542 results about "Computational logic" patented technology

The invention relates to the technical field of data information processing, in particular to an artificial intelligence-based index layer model construction analysis method and system, and the method comprises the following steps: 1, multi-source data synchronization and quality evaluation; 2, service context analysis and subject domain intelligent division are carried out, and service document and data table field semantics are analyzed; 3, index demand intelligent analysis and calculation logic generation: analyzing index demands input by a user through a natural language processing technology, matching service entities in the knowledge graph, generating initial calculation logic and optimizing execution efficiency; and 4, dynamically updating the index data and verifying the consistency, executing the optimized computational logic to generate the index data, tracking the blood relationship of the data, triggering dynamic updating, and setting a threshold value according to a historical fluctuation range to carry out abnormal alarm. Through automatic and intelligent processing, the probability of human intervention and human errors is reduced, and the efficiency and accuracy of data processing are improved.

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 railway contact networks, and provides a railway contact network icing thickness prediction method and system. The method comprises the following steps: inputting meteorological environment parameters into a machine learning model, and carrying out dynamic calibration on icing medium parameters based on the meteorological environment parameters by utilizing the machine learning model to obtain calibrated icing medium parameters; obtaining an icing growth coefficient based on the meteorological environment parameters, the conductor physical characteristic parameters and the calibrated icing medium parameters; and inputting the calibrated icing medium parameters and the icing growth coefficient into a Makkonen model to obtain an icing thickness prediction value. According to the technical scheme provided by the invention, the key icing parameters are dynamically calibrated through machine learning, and the computational logic of the Makkonen model is optimized, so that the icing thickness prediction precision under complex meteorological conditions is improved, and the problem of prediction failure caused by insufficient environmental adaptability of a traditional static model is solved.

The embodiment of the invention discloses a charging cost analysis method and system for a liquid cooling over-charging terminal, and belongs to the technical field of data analysis. According to the method, through multi-dimensional data acquisition and deep behavior analysis, accurate description of user charging behavior characteristics can be realized, the accuracy of charging demand prediction and resource scheduling is effectively improved, and the user behavior characteristics are converted into quantifiable parameters, so that the user experience is improved. According to the invention, the formulation of differentiated service strategies can be realized to enhance the personalized adaptation capability of the charging service. Besides, the generation and execution mechanism of the cross-terminal dynamic scheduling strategy can optimize the distribution efficiency of the power resources in the space-time dimension and relieve the local overload problem in the peak period, and the cooperative adjustment function of the real-time power supply parameters and the cost calculation logic can guarantee the charging efficiency and balance the operation stability of the power grid at the same time. In conclusion, the method can significantly improve the resource utilization efficiency of the charging facility.

A power equipment data intelligent interaction method, system, device and medium, comprising: retrieving database table information based on query information input by a user to obtain database table information; performing power equipment knowledge base retrieval based on the query information to obtain business knowledge calculation logic and a context learning example; creating prompts based on database table information, business knowledge calculation logic and context learning examples, and inputting the prompts into the large model to generate database statements; running the database statement and judging whether the statement succeeds or not, and if yes, outputting a query result; otherwise, error correction is carried out, and corrected database statements are obtained and run again; according to database table information retrieval, extraction of table field links, table main and foreign keys and table association relationships can be carried out on user query, the accuracy and performance of model generation database languages are improved, the data query threshold is lowered, and the data utilization efficiency is improved; the power equipment knowledge base can realize flexibility and expandability of business knowledge injection.

The embodiment of the invention provides a rapid data visualization generation method and device based on a large language model, and the method comprises the steps: receiving and analyzing a data analysis demand sent by a user, inputting a target business index and target business dimension information in the data analysis demand into a demand classification model, obtaining a type index and a measurement index output by the demand classification model; determining the hierarchical structure and layout of the report according to the logical relationship between the type indexes, and adding computational logic for the report according to the computational formula, aggregation mode and display format of the measurement indexes to generate a corresponding business report; according to the method, data visualization can be efficiently and accurately realized.

