29 results about "Logical relationship" patented technology

The invention relates to the technical field of engineering construction progress intelligent control, in particular to an engineering construction progress intelligent control method and system based on digital twinning, and the method comprises the steps: obtaining a preset plan logic relation set; acquiring a real-time process state set of the construction site; determining a plan failure index through real-time logic deviation calculation; in response to the plan failure index being greater than a preset failure determination threshold, determining that the plan fails and switching to a logic emergence mode; in response to the plan failure index being less than or equal to the failure determination threshold, maintaining the plan driving mode; deducing and generating an emergence logic set through emergence logic confidence calculation; determining a failure logic set; reconstructing to generate a hybrid logic model; the prediction completion time is deduced again; outputting a decision support signal; according to the method, the defect that a traditional system cannot judge the failure is overcome, the prediction accuracy is improved, and invalid warning out of reality is avoided.

The invention provides a software development system and method and a storage medium. The software development system comprises a process management module and a plurality of software development robots. The process management module is configured to obtain a development design document of to-be-developed target software according to a user instruction; and constructing a file tree according to a logical relationship among a plurality of development tasks recorded in the development design document, and creating a code file and a corresponding prompt word for a function node corresponding to each development task in the file tree. The cue word indicates the function content of the corresponding function node and the logical relationship between the cue word and other associated function nodes; and according to the function content of the at least one function node, determining a matched software development robot so as to enable the matched software development robot to execute the development process of the corresponding code file. The method can be used for autonomously arranging and managing the workflow of software development, so that the multiple robots are used for efficiently and collaboratively developing the software.

The invention discloses an aeronautical component heterogeneous data semantic mapping and logic conversion method and system, and relates to the technical field of aeronautical data processing.Multi-granularity candidates are generated by constructing unified intermediate representation and fusing accurate matching of a standard mapping table and fuzzy matching of an aeronautical field fine-tuning semantic embedding model; in combination with multi-dimensional features such as mapping confidence, semantic similarity and structural consistency, a combined decision is made through a fusion sorting model and a rule engine, and three types of results are output; unit standardization and dimension consistency verification is executed on the high-confidence result loading parameter logic relation graph, and incremental learning and versioning self-evolution of a semantic model, a mapping table and a PLG rule base are achieved based on manual feedback; and finally generating a standardized component parameter record and a complete auditing evidence chain. According to the method, high-reliability, traceable and self-evolution semantic alignment and logic verification of the aviation heterogeneous data are realized, and the data governance efficiency and the engineering credibility are remarkably improved.

The embodiment of the invention provides a multi-system access control method and device based on a dynamic intention, a storage medium and a program product. In the embodiment of the invention, the problem description information is received, a dynamic intention recognition model realized based on a large language model is utilized, the problem description information is converted into a mark sequence and is segmented through the guidance of a first cue word, and mixed intention recognition and mark fragment single intention recognition technologies are cooperatively applied to the sequence; generating a plurality of target sub-intentions fusing the two types of candidate sub-intentions and the probability distribution thereof; and further utilizing an access control model realized based on a large language model to guide and determine a target service system and an access path thereof through a second cue word, constructing a calling logic relationship, carrying out collaborative calling and result integration on the target service system in sequence, and finally generating and outputting target answer information. According to the method, the response efficiency of multi-system query is remarkably improved through an end-to-end model driving process, so that the user experience feeling is enhanced.

The application provides a kind of instruction driving machine task planning method and system based on knowledge model, and the specific knowledge of field is structuredly represented by knowledge model, and the object of class level, instance level of field knowledge and its logical relationship are represented;Further, the semantics of instruction is understood, and then the task planning problem represented by instruction is normalized, specifically including task planning object and its mutual constraint relationship;On this basis, further consider the space-time constraint between task objects and the measurement and evaluation of task efficiency.Finally, through atlas and visual graph display, give the pareto optimal scheme under multi-dimension, support intelligent or man-machine interactive decision, realize man-machine interaction in task planning, and output field-specific reliable scheme based on natural language.

