259 results about "Computational logic" patented technology

The invention relates to the technical field of network communication, and discloses a vehicle-mounted edge computing data recording system and method based on protocol adaptive analysis, and the system comprises a multi-protocol network access controller which is used for capturing an original data frame and extracting a physical feature triple; the identification analysis engine is used for executing hash operation on the triple to generate a physical feature code and retrieving a physical logic address mapping table; the direct memory access controller is used for responding to a target memory address pointer hit by retrieval and directly writing a data load into an input buffer area of the functional operation module, and by constructing a direct addressing mechanism based on Hash mapping, thorough decoupling of vehicle-mounted heterogeneous network physical topology and edge computing logic is achieved.

The invention provides an intelligent question number and index management engine and system based on dynamic reward optimization, relates to the technical field of data learning, and is used for enterprise index analysis, attribution diagnosis and decision support. The system is provided with an index governance layer, index caliber, computational logic, blood relationship, credibility score and version information are managed in a unified mode through a dynamic knowledge graph, unified semantic constraint is carried out on a multi-agent analysis process, and index consistency and traceability are guaranteed. The system also establishes a causal cognition module, based on time sequence data and in combination with expert priori, generates and corrects a business index causal directed acyclic graph, realizes root cause positioning and anti-fact simulation, and answers what change is and what intervention is. The multi-agent collaborative analysis core is responsible for natural language intention analysis, index compliance verification, automatic access, causal inference, narrative generation and chart presentation, calculates a multi-target composite reward value based on user feedback and interaction behaviors, and adaptively adjusts output; and the user corrects and writes back to form closed-loop learning.

The invention discloses a human resource data natural language query and SQL generation method and system, and relates to the technical field of SQL generation, and the method comprises the steps: preprocessing a natural language query text input by a user, and constructing a query semantic tree; traversing the query semantic tree to generate a candidate entity set, determining an unambiguous entity through a three-layer ambiguity resolution mechanism of semantic scoring, service verification and cross validation, identifying a composite intention, disassembling the composite intention into a sub-intention sequence, and generating an SQL operation instruction set in combination with a preset SQL operation mapping rule; based on the SQL operation instruction set and the human resource data association model, determining a data table set and an association path, generating a dynamic calculation logic and structured condition expression, and constructing a structured query skeleton; according to the method, the personalized SQL template is dynamically generated according to the query skeleton, after filling, grammar verification, strategy optimization and logic consistency verification are performed, and the optimized SQL statement is output, so that the query accuracy and performance are remarkably improved.

The invention relates to the technical field of natural language processing, and discloses a generated text quality processing method and system based on a large language model, and the method comprises the steps: constructing a logic topological graph and a Laplacian matrix of an original generated text, and extracting a feature value sequence; recognizing a logic bearing wall based on the attention gradient and generating an anti-fact contrast text; calculating a logic collapse index by combining the difference between the map characteristic values of the original text and the contrast text and the logic polarity overturning condition; and judging the quality of the generated text according to the logic collapse index, blocking the text which does not pass the judgment, and shaping and resampling the output probability value of the error position by utilizing the spectrum difference information to generate a new text. The method does not need to depend on an external knowledge base, quantifies the stability of text logic through anti-fact interference and spectrum analysis, and identifies a high-risk illusion text; and a wrong logic path is automatically corrected through Logits shaping, so that the logic self-consistency of the generated content is improved on the premise of ensuring the semantic smoothness of the text language.

The invention discloses an injection-production regulation imbalance quantitative diagnosis method based on fluid potential energy, and the method comprises the steps: extracting a streamline track space coordinate sequence and corresponding point oil reservoir parameters based on a dynamic permeability field, a pressure field and an injection-production streamline field; constructing a three-dimensional fluid potential energy field model in the injection-production unit, and dividing dominant seepage, a retention zone and a transition zone based on the injection-production unit through potential energy gradient tensor; establishing a seepage potential index LS by taking the flow line penetrating pore volume as a stability weighting factor and combining the potential energy gradient intensity; on the basis of LS sorting, a potential energy-volume two-factor accumulation curve is constructed, the development non-equilibrium degree is represented through curve form parameterization, and the envelope area of the accumulation curve is calculated and used for representing the oil reservoir flow field development non-equilibrium degree and the development effect of each type of injection-production unit. According to the method, fluid potential energy and a two-factor cumulative distribution concept are introduced into computational logic, and unified and quantitative characterization of an oil reservoir flow field and an injection-production unit is realized in combination with a seepage mechanism of the injection-production unit.

