each entity object; gridding the target space to obtain a network corresponding to the target space, and mapping each digital twin model to the network; establishing static attributes and dynamic attributes for each grid unit in the network, respectively, and generating a static attribute table and a dynamic attribute table for each grid unit; generating a global digital base based on the static attribute table of each grid unit, generating a global mathematical logic model based on the dynamic attribute table of each grid unit, and obtaining a digital twin system corresponding to the target space based on the global digital base and the global mathematical logic model, thereby realizing the association of multi-dimensional heterogeneous data, reducing the computing power requirements of the digital twin system, and facilitating data management and use.

The present invention belongs to the technical field of CNV detection, and discloses a CNV detection method, system and reliability verification method based on a small panel. The detection method comprises: obtaining an original data matrix, wherein one column in the original data matrix is ​​the depth data of the sample to be tested, and the remaining columns are the depth data of the control sample; calculating the ratio between each depth data in each row of the original data matrix and the geometric mean of the row to obtain an intermediate data matrix; calculating the ratio between each depth data in each column of the intermediate data matrix and the median of the column to obtain a correction data matrix; solving the ratio between the sample to be tested and the control sample in each amplification region based on the correction data matrix to obtain the CNV type of the sample to be tested. Thereby effectively improving the accuracy of the detection result. The reliability verification method is based on mathematical logic, which is simpler and more feasible than the existing method based on a large number of simulation calculations, and the reliability of the result is better.

The invention provides a mathematical description language large model establishment method, medium and system, and belongs to the technical field of computer models.The method comprises the steps that firstly, corpus information is obtained by constructing a training data set, then word segmentation and feature extraction are conducted on a natural language description text, and an imprecise description matrix is constructed; and performing structured processing on the standard mathematical description language text to form an accurate description matrix. On the basis, a video memory pool is established, training resources are pre-allocated, and a multi-level mathematical logic reasoning network model is constructed. Through contribution value evaluation and accuracy calculation, resource optimization allocation based on importance is realized, and efficient utilization of resources is ensured by adopting a video memory pool management mechanism. According to the whole scheme, efficient training of the mathematical description language conversion model is achieved through a quantitative evaluation mechanism and a dynamic optimization strategy, and the technical problem that in the prior art, in the mathematical description language large model training process, due to unreasonable video memory allocation, the computing resource utilization rate is low is solved.

The present application provides a data anomaly detection method based on a deformation model, a storage medium, and an electronic device. The method comprises: acquiring service data, and determining a data temporal characteristic of the service data; on the basis of the data temporal characteristic and historical service data, determining a reference baseline curve of the service data; on the basis of the service data and the reference baseline curve, calculating a baseline deformation variable of the service data; and on the basis of the baseline deformation variable, determining an anomaly alert. According to the method provided by embodiments of the present application, a data anomaly can be effectively converted into an anomaly in mathematical logic, and anomaly conditions can be quickly identified from time sequence data according to the described method, thereby significantly improving the accuracy of anomaly recognition. By applying data transformation processing twice, the described method enhances the capability of recognizing a data anomaly, and also improves the efficiency and accuracy during a recognition process. In addition, the reusability of the method is enhanced, so that high-efficiency and accurate performance can be maintained in different data scenarios.

The invention discloses a handwritten mathematical formula identification method, relates to the technical field of optical character identification, and is used for solving the problem of inaccurate handwritten mathematical formula identification in the prior art. The data of the handwritten mathematical formula is obtained and the data receiving type is judged in an offline and online data obtaining mode. And respectively carrying out offline image formula processing and online note formula processing on the data obtained in the offline mode and the online mode. And a convolutional neural network (CNN) and a recurrent neural network (RNN) are adopted to carry out symbol identification and model training on offline symbols and online symbols respectively, symbol analysis is further carried out on the symbols in the formula, and then the symbols form an expression conforming to mathematical logic. And the recognition accuracy of the handwritten mathematical formula is improved.

The invention relates to a graphical general killing chain construction and evaluation method, which comprises the following steps of: constructing a reachability matrix model of nodes in a chain according to a communication relationship among a reconnaissance node, a command node, a firepower node and a target in a closed system of a killing chain, and expressing a reachability matrix as a graticule form; traversing in an anticlockwise mode based on four areas of a target reconnaissance node, a command node, a firepower node and a target to obtain a killing chain combination scheme; and calculating the response time, strike precision and firepower strike capability of the killing chain, evaluating the performance of the killing chain, and determining an optimal killing chain combination scheme. The killer chain construction model provided by the invention has a visual graphical closed-loop form, a mathematical logic framework in a chain construction process is clear, and the method has good solution implementation and result convergence and is beneficial to engineering application.

The invention discloses a digital analysis, research and judgment method based on a K-line form theory, which comprises the following steps of: selecting K-line combination forms of three continuous trading days, and marking the K-line combination forms as K-line bodies of A, B and C days; a price generation track is extracted through four-dimensional K line body diagonal analysis (entity upper and lower diagonal groups and upper and lower leads); the golden section lines are established as price relay positions and intersections, and the golden section lines are determined in the following mode that manual line drawing is replaced with a geometric mathematical model, and traditional K line analysis depends on empirical trend line drawing and is easily affected by subjective judgment. By establishing standardized calculation rules of golden section lines (intersections) and multi-gear pressure / support lines, trend judgment is based on mathematical logic, and personal errors are reduced.

