129 results about "Logical tree" patented technology

The invention provides an unmanned aerial vehicle countering plan generation method and system based on an artificial intelligence technology, and the method comprises the steps: analyzing the dynamic monitoring data flow of a target unmanned aerial vehicle, recognizing the flight path characteristics and electromagnetic signal frequency spectrum of the target unmanned aerial vehicle, and constructing a three-dimensional space threat situation model to evaluate the threat level. Decomposing behavior patterns and attack intention parameters of a target unmanned aerial vehicle based on threat levels, generating a dynamic decision factor set in combination with geo-fence constraint conditions and environmental interference factors, generating a plurality of candidate countering plans by matching countering means basic plans in a plan knowledge graph, and constructing a plan logic tree; a multi-dimensional evaluation parameter set is generated based on a three-dimensional space threat situation model, a dynamic decision factor set and a countering efficiency index, collaborative optimization processing is performed on a plan logic tree, an optimal countering plan is generated and converted into an executable instruction set, the executable instruction set is synchronized to a countering device for execution, and the real-time performance and scene adaptability of the unmanned aerial vehicle countering plan are improved.

The invention discloses a text robot application system based on a large model, and the system comprises the following modules: a knowledge base and analysis module which receives and processes a business document, decomposes the content into semantic units, and marks context features; the question-answer generation module automatically generates question-answer pairs through deep semantic analysis and stores the question-answer pairs in a vector database; the question extension module is used for dynamically extending similar questions by using a natural language generation technology; the semantic intention analysis module is used for accurately extracting a problem core intention through context semantic analysis and mapping the problem core intention to a service path; the text workflow management module is used for realizing dynamic routing of multiple service scenes by adopting a logic tree model; the context semantic association module is used for analyzing and optimizing problem expression through multiple rounds of dialogues; the bottom response module is used for providing multi-level answers in combination with a question and answer database, document recall and dynamic generation; and the intelligent learning module records unsolved problems and optimizes the question and answer library and semantic rules through a learning algorithm.

Systems, devices, and methods are disclosed herein of an artificial intelligence-powered contextual customer service automation solution using logic trees enhanced with the mission and corporate values-based generative AI prompts to control responses with brand characteristics and tone.

The invention relates to an enhanced LLM-RAG multi-hop question and answer method based on logic tree reasoning, and belongs to the technical field of new-generation information, and the method comprises the following steps: inputting a multi-hop question and answer question into a computer system; the computer system calls a pre-training large language model LLM, the multi-hop question-answer question is decomposed into a hierarchical logic tree in a recursive mode, and each node of the logic tree comprises a sub-question and a corresponding hypothesis answer; performing image retrieval from a structured knowledge source Wikidata and performing text retrieval from an unstructured knowledge source Wikipedia on the basis of each node sub-question and the hypothesis answer to obtain corresponding evidence; traversing the logic tree, verifying the consistency between the hypothetical answer of each node and the evidence through LLM, if the contradiction exists, reconstructing the corresponding sub-tree, and dynamically correcting the reasoning path; and integrating the verified logic tree node information, and outputting an accurate answer to the multi-hop question and answer question.

The invention discloses a voice interactive console based on artificial intelligence, and relates to the technical field of intelligent consoles, a large language model is combined with context tracking and logic analysis technologies, a composite instruction is disassembled into independent tasks, a task chain is generated, a semantic weight is added to each task through a weight regression model, and the intelligent consoles are obtained. The task execution priority and the logic dependency relationship are identified, the limitation of a traditional system on the complex semantic analysis capability is overcome, a composite instruction can be accurately understood, a logic tree analysis method based on rules is adopted, a task chain is converted into a directed graph structure, the priority is dynamically adjusted, and a task execution sequence table is generated. In the scheduling process, multi-task parallel processing is carried out on tasks without logic dependence, and the resource utilization rate is increased; tasks with a dependency relationship are gradually scheduled by adopting topological sorting, so that the logic consistency is ensured.