The embodiment of the invention discloses a method and device for analyzing a data index, equipment and a medium, and the scheme can comprise the steps: generating a first graph structure used for representing the computational logic of a first data index based on the computational logic code of the first data index; generating a second graph structure for representing the computational logic of a second data index based on the computational logic code of the second data index; performing difference judgment on the first graph structure and the second graph structure to obtain a judgment result; and according to the judgment result, generating description information for representing statistical aperture difference information of the first data index and the second data index.

The invention relates to the technical field of derivative variable calculation, and discloses a derivative variable calculation method and system based on a graph algorithm, and the method comprises the steps: analyzing derivative variable definition and calculation logic through employing a variable SQL syntax tree analysis technology, taking an analyzed variable as a node, determining a variable dependency relationship as an edge according to a processing task, and carrying out the calculation of the derivative variable; constructing a directed acyclic graph and storing the directed acyclic graph in a graph database; the nodes store variable metadata, execution priorities and calculation information, and store calculation task metadata and calculation information; according to node priorities, finding out high-priority variable nodes, querying all in-degree edges of the high-priority variable nodes, forming one or more subtrees, forming high-priority execution subtrees, performing topological sorting on the execution subtrees, and performing execution by an execution engine; the method aims to solve the problems of low calculation efficiency and insufficient utilization of calculation resources in the prior art.

The application provides a smart question and index management engine and system based on dynamic reward optimization, relates to the technical field of data learning, and is used for enterprise index analysis, attribution diagnosis and decision support. The system sets an index management layer to uniformly manage index caliber, calculation logic, blood relationship, credibility score and version information by means of a dynamic knowledge graph, uniformly implements semantic constraints on a multi-agent analysis process, and guarantees index consistency and traceability. The system also establishes a cause-effect cognition module, generates and corrects a business index cause-effect directed acyclic graph based on time series data and in combination with expert priori, realizes root cause positioning and counterfactual simulation, and answers "why change" and "what if intervention". A multi-agent collaborative analysis core is responsible for natural language intention analysis, index compliance verification, automatic data acquisition, cause-effect inference, narrative generation and chart presentation, and calculates a multi-target compound reward value based on user feedback and interaction behavior, and adaptively adjusts output; user correction write-back forms a closed-loop learning.

The invention discloses a risk control rule generation method and device based on a large model and computer equipment. The method comprises the steps of obtaining a to-be-analyzed law and regulation policy entry; automatically analyzing to-be-analyzed laws and regulations and policies by using the large model, and identifying and extracting review structure information; converting the examination structure information into a structured rule expression, and defining a corresponding quantitative index name and computational logic; checking the data index completeness; when the verification is passed, a Python code is automatically generated; checking the Python code by adopting a dual mechanism of static grammar check and dynamic sandbox test; integrating and storing the review structure information, the generation result and the Python code passing the verification in a risk review rule base; and when the new review object is reviewed, obtaining the index data, matching the applicable rule, executing the corresponding code, and summarizing the review result. By implementing the method provided by the invention, deep fusion of policies and regulations can be realized, and efficient generation and dynamic update of risk control rules can be realized.