The invention relates to the technical field of data processing, in particular to an efficient parameter sharing city spatio-temporal data prediction method, which comprises the following steps of: defining a parameter sharing time expansion convolution operator and a parameter sharing graph diffusion convolution operator; a parameter sharing time expansion convolution operator and a parameter sharing graph diffusion convolution operator can effectively and quickly capture the space-time dependency relationship in the data under the condition that the model calculation time and the model parameter scale are not remarkably increased; a mathematical logic relationship among the hyper-parameters is established, the search space of the hyper-parameters is reduced, the parameter adjustment difficulty of the hyper-parameters is reduced, the trial and error time and resource investment are reduced, and the excellent performance of the PSDCNN model in a space-time prediction task is ensured. According to the PSDCNN model provided by the invention, the space-time prediction task can be accurately completed under the condition that the model calculation time / model parameter scale is not remarkably increased. The PSDCNN model has a prediction accuracy that exceeds or approximates a baseline method.

The invention discloses a calculation guidance method and device for mathematical logic recognition, and relates to the technical field related to data processing, and the method comprises the steps: obtaining user submission information for a target bridge; performing mathematical logic identification on the bridge three-dimensional design model, and establishing a mathematical logic rule base; each to-be-machined sheet metal part is dispersed into a limited number of sheet metal units, and target parameters of each sheet metal unit are configured; constructing a mathematical model and a target function for sheet metal blanking optimization; the mathematical model is input into a calculation guide module for solving, and an optimal blanking scheme is obtained; and the metal plate discharging equipment is controlled to conduct machining, and the multiple metal plate parts needed by the target bridge are obtained. The technical problems that in existing sheet metal part machining, manual discharging depends on workers according to sheet metal bridge drawings, the sheet metal machining precision is insufficient, and the machining efficiency and the material utilization rate are low are solved, intelligent control over sheet metal discharging is achieved, and the technical effects that the sheet metal discharging efficiency and precision are improved, and materials are saved are achieved.

The invention discloses a configuration solving method and device based on multi-normal-form analysis and electronic equipment, and relates to the field of data processing. The method comprises the following steps: acquiring various types of constraint formulas; according to the type of the constraint formula, extracting a corresponding variable set, a value domain set and a constraint set to form a basic logic expression; performing standardization processing on the basic logic expression to obtain a standardized logic expression; based on the standardized logic expression, a logic syntax tree is constructed, and the logic syntax tree comprises a logic structure and a variable relation of a constraint formula; converting the constraint formula in the logic syntax tree into a standard normal form formula by utilizing a mathematical logic identical equation; inputting the standard normal form formula into a preset SAT solver based on conflict-driven clause learning to generate a solving result; and according to a solving result, generating effective configuration options meeting constraint conditions. By implementing the technical scheme provided by the invention, the accuracy of the configuration solution result is improved.

The application discloses a kind of structure response fast prediction methods based on physical coding graph network, comprising: constructing physical coding graph network;The physical parameters of target structure are input into physical coding graph network coding;Message passing is carried out to the physical parameters after coding, message passing includes successively carried out node mapping and edge mapping, and the data flow of message passing meets mathematical logic;The result of node mapping and edge mapping is decoded, and displacement prediction result and internal force prediction result are obtained.The application, by constructing physical coding graph network, realizes the fast prediction of structure response in multiple working conditions;Wherein, the coding, message passing, decoding process adapts complex structure parameters, node mapping, edge mapping division completes the accurate prediction of displacement and internal force, solves the problem of repeated calculation of traditional method, meets the real-time interaction demand of digital twin, efficiently supports fast iterative design and real-time performance evaluation, provides better solution for structure engineering calculation.

The present invention discloses a pseudo-dual learning method for automatically solving math problems. During the training and optimization process of the automatic solver for math problems, a pseudo-dual task is introduced to simulate the review process. That is, after obtaining the solution expression, the numbers in the expression are filled back into the original text problem description, thereby improving the automatic solver's ability to capture the number of math problems and its mathematical logic ability. In addition, during the joint training optimization process, the present invention also designs a plan fusion strategy, which uses the correct expression for number filling in the early stage of training, and smoothly transitions to using the predicted expression for number filling in the later stage of training, to solve the problem that the predicted expression is not ideal in the early stage of training and will mislead the pseudo-dual learning. At the same time, the plan fusion strategy can balance the learning of the solution process and the pseudo-dual filling process during the training process. Through experimental research, the present invention significantly improves the performance of multiple representative automatic solvers for math problems.

The application discloses a multiplication table learning device, which comprises a machine body, a first button group, a second button group and an intermediate area are arranged on the front of the machine body, the intermediate area comprises 81 physical buttons of the same size arranged according to a 9*9 array, each physical button corresponds to a number button of the first button group and the second button group, and each physical button can be separately lighted and pressed, a circuit board electrically connected with the physical buttons is further arranged in the machine body, a voice module and a function module are arranged on the circuit board, and a first function button, a second function button and a third function button electrically connected with the function module are arranged on the front of the machine body. The application has the effect of reverse memory and learning, helps children understand the mathematical logic behind the multiplication table, and assists them to more quickly remember the multiplication table. In addition, the function module is diversified, can enhance the interactivity from different angles, and thus improves the interest and the learning efficiency.