Described is a packaging technology to improve performance of an AI processing system. An IC package is provided which comprises: a substrate; a first die on the substrate, and a second die stacked over the first die. The first die includes memory and the second die includes computational logic. The first die comprises DRAM having bit-cells. The memory of the first die may store input data and weight factors. The computational logic of the second die is coupled to the memory of the first die. In one example, the second die is an inference die that applies fixed weights for a trained model to an input data to generate an output. In one example, the second die is a training die that enables learning of the weights. Ultra high-bandwidth is changed by placing the first die below the second die. The two dies are wafer-to-wafer bonded or coupled via micro-bumps.

The invention belongs to the field of data processing, particularly relates to a standardized processing method, system and equipment for original engineering parameters of a flight simulator, and aims to solve the problems of serious field limitation, low processing efficiency and poor adaptive capacity in the prior art. The method comprises the following steps: analyzing a predefined configuration file, and dynamically generating a database temporary table matched with an original data file structure according to field structure information and a parameter mapping rule defined in the configuration file; directly loading original engineering parameter files into the temporary table by adopting a batch loading mechanism based on a file system path, and executing multi-file parallel import based on a task queue; and converting calculation logic in the parameter mapping rule into an executable query expression, and directly exporting a standardized parameter file after calculation is executed through the temporary table. According to the method, field limitation is broken through, efficient processing of mass data is achieved, instant updating of service logic is achieved through configuration rules, and the maintenance cost is greatly reduced.

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 embodiment of the invention discloses a method and device for constructing a field consanguinity tree, a storage medium and a terminal. Firstly, a target field, a database query statement of the target field and upstream blood relationship information are obtained, the target field serves as a root node, a first executable calculation function packaging calculation logic of the target field is generated, and the calculation process is dominant and modularized. By analyzing input parameters of the function, an upstream field which directly depends on is automatically identified and determined to serve as a child node. And then recursively processing each sub-node, generating a corresponding calculation function, analyzing the dependency of the calculation function, tracing layer by layer until all leaf nodes (namely original bottom table fields), outputting a complete blood relationship tree containing all the nodes and the corresponding calculation function, and displaying the complete blood relationship tree through a visual interface. According to the method, automatic and accurate tracing from a target field to an original data source is realized, a computable and reusable blood relationship knowledge framework is constructed, and a solid foundation is provided for data understanding, problem investigation and intelligent data service.

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 invention discloses a three-dimensional model rendering method and device, a storage medium and electronic equipment. The method comprises the following steps: firstly, determining an implicit function corresponding to a to-be-rendered model; and based on the implicit function, determining calculation logic used for calculating a directed distance from each voxel in a to-be-rendered space corresponding to the to-be-rendered model to the to-be-rendered model. And generating an operation instruction sequence for realizing computational logic. And determining a directed distance from each voxel to the to-be-rendered model according to the operation instruction sequence through a graphics processing unit (GPU). And determining an observation view angle corresponding to the to-be-rendered model, and rendering the to-be-rendered model according to the observation view angle and each directed distance to obtain a rendered image corresponding to the observation view angle. The operation instruction sequence used for achieving calculation logic is generated firstly, then the directed distance from each voxel to the to-be-rendered model is calculated by the GPU according to the operation instruction sequence, the calculation efficiency is improved, and therefore the rendering efficiency is improved.

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 present application provides a TVM-based NPU neural network model deployment method and device, including: obtaining the neural network model to be deployed and the hardware attribute information of the current NPU; determining the convolution operator to be deployed to the current NPU based on the computational logic of the neural network model; determining the optimal parameter configuration of each convolution operator in the current NPU based on the hardware attribute information of the current NPU and the parameter information of each convolution operator; adjusting the data layout and convolution weight of the TIR layer and modifying the parameters of the relay layer based on the optimal parameter configuration and the hardware attribute information of the current NPU to obtain a target TVM adapted to the current NPU; generating a deployment file for the neural network model suitable for the current NPU based on the target TVM. By adjusting the parameters of the TVM's TIR layer and relay layer accordingly, the obtained target TVM can be adapted to the NPU.

The invention relates to an anti-reverse confusion method and system for an end-side equipment deep learning model, and the core process comprises the steps: firstly inputting an original model obtained through the training of a model training frame into a deep learning compiling frame, and extracting three types of key information, namely, a model operator, a topological structure, parameters and dimensions, through the characteristics of a compiler; then constructing a feature analysis module to evaluate model features, dynamically matching a confusion scheme from a strategy library, and balancing safety and performance; the confusion module is embedded into a plurality of different levels such as a computational graph level, an operator template level and tensor intermediate expression through a hierarchical compiling mechanism, and a complex scheme can be jointly implemented across multiple levels; and finally, the compiler synchronously completes confusion reinforcement when generating the target code. According to the method, hardware adaptation is not needed, low-overhead confusion is achieved through a native pass mechanism of a compiler, fine-grained customized protection is supported, a model structure, parameters and computational logic can be effectively hidden, reverse engineering attacks can be resisted, and the method is particularly suitable for end-side equipment scenes with limited computing power.