The invention relates to the technical field of artificial intelligence chips, and provides an operator performance evaluation method and device, equipment, a storage medium and a program product, and the method comprises the steps: obtaining a configuration file corresponding to a to-be-evaluated operator, enabling the configuration file to comprise a hardware configuration file and an operator configuration file, carrying out the instantiation of a global object based on the configuration file, obtaining a hardware platform instance and an operator instance; the operator instance inherits a base class in a unified manner, and the base class is a standardized interface obtained by abstracting computational logic of performance indexes of operators; the global object is a class object obtained by performing interface abstraction on a hardware platform interface and an operator interface; according to the performance index of the base class calculation operator instance when the base class calculation operator instance runs on the hardware platform instance, the evaluation result of the theoretical performance of the to-be-evaluated operator is obtained, multiplexing of the calculation logic of the operator performance index is achieved, the calculation logic of the operator performance index does not need to be rewritten for different hardware platforms, and the calculation efficiency is improved. And the evaluation efficiency of operators across hardware platforms is improved.

A computing system is provided, including one or more processing devices configured to receive an extended stabilizer form of a quantum error correction code. The one or more processing devices are further configured to receive a logical Clifford operation specification of a logical Clifford operation. Based at least in part on the extended stabilizer form, the one or more processing devices are further configured to compute a stabilizer tableau of the quantum error correction code. Based at least in part on the stabilizer tableau and the logical Clifford operation specification, the one or more processing devices are further configured to compute a physical representation matrix of the logical Clifford operation. The one or more processing devices are further configured to output the physical representation matrix.

The invention discloses a privacy protection data classification method and system based on a cloud platform, and relates to the field of data classification management, and the method comprises the steps: distributing sensitivity tags for different data attributes at a client according to a preset strategy, and carrying out the encryption through selecting a homomorphic encryption public key matched with the tag level, and forming a ciphertext beam containing the ciphertext and the label. And then, at the cloud, guiding a subsequent calculation process by using the tag vector in the ciphertext beam. Through a self-adaptive encryption model, different calculation paths can be dynamically selected to execute homomorphic feature engineering and classification calculation according to whether high-sensitivity data exists in a label or not. According to the method, refinement and isolation processing of data with different sensitivities is realized, an encryption strategy and calculation logic are deeply bound, and dynamic balance between calculation efficiency and security level is realized on the premise of ensuring data security.

The invention discloses a bid invitation file compiling method and system based on artificial intelligence, a medium and a product, and relates to the field of intelligent contract processing. The method comprises the steps that a file compiling system divides a natural language text into first text content containing computational logic and common second text content through semantic analysis; then, the first text content is converted into an executable formalized rule expression, and an association mapping relation between the executable formalized rule expression and the first text content is established; and calculating and generating a derivation record containing parameters, calculation steps and dependency relationships according to the expression. And finally, embedding a unique tracing identifier in the generated clause text, and querying and displaying a derivation record through the association mapping relationship by triggering the identifier by a user. According to the method, a complete traceable link from the natural language to the calculation result is realized, so that auditing personnel can clearly understand the logic source of the calculation result, the interpretability and the credibility of the generated calculation terms are improved, and the verification efficiency and the accuracy of the bid invitation file are improved.

The invention provides a lightweight detection method for a small target of an intelligent unmanned vehicle, and belongs to the field of target detection in an artificial intelligence driving scene, YOLOv5s is taken as a reference model, and the specific improvement comprises the following steps: embedding an efficient multi-scale attention (EMA) mechanism behind P3 / 8 and P4 / 16 feature layers of a backbone network, and enhancing the feature perception ability of the model to the small target; a check network is improved, common convolution is replaced by a Ghost module, a C3 module is replaced by a C3Ghost module, and model parameters and calculation amount are reduced to realize light weight; and proposing an SU-WIoU loss function, introducing positioning uncertainty parameter correction anomaly calculation logic, and improving the regression precision of the bounding box of the small target. According to the invention, through collaborative improvement of backbone, check and loss functions, the conflict defect of the existing method on the aspects of small target detection precision and lightweight adaptability is overcome.

The invention discloses a code running time determination method based on a CORTEX M4 chip and related equipment. The method comprises the following steps: establishing a C + + operation support environment for a CORTEX M4 chip; defining a time measurement class, taking system time recorded by a constructor function of the class as starting time, and taking system time recorded by a disruptor function of the class as ending time; and determining the running time of the target code block based on the starting time and the ending time. The problems that at present, a system beat interface is called before and after a code segment to obtain a timestamp, difference is made to measure the running time of the code segment, and repeated time obtaining and difference calculation logic needs to be inserted into each code segment needing to be measured, so that code redundancy and structure bloating are caused can be solved.