The invention discloses an automatic script disassembling method and system based on reinforcement learning and AIGC, and relates to the technical field of document analysis, and the method comprises the steps: determining a to-be-disassembled task based on an input original script; based on the to-be-disassembled task, extracting information elements in the disassembling analysis process, and performing task tracing analysis on the information elements to form a task chain; obtaining a first result and a second result based on the to-be-disassembled task and task chain identification, importing the first result and the second result into a pre-constructed AIGC model, and outputting a disassembling scheme for the original script; wherein the disassembling scheme at least comprises an element structuring result and a logical relationship analysis result; the AIGC model is obtained by taking a first result and a second result of historical disassembly as a state space of reinforcement learning and introducing a residual block through multiple times of training optimization; according to the method, the automatic script disassembling quality is improved, and the large-scale and rapid processing of the script disassembling task is realized.

The application discloses a kind of microservice order processing system and method based on dynamic load balancing, it is related to the technical field of microservice, the system is applied to microservice architecture, system includes: event monitoring module, the instance lifecycle event stream of containerization management layer is monitored in real time, the logical relationship of microservice instance and the state attribute of the logical relationship are determined according to instance lifecycle event stream;Intelligent decision module is used to when receiving order task request: according to the real-time load index of microservice instance, determine candidate instance set;The microservice instance in replacement relationship and the state attribute for closing is removed from candidate instance set, obtain safe candidate instance set;Based on the real-time load index of each instance in safe candidate instance set, determine target microservice instance;Order task request and target microservice instance are sent to load balancing layer.The application improves the distribution ability of load balancer in microservice architecture to order task request.

The application discloses a question and answer result generation method and device, equipment, storage medium and product, relates to the technical field of data processing, and includes the following steps: when it is determined that the current intention of a user is a preset intention according to a current question and historical question and answer information, a large language model splits the current intention into multiple sub-intentions; an execution logic relationship between the sub-intentions and independent execution paths of the sub-intentions are generated; according to the execution logic relationship and the independent execution paths, at least one intelligent enhancement tool is called to determine sub-question and answer results meeting the sub-intentions; and a question and answer result corresponding to the current question is generated according to the sub-question and answer results. In the above manner, after the execution logic relationship and the independent execution paths are generated, the intelligent enhancement tool is called to determine the sub-question and answer results meeting the sub-intentions in a parallel manner, and then the question and answer result corresponding to the current question is generated, so that the efficiency and accuracy of generating the question and answer result can be effectively improved, and the experience of the user is improved.

This invention provides a control method, device, terminal, and storage medium based on a soft PLC. The method includes: acquiring a PLC logic diagram corresponding to the control logic; wherein the PLC logic diagram includes multiple logic modules and the logical relationships between each logic module; selecting logic elements corresponding to each logic module from a preset soft PLC component library; wherein the soft PLC component library contains multiple logic elements, each logic element implementing logical operations in the form of a soft PLC; and calling each logic element based on the logical relationships to obtain the soft PLC control quantity corresponding to the PLC logic diagram. This invention enables rapid soft PLC control without requiring customized code for the control logic, thus improving the efficiency of soft PLC development.

The invention provides a multi-subsystem joint test method for autonomous flight of a high-orbit satellite, and the method comprises the steps: building an integrated test system, analyzing the logic relation between a series event and a parallel event in the autonomous flight of the satellite, formulating a test strategy based on the time length of the event, an execution main body and a scheduling demand, and compiling a test detailed rule which can be automatically executed; and after initializing equipment and satellite states, executing all event tests according to detailed rules, compressing the time of long-time events by adjusting parameters, and recovering the initial state after the test is finished. Therefore, the verification of the satellite autonomous flight program and subsystem collaboration in a short time is realized, and the test efficiency is improved.

Embodiments of the present application disclose a test tool generation method and device, electronic equipment and a storage medium. The method comprises: determining various functional modules required by a target test tool to be created, and determining logical relationship information between the various functional modules; obtaining basic data and business data of the various functional modules; constructing the various functional modules based on the basic data and the business data of the various functional modules; and associating the various functional modules based on the logical relationship information to generate the target test tool. Embodiments of the present application template the construction process of the test tool, and relevant personnel provide the logical relationship information, the basic data and the business data of the various functional modules through configuration, input, selection and other operations, so that the construction of the test tool can be automatically implemented. The construction process no longer needs to be implemented through hard coding, and is convenient and fast. Changes in the test tool can be implemented by modifying configuration and input, so that the response speed and multi-scene coverage capability of test tool updating are improved.