The invention discloses a big language model logical reasoning method, device and equipment, a storage medium and a product, and relates to the technical field of big language models.The method comprises the steps that a logical reasoning tree is constructed according to a preset problem, an intermediate step generated by a logic big language model and a reasoning path; alternately training the logic big language model and the logic tree scoring model to obtain a trained logic big language model and a trained logic tree scoring model; and according to the trained logic tree scoring model, evaluating a plurality of next-step reasoning paths generated by the trained logic big language model according to the logic reasoning tree to obtain an optimal reasoning path. According to the method, the training logic tree scoring model is used for replacing an existing prompt large model scoring strategy, a prompt or a high-level large language large model does not need to be preset in the scoring process, and the logic tree scoring model and the logic large model are alternately trained, so that the accuracy of model reasoning is improved in the face of complex problems.

The invention provides a multi-variety assembly production line reconfigurable switching method and system based on digital twinning. The method comprises the steps that the dynamic mapping relation between the variety of a product to be produced and assembly steps is achieved through a reconfigurable logic tree model; feature parameters of the to-be-produced product are obtained through visual identification or order data analysis; importing the reconfigurable logic tree model into a digital twin system, fusing actual production data to dynamically reconstruct an assembly model, and optimizing an assembly path through simulation rehearsal; automatically generating an executable assembly control program according to the rehearsal result; and issuing the executable assembly control program to a production field to execute actual switching, and feeding back closed-loop adjustment through real-time data. According to the invention, the production line switching efficiency and the flexibility level can be improved, and the human resource consumption is reduced.

Techniques are described with regard to container image configuration in a computing environment. An associated computer-implemented method includes initializing a container image storage engine associated with a logical tree structure having a plurality of container image nodes, where each of the plurality of container image nodes includes a hash layer array and a hash data array. The method includes building at least one new container image node to incorporate into the plurality of container image nodes. The method further includes applying a software patch to a target container image node among the plurality of container image nodes. In an embodiment, the method further includes starting at least one container based upon a respective container image node among the plurality of container image nodes.

The invention relates to the field of computers, and provides a logic tree establishing method, network node equipment, computing node equipment and a system, and the method comprises the steps that first network node equipment acquires a first tree establishing request initiated by first computing node equipment in a plurality of pieces of computing node equipment; the first network node equipment updates a value of a tree building request counter corresponding to the first logic tree in a tree building information table according to the first tree building request; and the first network node equipment determines a tree building result according to the tree building request counter and a first threshold value. According to the method, the computing node equipment at the end side initiates the tree building request, the structure information of the nodes on the branch of the logic tree where the computing node equipment is located is carried in the tree building request, and the network node equipment counts the number of the tree building requests aggregated by the corresponding nodes in the logic tree, so that the influence of a single-point fault is reduced; and the reliability of establishing the logic tree by the distributed computing cluster is improved.

Techniques are described with regard to container image configuration in a computing environment. An associated computer-implemented method includes initializing a container image storage engine associated with a logical tree structure having a plurality of container image nodes, where each of the plurality of container image nodes includes a hash layer array and a hash data array. The method includes building at least one new container image node to incorporate into the plurality of container image nodes. The method further includes applying a software patch to a target container image node among the plurality of container image nodes. In an embodiment, the method further includes starting at least one container based upon a respective container image node among the plurality of container image nodes.

The invention relates to the technical field of semantic analysis, can be applied to business system platforms of financial science and technology, medical health and the like, and discloses a business process analysis method, device and equipment based on a natural language and a medium. Generating a target logic tree corresponding to the natural language instruction; converting the logic structure in the target logic tree into a structured code, and performing grammar verification on the structured code; correcting the structured codes which do not pass the grammar verification, and performing rendering operation on the target structured codes to obtain a visual flow chart; adjusting the visual flow chart, and updating the structured code based on the adjusted visual flow chart; and when the visual flow chart meets the flow demand of the target user, outputting a target flow chart corresponding to the natural language instruction, and performing business flow analysis on the natural language instruction by using the target flow chart. And the efficiency of business process analysis is improved.