A feature deployment service of a provider network may deploy feature processing units (FPUs) to implement data processing features at both a provider network and edge devices. The use of FPUs may allow a client to use new features at the edge, without delays due to compliance / testing or software upgrades. An FPU includes a model and compute logic that are used to implement a data processing feature. A feature processing service deploys the FPU to an FPU engine at the provider network and also deploys the FPU to edge devices of the client's network that each include an edge FPU engine. The FPU engine at the provider network and the edge FPU engine at each edge device conform to a common specification / API, allowing deployment and use of the same FPU / data processing features at both the cloud and the edge.

The invention discloses a method for constructing a Text2MDX framework based on an intelligent agent, and relates to the technical field of natural language processing, and the method comprises the steps of constructing an intelligent agent architecture, constructing a chain structure composed of a semantic analysis intelligent agent, a rule memory intelligent agent and an MDX synthesis intelligent agent, and constructing a Text2MDX framework. The method has the advantages that the chain structure composed of the semantic analysis intelligent agent, the rule memory intelligent agent and the MDX synthesis intelligent agent is constructed, the semantic analysis intelligent agent can accurately disassemble the text and extract potential self-defined semantic rules in multi-round dialogue or long text processing, in the whole process, the intelligent agent chains cooperate in order, and the user-defined semantic rules are extracted; the cross-sentence context logic is automatically maintained, the situation that the MDX expression lacks key calculation logic is avoided, the accuracy and reliability of conversion from the natural language to the MDX expression are remarkably improved, more accurate data analysis support is provided for a user, and the problem of context breakage of a complex interaction scene is solved.

The invention discloses a reusable key value cache generation method and device, equipment, a storage medium and a product, and relates to the technical field of computers.The reusable key value cache generation method comprises the steps that an obtained text block is input into a preset large model, and a reusable key value cache corresponding to the text block is output based on a preset fixed prefix key value, the preset large model is obtained by optimizing calculation logic of an attention layer of the original large model based on an attention distribution mechanism. According to the method, the reusability of the key value cache is realized through the preset large model based on the preset fixed prefix key value, the problem of unstable model output caused by position coding and attention distribution changes is effectively solved, and the reuse efficiency of the key value cache is remarkably improved. Meanwhile, the computational logic of the attention layer of the model is optimized, so that the performance and stability of the model during multiplexing of the key value cache of the text block are improved.

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 invention discloses a knowledge graph inference method based on prior knowledge enhancement, and mainly solves the problem of inaccurate reward caused by insufficient knowledge graph prior knowledge in the existing knowledge graph inference method based on reinforcement learning, thereby optimizing a model more effectively. The method comprises the following steps: reasoning path searching based on reinforcement learning; calculating an answer correctness reward; logic rationality reward calculation; a reward enhancement strategy based on path importance; performing logic rationality reward enhancement based on large language model context learning; and optimizing the model. According to the method, on the basis of an existing knowledge graph reasoning method based on reinforcement learning, huge internal knowledge of a large language model is fused into reward calculation in an efficient and information loss resistant mode, and the problem that rewards are inaccurate due to insufficient prior knowledge of a knowledge graph is solved. The performance of the knowledge graph reasoning method based on priori knowledge enhancement is remarkably improved compared with that of an existing method.

The embodiment of the invention provides an information configuration method, an information processing method, equipment, a storage medium and a program product. In the embodiment of the invention, through decoupling a business index computational logic and an application system, computational logic description information expressed by a natural language is received, a corresponding relation between a business index and a data source is generated, and the business index is converted into a factor and configuration information thereof by utilizing an artificial intelligence (AI)-based language model; meanwhile, the computational logic is converted into a computational formula of a dependency factor, and finally independent and configurable computational logic configuration information is formed to be called by an application system. When the calculation logic needs to be updated, only the configuration information needs to be modified, the application system does not perceive, and synchronous upgrading or updating is not needed, so that business personnel can flexibly adjust the calculation relation between the business indexes according to actual requirements, and the flexibility and efficiency of business decision making are improved; and the dependence on developers and the adjustment cost of the application system are reduced.