The application relates to the technical field of interface development, in particular to a code generation method and device, equipment and medium, which are used for solving the problems of low development efficiency and difficult code maintenance of a traditional interface development scheme. The method comprises the following steps: in response to a code generation operation for a first control, calling a code generation tool corresponding to the first control, parsing a configuration file of a to-be-developed interface to obtain various fields contained in the configuration file and logical relationships between the various fields; and then generating a target file and a test file corresponding to the to-be-developed interface based on the various fields and the logical relationships between the various fields, wherein the target file comprises at least one of the configuration file and an application file of the to-be-developed interface. In this way, the development efficiency can be improved, the labor cost can be reduced, the front-end and back-end interface can be debugged in advance, the code format is consistent, and the code maintenance is facilitated.

The application discloses an automatic connection method and device between function blocks in an FBD program, comprising the following steps: in response to a first target event triggered in a connection pool of a visual window, obtaining a target function block to be connected according to the first target event; analyzing the target function block to obtain a function block ID number and pin information of the target function block; judging whether a network relationship file associated with the target function block is imported; if yes, adding a connection between a pin of the target function block and a pin of a determined associated function block according to a logical relationship determined in the network relationship file; if not, executing a preset connection rule configuration, and completing automatic connection between the target function block and pins of other function blocks in the connection pool according to the connection requirement configuration, the function block ID number and the pin information. The application saves the time for manually adding function block connections, improves the configuration operation efficiency, reduces the possibility of manual connection errors, and guarantees the correctness of control logic.

The invention relates to the technical field of fault detection, in particular to a teaching facility fault intelligent diagnosis method and device, a medium and a product. The method comprises the following steps: acquiring historical fault data; based on the historical fault data, determining a first logic relationship between fault types of the teaching facility and a second logic relationship between the fault types and fault causes; constructing a fault topological graph based on the first logical relationship and the second logical relationship; monitoring the working state of each teaching facility in the teaching scene in real time, and when the working state of any teaching facility is abnormal, positioning a source fault facility and a target fault reason of the source fault facility based on the fault topological graph; and formulating a fault removal strategy for the target fault reason, and executing the fault removal strategy until each teaching facility in the teaching scene works normally. According to the invention, source fault facilities and fault reasons can be quickly positioned.

A plurality of concepts is identified from utterances of a user of a service using a set of machine learning models. The plurality of concepts includes a primary concept representing an offering included in a catalog of the service, and a non-primary concept which provides additional information about the offering. A logical relationship is inferred among a pair of concepts using the set of machine learning models. A service order for the service is populated based at least in part on the relationship.

The invention discloses a task process display method and device, equipment, a medium and a program product, and aims to predict and display subsequent process nodes in a complex task process and improve user experience. The method comprises the steps of obtaining a task process; according to the task process, determining a logical relationship of process nodes contained in the task process, and predicting subsequent process nodes needing to be passed in the task process based on the logical relationship; and displaying subsequent process nodes needing to be passed in the task process.

The invention discloses an information processing method and device, equipment and a medium product, and the method comprises the steps: obtaining a plurality of pieces of progress record information of a sample media item, calling a language model to carry out summarization based on the plurality of pieces of progress record information of the sample media item, and obtaining an initial item progress summary; based on the time information and the execution progress described by each clause in the initial project progress summary, calibrating a plurality of clauses in the initial project progress summary to obtain a target project progress summary, a plurality of clauses in the target project progress summary are arranged according to a time sequence, and a logical relationship among execution progresses described by the plurality of clauses is matched with a logical relationship specified by a media production process, and performing model training on a language model by adopting the target project progress summary, the trained language model can generate the project progress summary of the corresponding media project based on the multiple pieces of progress record information of any media project, so that the generation efficiency and accuracy of the project progress summary are improved, and the labor cost is saved.

The application provides a shipping service-oriented time sequence event graph construction and application method and system. The method comprises the following steps: acquiring shipping information for unique verification and adaptive blocking; identifying core events and associated entities in the blocked text, and constructing a graph topology network containing logical relationships such as co-reference, causality and time sequence; performing knowledge fusion based on semantic alignment to eliminate knowledge base redundancy; constructing a multi-level fact traceability index storage architecture composed of original text, blocks and entity mapping; in response to a query instruction, generating a double-layer keyword and performing three-way concurrent collaborative recall of entities, relationships and blocks, and generating an analysis report after context rearrangement. The application upgrades the static graph to a dynamic time sequence event graph, realizes dynamic evolution reasoning of shipping events, and effectively overcomes the 'illusion' problem of large language model generated intelligence through a multi-level traceability association mechanism.