The invention relates to the field of programmable logic controller programming software, in particular to a method for converting a ladder diagram of a PLC into an instruction list, which comprises the following steps of: obtaining a mapped AOV diagram by adopting a mode of adding and deleting virtual nodes; generating a logic tree by adopting a series-parallel scanning method of dynamic priority; and after the logic tree structure is obtained, performing subsequent traversal on the logic tree according to the logic relationship described by the logic tree to generate an instruction table structure. Compared with the prior art, a complex ladder diagram is greatly simplified through a preprocessing mechanism, the scanning steps of continuous series connection or continuous parallel connection original parts can be reduced, unnecessary node scanning can be fully reduced through dynamic priority series-parallel connection scanning, and the scanning efficiency is greatly improved; in addition, the method can be widely applied to a complex ladder diagram program in the PLC, and the series-parallel scanning efficiency can be greatly improved.

The invention discloses a condition analysis execution method and device based on dynamic configuration and computer equipment. The method comprises the following steps: acquiring a condition expression and corresponding data; constructing a logic tree structure; traversing condition items; judging whether the condition item is a leaf node or not; if yes, inquiring an operator registration library to determine whether an operator exists or not; if yes, executing an operation method, and performing type self-adaptive processing to obtain a Boolean result; recording Boolean results; judging whether the current condition item is the last condition item or not; if yes, applying root logic to output a result; if not, performing exception handling; and if the condition item is not the leaf node, recursively processing the sub-conditions, aggregating results obtained by processing to obtain a Boolean result, and recording the Boolean result. By implementing the method provided by the invention, flexible and easy-to-maintain condition processing capability can be provided, and the problems of framework rigidity, high maintenance cost, function limitation and the like in the prior art are effectively solved.

The present application relates to the technical field of computers, and in particular to a fault root cause locating method, a fault root cause positioning system implementing the method, and a computer-readable storage medium and a computer program product. The method comprises: acquiring an architecture topology graph and abnormal alarm information of an application system; on the basis of the architecture topology graph and the abnormal alarm information, constructing a troubleshooting logical tree, wherein in the troubleshooting logical tree, a logical relationship between nodes is used to indicate a potential fault propagation link between configuration components in the architecture topology graph; performing qualitative analysis on the troubleshooting logical tree, so as to identify a potential fault point that causes a fault; performing quantitative analysis on the troubleshooting logical tree, so as to calculate a fault probability and the degree of influence of each potential fault point; and on the basis of results of the qualitative analysis and the quantitative analysis, determining a root cause fault point, and acquiring a fault propagation link of the root cause fault point.

The invention discloses a multi-mode complex event detection and optimization method for semi-structured data, and relates to the field of data stream processing. According to the method, mode matching of the semi-structured data is realized by using a multi-mode normal tree. In order to enable a regular tree mode to be matched with a semi-structured data stream, the patent adopts a method of disassembling the regular tree mode into two parts, namely a tree mode and a regular mode, and realizing matching step by step. The tree mode designs a node relationship in which a user is interested into a logic tree, and a TwigList algorithm is used for matching data meeting conditions in a data stream and storing the data. The regular pattern defines a behavior sequence in which a user is interested, and state transition is realized by using NFA. And carrying out NFA processing on the data stream which is successfully matched with the tree pattern to obtain a final result.

