14 results about "Logical expression" patented technology

The application belongs to the technical field of natural language processing and knowledge graph, and discloses a kind of multi-modal acquisition and evolution graph analysis method and system of policy text. In view of the passive decision problem caused by the rigidity of existing policy analysis, semantic understanding and lack of dynamic correlation, the application adopts visual and DOM feature weighted fusion and reinforcement learning agent to realize multi-modal adaptive acquisition and joint alignment in anti-crawling environment;Use large language model for semantic deconstruction, and convert implicit logic into computer-readable explicit logic expression through thought chain reasoning;Construct a policy evolution knowledge graph with time and validity level attributes, perform satisfiability analysis to output conflict detection results;Map the target object portrait to the graph and the logic expression to evaluate item by item, and output intelligent decision deduction results combined with quantitative dimensions. The application realizes the whole life cycle intelligent analysis of policy data acquisition, deep logic analysis and active deduction.

This invention belongs to the field of enterprise resource planning (ERP) technology and discloses an intelligent matching method and system for policy application conditions based on enterprise resource analysis. By constructing a dedicated extraction model for policy application elements, it performs structured parsing and industry-customized four-level hierarchical decomposition of policy texts, transforming natural language application conditions into executable logical expressions. It accurately handles complex rules such as AND, OR, non-nested logic, numerical thresholds, and temporal constraints. A four-level progressive matching and verification mechanism is adopted, prioritizing matching according to the order of prohibition (one-vote veto), rigid access, core scoring, and auxiliary bonus points. It incorporates industry-specific rules and enterprise lifecycle adaptation logic to avoid invalid matching and screening biases, upgrading policy matching from superficial textual association to deep compliance verification, thus improving matching accuracy and adapting to the application and screening needs of various complex preferential policies for enterprises.

The application discloses a kind of automatic identification MOS tube gate circuit logic method, device and electronic equipment, the method includes the following steps: S1, check the source-drain sequence of all MOS devices in circuit, and adjust to flip the MOS device that does not comply with connection sequence therein;S2, check whether all pin attributes in circuit are correct, the pin attribute is divided into power supply / ground input pin, signal input pin, signal output pin;S3, calculate circuit diagram truth table: according to the switching characteristic of MOS tube, automatically calculate circuit diagram truth table;S4, truth table is converted into operation logic: call truth table conversion model, and truth table is converted into and or formula logic expression.The application automatically identifies the gate circuit logic formed by MOS tube under integrated circuit reverse analysis, by simulating the analysis logic of experienced engineer, quickly generates truth table to a large number of gate circuits and analyzes, reduces the time of manual analysis, reduces cost, improves the accuracy of circuit analysis.

This application provides an intelligent PPT generation method, apparatus, device, and storage medium, relating to the field of artificial intelligence technology. The method includes: performing multiple rounds of in-depth research content analysis based on pre-acquired in-depth research materials to generate an in-depth research report; inputting the in-depth research report into a domain fine-tuning model; combining the research scenario to perform logical reconstruction to obtain the reconstruction result; and based on the reconstruction result and the research scenario, matching the optimal layout template in a preset research scenario layout rule library to generate a first draft of the PPT. This method improves the understanding and adaptation capability of the logic of in-depth research content, ensures that the generated outline and content conform to academic / industry argumentation standards, achieves precise matching between layout design and research scenario, makes visual presentation serve logical expression, and, through deep integration of in-depth research and a large model, balances generation efficiency and quality while reducing manual intervention.

The application provides a variable entry-based document asset generation method and device and a medium. Non-entry documents are converted into entry documents including a plurality of entries with hierarchical relationships. Feature variables are set for the entry documents. Entries containing non-common content in the documents are marked as variable entries, and logical expressions composed of the feature variables are set for the variable entries. A document asset output template is created, and the feature variables are assigned values in the template. The value operation logical expressions in the template are applied, the variable entries are filtered according to the operation results, and the retained entries are combined to generate a document asset. When a variable entry is not provided with a logical expression, the sub-variable entries meeting the conditions of the variable entry are retained and promoted in title level. The application simplifies content structure reorganization, reduces configuration complexity, and realizes single data source management of content, thereby improving document maintenance efficiency and flexibility.