The embodiment of the invention provides a mining factory aided design method and system, and the method can obtain design demand data input based on a browser page canvas, and builds a target process model according to the design demand data. Wherein the target process model comprises a general model and a special model. And calculating process flow data based on the target process model, executing equipment type selection calculation according to the process flow data, generating a calculation logic diagram, and mapping the calculation logic diagram into a process flow diagram. According to the method, process modeling and process calculation can be quickly carried out, and a special model conforming to the industrial computer theory is supported to be built, so that modeling and calculation are simpler and more efficient. Meanwhile, a calculation result and a model can be conveniently applied, equipment type selection calculation and process flow diagram output are carried out, unification of models and data in all links is achieved, and the design efficiency of a mining factory is improved.

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 natural language processing system encryption method, electronic equipment and a computer readable medium. The method comprises the following steps: acquiring a character mapping relationship between an original character and an encrypted character determined based on a character encryption algorithm; according to a Token ID transformation algorithm, a Token ID mapping relation between the original Token ID and the transformed Token ID is determined; and according to the character mapping relationship and the Token ID mapping relationship, encrypting a pre-trained natural language processing system, so that the encrypted natural language processing system can output a ciphertext response based on an input ciphertext prompt word. Side channel attacks and middle eavesdropping can be resisted, the exposure risk of original data is remarkably reduced, the data security is improved, mathematical reconstruction of computational logic of the system is avoided, so that the computational overhead is remarkably reduced, the reasoning delay is reduced, the computational efficiency and the response real-time performance are improved, a natural language processing system does not need to be retrained, and the method is easy to implement. The calculation overhead is further reduced, and the encryption efficiency is improved.

The invention aims to provide an elite colony search method for a multi-factory capacity and inventory integrated allocation problem. The method comprises the following steps: obtaining order data and production resource data to be allocated; calculating an order allocation scheme according to the order data to be allocated and the production resource data by adopting an elite ant colony algorithm; and calculating the productivity and inventory distribution result of each order according to the order distribution scheme. In a large-scale multi-factory order allocation scene, the idea of the ant colony algorithm is adopted, an elite ant colony search idea of directional production line search is introduced, convergence of the algorithm to an optimal solution is accelerated, calculation logic is optimized, the result goodness is improved, and therefore the limitation of manual order allocation decision making is made up.

The invention provides a sensitive data collaborative auditing platform and method based on multi-party network security computing, and relates to the technical field of multi-party security computing. The platform comprises a data input layer which is used for each data holder to acquire original data, standardize the original data, perform differential privacy processing on the standardized data, encrypt private data by adopting a Paillier homomorphic encryption algorithm to obtain a ciphertext, segment the ciphertext by adopting Shamir secret sharing to obtain a plurality of segment ciphertexts, uploading the fragmented ciphertext to a confusion layer; the confusion calculation layer is used for aggregating the fragmented ciphertexts to obtain aggregated ciphertexts, fragmenting the aggregated ciphertexts by adopting Shamir secret sharing to obtain a plurality of fragmented aggregated ciphertexts, and distributing the fragmented aggregated ciphertexts to audit layer nodes; performing target calculation on the fragmented aggregation ciphertext by adopting MPC calculation logic; and the auditing execution layer is used for converting the auditing rule into MPC computational logic. According to the application, the security, efficiency and cross-domain compatibility of multi-party collaborative auditing can be improved.

A method for controlling a power generating asset having a generator with a stator operably coupled to a transformer and a rotor operably coupled to the transformer via a power converter includes using an angle of a phase-locked loop (PLL) reference signal of a PLL at a PLL reference node of the power generating asset to transform a three-phase set of signals to a two-dimensional orthogonal coordinate system of a synchronously rotating frame. The two-dimensional orthogonal coordinate system includes x and y components of at least one of voltage and current. The method also includes determining one or more dynamic decoupling factors as a function of one or more of the x and y components of at least one of voltage and current. Further, the method includes applying the one or more dynamic decoupling factors to current command calculation logic to mitigate a coupling effect of one or more current command components.