The present invention discloses a probabilistic landslide tsunami disaster assessment method, device, and medium based on a logic tree, including: obtaining landslide data corresponding to the area to be detected; constructing a probabilistic landslide scenario set based on the logic tree method and deriving the geometric parameters of the landslide scenario; the first-level, second-level, third-level, and fourth-level nodes in the logic tree are landslide location, landslide volume, tsunami arrival point, and tsunami wave height; obtaining historical landslide tsunami records and submarine topography data of the area to be detected, and calculating the initial water level field of the tsunami wave through a first tsunami propagation numerical model according to the landslide location and volume in the probabilistic landslide scenario set; performing simulation using a second tsunami propagation numerical model based on the initial water level field of the tsunami wave to obtain the propagation path, maximum wave amplitude, and influence range of the tsunami; estimating the spatial probability of potential landslides in the area to be detected, the annual occurrence probability of landslides in each volume interval, and the probability that the maximum wave amplitude of the triggered tsunami does not exceed the tsunami wave height threshold at the tsunami arrival point.

The invention discloses a call recording quality inspection method and system based on a logic expression, and relates to the field of call quality inspection, and the method comprises the steps: receiving a logic expression and a call recording text inputted by a user; logic operators in the logic expression are extracted, and operation logic of the logic operators is determined; when it is detected that the customized operator exists in the logic expression, obtaining a detection logic setting of the customized operator in a customized logic database, and determining a customized logic of the customized operator based on the detection logic setting; determining a detection logic tree corresponding to the call recording text; traversing all leaf nodes of the detection logic tree, and determining a node calculation result of the call recording text at the leaf nodes; determining an output result of the detection logic tree at the root node; and according to the logic expression, the call recording text and the output result, generating a recording quality inspection report. By implementing the method, a complex language mode can be identified and processed more accurately, and errors in call recording quality inspection can be avoided to a greater extent.

In some implementations, a memory apparatus may receive a command indicating a logical block address (LBA) that is associated with a logical-to-physical (L2P) table. The memory apparatus may perform a lookup operation associated with a compressed version of an address range of the L2P table to identify a physical address in non-volatile memory associated with the LBA, wherein the compressed version is stored in a volatile memory of the memory apparatus, wherein the compressed version is associated with an exception list that indicates physical addresses for respective LBAs, included in the address range, that are associated with non-sequential physical addresses, and wherein the compressed version is associated with a binary tree that indicates locations in the exception list associated with the respective LBAs. The memory apparatus may perform, based on the command, an action associated with the physical address.

The invention provides a visual logic execution system and method based on logic block nesting and JSON (JavaScript Object Notation) dynamic configuration, and the system comprises a front-end visual editing module which is used for providing a logic block library and a nested canvas editor, receiving the dragging and nesting operation of a user based on a logic block, and storing the dragging and nesting operation in the front-end visual editing module; serializing the finally edited nested logic tree structure into JSON (JavaScript Object Notation) configuration data; the back-end dynamic analysis execution module is used for receiving and persisting the JSON configuration data, constructing an executable object tree isomorphic to the nested logic tree structure by dynamically analyzing the JSON configuration data, and executing the executable object tree to run logic edited by a user; and the front-end visual editing module communicates with the rear-end dynamic analysis execution module through a data transmission interface. The front end and the rear end are coupled through the JSON interface, and the front end and the rear end can be independently upgraded and expanded.

This invention relates to the fields of computer data processing and network communication technology, specifically to a method and system for real-time synchronization of paperless interactive information across multiple terminals. The method includes: a logic construction step: acquiring the original interactive command stream, constructing a semantic causal logic tree based on a vector clock, and dividing strong barriers and weak streaming events; a backpressure monitoring step: establishing a rendering backpressure model to calculate the rendering backpressure value of the target terminal; a dynamic shaping step: responding to a backpressure value exceeding a threshold, reducing the dimensionality of the command stream and reorganizing its timing, attaching weak streaming events to strong barrier events and merging them into an atomic state snapshot for transmission; and a consistency verification step: comparing the screen content-aware hash value, and if a mismatch occurs, performing full state synchronization. This invention solves the problem of visual semantic confusion caused by differences in rendering capabilities between heterogeneous terminals.