The present application provides a kind of function automatic generation method and system based on truth table, including: the scientific law that the relationship of each syntax symbol of logic expression in the problem based on truth table and their distance size in actual processing sequence are irrelevant, the generation semantic rule of logic expression is irrelevant with the result length of Boolean vector function example sampling, as the scientific basis for solving the problem of truth table function automatic generation.Besides, a kind of neural network model of encoder-decoder structure is designed to solve the problem of truth table function generation, the model uses two self-attention mechanism encoders to encode input and output respectively, and uses 1 self-attention mechanism decoder to output corresponding logic expression autoregressively, and uses attention mechanism between encoder and decoder;For solving the problem of truth table function automatic generation, a technical scheme is provided, which achieves better results on the specified data set compared with the mainstream benchmark model at the same period.

The application provides an assertion-oriented vulnerability detection method fusing a large model semantic reasoning, a dependency graph is constructed according to control and data dependency relationships and statements of an assertion, a slice graph related to the assertion is obtained by performing directional slicing according to the dependency graph, and path decomposition is performed on the slice graph to generate a key execution path; the key execution path is reasoned forward from an assertion failure condition according to a weakest precondition norm to obtain a target path constraint capable of triggering the assertion; the target path constraint is embedded in symbolic execution for solving and satisfaction verification is performed according to a solving process, and constraint generation is modified and re-reasoned according to a verification result; only control dependency and data dependency related to the assertion are reserved, and the path explosion problem of symbolic execution is solved; a path condition with semantic consistency is generated to avoid a semantic sensitivity problem; a semantic conclusion is mapped into a formal logic expression to ensure verifiability of a logical constraint; and the effect of explainability, verifiability and high accuracy is achieved.

An AI-based system and method for generating quantitative underwriting metrics based on risk assessment of a subject property is disclosed. The AI-based system includes a data obtaining subsystem to obtain visual data, environmental condition data, structured numerical data, and natural language instructions. A computer vision subsystem analyzes visual features to generate a curb appeal score and an interior quality score. A contextual data processing subsystem computes contextual indicators and temporal predictors to produce a contextual risk feature set. A rules interpreter subsystem converts natural language underwriting rules into executable logical expressions. A risk analysis subsystem integrates multi-modal data to generate a composite risk score and a corresponding confidence value. An underwriting metrics generating subsystem computes performance metrics, including predicted temporal performance and expected return parameters, to generate quantitative underwriting metrics and enable automated, data-driven underwriting decisions for the subject property.

This application provides a data processing method, data processing device, electronic device, medium, and product. The method is applied to the field of large-scale intelligent agent technology. The data processing method includes: logically parsing a target JSON text to obtain a Boolean logical expression of the target JSON text, where the Boolean logical expression includes the logical conditions of various business rules; simplifying the Boolean logical expression based on the logical conditions of M business rules to obtain a simplified logical expression; and removing duplicates from the simplified logical expression to obtain the target logical expression of the target JSON text. This method can effectively reduce the number of tokens processed by large models by preprocessing the JSON text, merging duplicate content, and simplifying the JSON text, thereby improving the inference speed of large models.

This invention provides a marketing plan generation method and system based on a multi-model combination. The marketing plan generation method includes: acquiring customer tag data and product data; using a pre-trained first model to perform business classification on the customer tag data and product data respectively, generating tag business label data and product business label data; using a pre-trained second model to generate the product-customer tag contribution between the customer tag data and product data; acquiring target product information, and combining the tag business label data, product business label data, and product-customer tag contribution to generate a tag logical expression; and using a pre-trained third model to generate a marketing plan based on the target product information and the tag logical expression. This invention achieves deep matching between customer tags and product features through a multi-model collaborative mechanism, improving the accuracy and automation level of marketing plans.

The application discloses a geographic space-time modeling method, system, product, equipment and storage medium for twin space virtual-real interaction, abstracts geographic entities, sensors, geographic data, geographic models, rule knowledge, geographic objects and controllers in twin space virtual-real interaction into corresponding nodes respectively, constructs edges connecting the nodes according to predefined logical relationships between the nodes, and generates a semantic and logical expression model for twin space virtual-real interaction; based on a graph database and the semantic and logical expression model, node storage files of the nodes and edge storage files of the edges are constructed; based on an object-relational database, an object storage table is constructed; through a geographic object identifier, an association between an object node in the graph database and a geographic object table record in the object-relational database is established, and the problem of element fragmentation and process breakpoint in existing virtual-real interaction modeling is solved.