The invention discloses a data partitioning method and device, electronic equipment and a storage medium, and relates to the technical field of computers, and the method comprises the following steps: dividing a sliding window of to-be-processed data into a plurality of sub-regions, comparing adjacent byte pairs in the sub-regions in parallel by utilizing a vector instruction to generate a local maximum set, vector maximum comparison is carried out on a local maximum set through a tree structure so as to reduce the scale of the set layer by layer, finally, a global extreme value is determined to serve as a data block boundary, efficient data block division based on vector parallel calculation is achieved, byte-by-byte or block-by-block serial calculation logic is not adopted, and therefore efficient data block division is achieved. The technical problem that in the prior art, due to the fact that serial computing logic is adopted, computing efficiency is limited, performance bottleneck occurs, and then the processing speed and the resource utilization rate of applications such as data deduplication, compression and encryption are affected can be solved. The technical effects of improving the calculation efficiency, reducing storage fragmentation, relieving the performance bottleneck of a high-concurrency scene and improving the data processing speed and the resource utilization rate are achieved.

The invention discloses an automatic data calculation method and system based on configuration driving, relates to the technical field of automation of configuration driving, and solves the problems that although standardized data acquisition of multi-source heterogeneous equipment is realized in the prior art, data calculation modeling depends on hard coding; the same function is difficult to reuse so that the development period is long; computational logic is embedded in a program, debugging and modification are difficult, system retransmission is needed for demand change, and the maintenance cost is high; the technical problems that a large amount of manual intervention exists in a calculation link, rules cannot be dynamically adapted according to field requirements, system universality and expandability are poor, project efficiency is restricted, and multi-scene energy data analysis requirements are difficult to meet are solved. According to the method, common model measuring point configuration is set; after common model measuring point configuration information is read, a function registration mechanism is executed; carrying out callback function binding; and setting a function operation mechanism to solve the technical problem.

The invention relates to the technical field of artificial intelligence and natural language processing, and discloses a large language model reasoning enhancement method based on multilayer reasoning chain verification, which comprises the following steps: constructing a multilayer reasoning architecture based on a pre-trained large language model, and establishing a reasoning state space and a reasoning step transfer function; receiving an input question, generating a parallel inference chain according to the multilayer inference architecture, and determining an inference step sequence and a confidence score of the parallel inference chain; performing consistency score calculation and logic consistency check according to the parallel reasoning chain, and determining a final answer according to the consistency score and the confidence score; and calculating complexity according to the input problem so as to perform adaptive reasoning depth adjustment, determining a reasoning process according to the reasoning depth, and outputting a complete reasoning result. According to the method, a multi-layer parallel reasoning architecture is constructed, and a reasoning chain cross validation mechanism and a self-adaptive reasoning depth adjustment strategy are combined, so that precise processing of a complex reasoning task is realized.

The application provides an automatic disk IO method based on structural mechanics CAE simulation software, comprising the following steps: S1, constructing a memory-disk cooperative computing framework, and dynamically monitoring a data access state in a simulation solving process; S2, automatically exchanging non-active core data structures to a high-performance disk according to a data access frequency, a life cycle and a memory pressure; S3, loading back to the memory on demand when subsequent calculation needs to access the data exchanged to the high-performance disk; wherein the core data structures comprise a stiffness matrix, shape function data, an intermediate result vector and derivative physical quantities, and the exchange process is transparent to the solver. According to the application, the exchange process is highly transparent to the core computing logic of the solver, is automatically managed by the system, and does not need user intervention, so that efficient utilization of memory resources and stable operation of super-large-scale model simulation are realized.