Provided is a storage device that has a computation function and comprises: a plurality of differential logic tree cells; a plurality of digital differential sense amplifiers for respectively reading the computation results of the plurality of differential logic tree cells; a plurality of write circuits for writing data to each of the plurality of differential logic tree cells; and a digital computation circuit for performing computations by using the computation results from the plurality of digital differential sense amplifiers. Each differential logic tree cell includes: a memory cell which includes first and second magnetic storage elements for storing the data based on a change in a resistance value; and a differential logic circuit for performing logical computations by using the data stored in the memory cell and external data input from the outside.

The invention discloses a vehicle dynamics modeling method based on a logic tree, and relates to the technical field of automobile electronic control, a model to be inspected and tested is selected from an ECU end and a software development platform, the position / working path of the model is determined, and the relative position of the position of the model in the whole model is determined; the model is converted into a logic tree, after a tree structure is generated, execution logic with missing coverage is sorted based on the tree structure, an automatic test framework based on the tree structure is generated, and errors are rapidly positioned and maintained; finally, the model is copied to the vehicle-mounted ECU or the software development platform again, and updating of the test and inspection model is completed. According to the method, the logic and the content of the model are simply described through a graphical tree structure, the node can be directly described according to the model, the execution logic of the model can also be viewed from a code tree, the system is modularized, and a clear interface is displayed, so that the complexity is reduced and the maintainability is improved.

The present application relates to the technical field of clinical trial data analysis, and particularly relates to a clinical trial compiling method and system based on semantic rules and logic trees, comprising: obtaining a clinical trial standard original text, determining inclusion criteria and exclusion criteria; marking an unsplit unit corresponding to a count aggregation relationship and a condition obligation relationship; obtaining a candidate condition unit by dividing the text into sentences, determining a combination relationship type between the candidate condition units in combination with a conjunction word and the unsplit unit; performing semantic rule compiling on the candidate condition units to generate a semantic rule configuration; constructing a logic tree with the candidate combination structure as a skeleton, with leaf nodes corresponding to the semantic rule configuration, intermediate nodes corresponding to the combination relationship type, and a three-value evaluation rule and a three-layer fingerprint being configured; and performing feasible domain verification on parts with the same constraint object in the inclusion criteria and the exclusion criteria to obtain a compiling product. The present application makes the analysis result consistent with the combination constraint expressed in the standard original text, and reduces analysis deviation caused by combination relationship misjudgment.

The invention discloses a data operation auditing method and device for a background database, equipment and a medium, and relates to the field of computers.The data operation auditing method comprises the steps that key operation elements are extracted through a preset entity recognition channel, and a target structured logic tree is generated based on the key operation elements through a preset logic reasoning channel, converting the target structured logic tree into a target standard approval template; determining a target strategy knowledge graph based on a preset business approval strategy and a preset data security auditing rule, and identifying abnormal key operation elements according to the target strategy knowledge graph; obtaining a first abstract syntax tree and a second abstract syntax tree, determining a target editing distance, and generating a target difference analysis report based on the target editing distance; and constructing an operation log auditing detection framework according to a preset dimension, and determining an auditing result of the target data operation approval work order by utilizing the operation log auditing detection framework based on the operation log data, the abnormal key operation elements and the target difference analysis report. And the approval and auditing efficiency and accuracy are improved.

This invention relates to the field of artificial intelligence decision-making technology, specifically to an intelligent decision-making system and method based on a large model. The system includes: receiving raw decision request streams from heterogeneous business sources; performing semantic normalization and knowledge enhancement processing on these streams to generate a structured decision query containing a core problem statement, key fact triples, and a knowledge index; invoking a large language model inference engine to generate a preliminary decision reasoning chain based on the structured query; using a predefined decision logic constraint graph to perform consistency verification and completion of the reasoning chain, generating a verified complete decision logic tree; and performing pattern matching in an executable atomic operation library based on the logic tree to map and assemble an executable decision action plan. This invention improves the understanding accuracy, reasoning reliability, and decision executability of large models in complex decision-making scenarios through structured query input and external logic verification.

The invention discloses a method and a device for testing an automobile software unit by a tree structure, and relates to the technical field of automobile software unit testing, the method for testing the automobile software unit by the tree structure comprises the following steps: step 1, modeling by a logic tree Stateflow; step 2, carrying out an overall logic process of modeling from a logic tree Stateflow; step 3, generating a logic flow of the analysis logic tree of Stateflow from the logic tree; step 4, generating a method for calibrating the position of each node of Stateflow from the logic tree; in the first step, the positions where all juctions of the Stateflow are created are standardized through a method of calculating child nodes and characters. According to the method for realizing Stateflow modeling through the logic tree, the logic tree can be firstly combed, and then the Stateflow model is generated from the logic tree, so that logic errors can be avoided, the logic check time is saved, logic and writing specific execution are distinguished, the maintainability of the model can be ensured, and new members do not need very mature writing ability.

In a scheme for generating process prompt statements provided by this application, this scheme adopts a method combining a finite state machine and a logical inference graph. That is, it uses a finite state machine representation to manage the process state nodes in the scenario, and uses a logical inference graph formed by a logical tree to control the generation of process prompt statements and the switching of process state nodes. For the court trial scenario, different case types can be adapted by flexibly configuring the states included in the finite state machine and the template nodes in the logical tree. Therefore, the workload for different case types can be reduced, and the generality is good.

The present application relates to an enhanced LLM-RAG multi-hop question and answer method based on logical tree reasoning, belonging to the field of new generation information technology, comprising the following steps: inputting a multi-hop question and answer problem into a computer system; the computer system calls a pre-trained large language model LLM, recursively decomposes the multi-hop question and answer problem into a hierarchical logical tree, each node of the logical tree contains a sub-problem and a corresponding assumed answer; based on the sub-problem and the assumed answer of each node, image retrieval is performed from a structured knowledge source Wikidata, and text retrieval is performed from an unstructured knowledge source Wikipedia, to obtain corresponding evidence; traversing the logical tree, verifying the consistency of the assumed answer and the evidence of each node through the LLM, if there is a contradiction, reconstructing the corresponding sub-tree and dynamically modifying the reasoning path; integrating the node information of the verified logical tree, and outputting the accurate answer of the multi-hop question and answer problem.

The invention discloses an invalid operation prompting method and device, a storage medium and a system. The method comprises the following steps: acquiring and identifying an operation signal of an equipment operator; retrieving a logic tree associated with the operation signal; wherein the operation signal is associated with at least one logic tree; based on each logic tree, retrieving whether a preset condition allowing response to the operation signal is established or not; if the preset condition is not established, based on a corresponding logic tree, searching out a limiting root cause corresponding to the preset condition which is not established; and sending the restriction root cause code to an information prompting unit, so that the information prompting unit prompts the restriction root cause code. According to the technical scheme, the limiting root cause can be actively recognized and prompted, the experience requirement for troubleshooting response abnormity of an operator is lowered, and normal operation of equipment is guaranteed.

A blockchain data storage method includes: obtaining key-value pairs of blockchain data to be stored; converting the key-value pairs of the blockchain data into root nodes, intermediate nodes, and leaf nodes on a logical tree structure; the nodes on the logical tree structure are linked to the nodes on the upper layer via their hash values; the storage content of the nodes on the logical tree structure includes the hash value of the node on the lower layer linked to the node and the database identifier of the database storing the node on the lower layer; the root node and the intermediate node are used to store the characters in the key of the key-value pair corresponding to the blockchain data; the leaf node is used to store the value of the key-value pair corresponding to the blockchain data; the root node, the intermediate node, and the leaf node are respectively stored in a database; and the nodes on the logical tree structure are respectively stored in at least multiple databases.