The invention relates to the technical field of automatic generation of low-code components, and discloses an automatic component generation method for a low-code platform. The method comprises the following steps: acquiring and standardizing an original interaction event stream of a user on a canvas to form a user operation chain; and scanning and marking a composite operation unit conforming to a predefined structure on the operation chain, and carrying out dynamic weight distribution according to the spatial layout and the time decay attribute of the composite operation unit. And combining the similar units with similar weights to form candidate component logic blocks. And extracting an interface element dependency relationship of the logic block to construct a dependency graph, and calculating cohesiveness measurement of the logic block based on graph node characteristics. Bridging operations connecting different logic blocks are identified and analyzed, and coupling metrics therebetween are calculated. And fusing cohesiveness and coupling measurement to generate a componentized evaluation matrix. And analyzing the matrix and driving a code template engine, and automatically synthesizing a final visual component. According to the invention, intelligent generation from user interaction to high-quality, high-cohesion and low-coupling components is realized.

A method and system for ensuring consistency between a floating-point arithmetic algorithm verification prototype and hardware engineering, relating to the field of floating-point arithmetic, are disclosed. The method includes: obtaining the HDL source code of a hardware floating-point IP core; converting the sequential logic describing floating-point operations in the HDL source code into a behavioral-level combinational logic expression, which retains the computational logic of floating-point operations; compiling the converted HDL source code using an HDL compilation tool to generate a library file executable on a processor; calling function interfaces in the library file to perform floating-point operations in a prototype verification program running on the processor; and integrating a hardware floating-point IP core into the hardware system to implement floating-point operations, wherein the library file and the hardware floating-point IP core are based on the same HDL source code. Implementing this method can reduce the cost of ensuring consistency between the floating-point arithmetic algorithm verification prototype and hardware engineering.

A system for processing signals from multiple analog-to-digital converters (ADCs) is provided. The system may include a first ADC to receive a first input signal and convert the first input signal to a first digital signal, a second ADC to obtain a second input signal and convert the second input signal to a second digital signal, a control logic circuitry to receive one or more configuration settings of the first ADC and apply the one or more configuration settings to the second ADC, and a computation logic circuitry to generate one or more computational results in response to comparing the first digital signal and the second digital signal.

The application provides a cloud report automatic generation method and system for the financial insurance field, relates to the technical field of financial insurance data processing, and comprises the following steps: abstractly processing original business data, and establishing a data desensitization structure; based on the data desensitization structure, the database table is divided into a basic table, a parameter table, a dictionary table, an intermediate table and a result table; a unified prefix identifier is set for the fields in the basic table and the parameter table, and a mapping relationship between desensitization fields and actual business meanings is established through the dictionary table; based on the data desensitization structure, a business requirement submitted by a business personnel is received; the business requirement comprises a data screening condition, an index field to be displayed and a calculation logic expression of each index; the business requirement is analyzed, core information in the business requirement is extracted, and a security prompt word containing only desensitization fields and logic instructions is obtained. While the safety of sensitive data is ensured, the report generation efficiency and accuracy are improved.

Embodiments of the present application provide a data processing method, system, device, storage medium and program product, relating to the field of distribution. The method comprises: an edge computing node collecting transaction data in real time, extracting feature information of the transaction data, and generating a preliminary risk score based on the feature information through a lightweight model deployed in the edge computing node. The edge computing node receives a global model from a distributed parameter aggregation computing node, updates the parameters and computing logic of the lightweight model based on the global model, so as to update the calculation result of the preliminary risk score. The method of the present application increases the accuracy of abnormal transaction behavior identification and improves the data response speed.

The invention relates to a street view image recognition method and system based on quantum transfer learning. The method comprises the following steps: acquiring a streetscape image data set, and preprocessing the streetscape image data set; pre-training a DenseNet classical neural network based on the preprocessed streetscape digital image data to obtain pre-training parameters; removing the last layer of full-connection neural network of the DenseNet classical neural network, combining the last layer of full-connection neural network with a quantum convolutional neural network to form a mixed quantum classical neural network, fixing parameters of the DenseNet classical neural network based on pre-training parameters, and training the mixed quantum classical neural network by adopting a quantum machine learning framework based on an ISQ quantum compiler; and street scene image recognition is carried out by using the trained hybrid quantum classical neural network. According to the method, strong parallelism and non-local characteristics of quantum computing are applied, hidden information in data is potentially learned by using new computational logic, data training is accelerated, computing resources are saved, and street view digital image recognition can be realized.

The invention discloses a software and hardware collaborative design method for three-dimensional imaging internal structure reconstruction. The method comprises the steps that a three-nested loop general programming model is established, a hardware-friendly algorithm is designed, and a novel near memory computing architecture Waffle is designed; defining a unified programming model to cover different three-dimensional reconstruction tasks; a data stream of the algorithm is redesigned to improve data locality, and redundant calculation is reduced through pre-calculation and simplification of a synchronization scheme; a Waffle hardware accelerator with a near memory computing architecture is constructed and used for accelerating algorithm execution, and related operation is executed under customized computing logic; according to the method, the advantages of near-storage calculation are fully exerted through software and hardware collaborative design, and the speed and energy efficiency of three-dimensional imaging internal structure reconstruction can be improved.

This invention provides a multi-task AI intelligent agent cost estimation system and method adapted to hydropower engineering cost estimation scenarios, relating to the field of hydropower engineering cost estimation technology. It utilizes a visual task interaction module to input basic hydropower engineering information and multi-task instructions. A multi-task AI intelligent agent decouples the input basic hydropower engineering information and multi-task instructions to obtain a task list and task priorities. Based on the tasks, it calls the corresponding data resource sub-libraries, and according to the corresponding calculation logic and priorities, combines the data resource sub-libraries to complete multi-task calculations, outputting the calculation results for each task. This invention solves the problems of information silos, low efficiency, and high error rates in existing cost estimation systems and is applicable to hydropower engineering cost estimation.

The invention provides a data analysis index management method and apparatus, an electronic device and a readable storage medium. The method comprises the steps of obtaining business data; inputting the business data into the large language model to obtain analysis index data corresponding to the business data, the analysis index data including associated analysis indexes, data models and data relationship information; the analysis indexes and a data model are published, and the data model comprises computational logic and related fields of the analysis indexes; and extracting data related to the analysis indexes from the business data according to the data relationship information, and filling the data model with the data. The business data is analyzed through the large language model to obtain the corresponding analysis indexes, so that the problem of index definition errors caused by a manual mode is avoided; meanwhile, the data relation information and the data model are generated, so that the data association between the indexes and the data model can be clearly analyzed, and the flexibility of the data model is improved.

A compute engine including an input buffer and a compute-in-memory (CIM) hardware module is described. The input buffer is coupled to the CIM hardware module and provides an input vector to the CIM hardware module. The CIM hardware module includes an array of storage cells and compute logic. The array of storage cells is configured to store weights corresponding to a matrix. The compute logic is configured to perform a vector-matrix multiplication (VMM) for the matrix and the input vector. The array of storage cells includes storage blocks. Each storage block includes rows and a particular number of columns corresponding to a portion of the matrix. The compute logic includes compute logic blocks. Each compute logic block corresponds to a storage block of the storage blocks. The compute logic block performs a portion of the VMM for the portion of the matrix.

The application provides a compilation method and device of an operator, equipment and a medium, and relates to the technical field of artificial intelligence. The compilation method of the operator comprises the following steps: obtaining operator source code to be compiled, the operator source code being code written in a domain-specific language based on Triton; converting the operator source code into a Triton dialect, performing hardware-independent optimization, the Triton dialect being a hardware-independent dialect based on an MLIR framework and used to represent the computing logic of the operator source code; converting the Triton dialect into a hardware-specific dialect, the hardware-specific dialect being a hardware-related dialect based on the MLIR framework and used to represent hardware-oriented computing logic; generating source code in a general programming language according to the hardware-specific dialect; and calling an LLVM-based compilation tool corresponding to a target chip to generate target code according to the source code in the general programming language. The operator can be applied to chips with different chip architectures.