The embodiment of the invention provides a script definition-based business process, business function and operation and maintenance system control method and related equipment, and the method comprises the steps of constructing a plurality of step types in one-to-one correspondence with different operation processes according to the executed different operation processes; performing feature extraction on the logic relationship of the plurality of step types in the business process, and determining the common attribute of the plurality of step types; performing script content compiling on the plurality of step types based on common attributes to form step type script fragments; performing business logic analysis on the business process to obtain a process step chain; the process step chain comprises a plurality of steps arranged according to a business logic sequence, and each step corresponds to a step type script fragment; performing attribute assignment on each step type script fragment in the process step chain to form a business process script block; the method has the beneficial effects of high flexibility and high expansibility, and is suitable for the technical field of equipment operation and maintenance.

This invention discloses a method, system, and equipment for compiling a comprehensive construction schedule, belonging to the field of pumped storage power station construction schedules. The method replaces the cumbersome process of manually setting logical relationships by establishing a template library for the comprehensive construction schedule of pumped storage power stations, based on the logical relationships between construction procedures and processes, and between individual buildings. This method provides users with a reference during operation, is simple and easy to learn, greatly improves the work efficiency of schedule designers, and enables the rapid compilation of comprehensive construction schedules and the rapid generation of related charts.

The invention discloses a multifunctional engine arrangement method and device, equipment, a storage medium and a product, and relates to the technical field of data processing.The multifunctional engine arrangement method comprises the steps that when a task execution request is received, the number of engines needing to be called for task execution is determined according to the task execution request; when the number is greater than a preset threshold value, determining engine arrangement objects required for realizing the engine functions and an execution logic relationship among the engine functions; obtaining an arrangement rule of the engine arrangement object; engine arrangement is carried out according to the engine arrangement object based on the arrangement rule and the execution logic relation; by means of the mode, when it is determined that the number of the engines needing to be called for task execution is larger than the preset threshold value, it is indicated that multiple engine functions need to be used, and at the moment, the multifunctional engine is arranged through the engine arrangement objects needed for achieving the engine functions and the execution logic relation between the engine functions, so that the engine calling requirement is met; therefore, the task execution efficiency can be effectively improved.

The invention discloses a logical relation graph generation method and device, equipment and a medium. The method comprises the following steps: establishing a plurality of relational graph templates, and setting use conditions of each relational graph template; matching a target relational graph template according to the relational graph demand list of the project, the equipment type in the project, the number of each equipment instance and the use condition of each relational graph template; and instantiating the target relation graph template to generate a logical relation graph of the project. By adopting the technical scheme, the relation graph template can be matched according to the quantity of the equipment instances in the project, so that when the quantity levels of the equipment instances of the project are different, the logical relation graphs in different expression forms are generated, and the adaptability and readability of the logical relation graphs are improved.

The invention discloses an information processing method and device based on a collaborative whiteboard and a storage medium, and the method comprises the steps: obtaining a first text content comprising a plurality of first content main bodies in a first online document in response to the import of the first online document, and carrying out the logic relation extraction of the first text content, obtaining logical relationship description information for describing a first logical relationship among the plurality of first content main bodies, and then performing information conversion processing on the logical relationship description information to obtain first embedded object information; the method comprises the following steps: receiving first embedded object information, generating a plurality of first whiteboard elements having a second logical relationship consistent with a first logical relationship according to the first embedded object information, the first whiteboard elements corresponding to a first content main body, and then displaying the plurality of first whiteboard elements and the second logical relationship among the plurality of first whiteboard elements in a collaboration whiteboard. By importing the online document, the collaborative whiteboard automatically displays the logical relationship contained in the online document, so that the use experience of a user can be effectively improved.

The invention discloses a micro-service work order processing system and method based on dynamic load balancing, and relates to the technical field of micro-services, the system is applied to a micro-service architecture, and the system comprises an event monitoring module for monitoring an instance life cycle event flow of a containerized management layer in real time, and sending the event flow to a server; determining a logic relationship of the micro-service instance and a state attribute of the logic relationship according to the instance life cycle event stream; the intelligent decision module is used for determining a candidate instance set according to the real-time load indexes of the micro-service instances when a work order task request is received; removing the micro-service instances which are in the replacement relationship and have closed state attributes from the candidate instance set to obtain a security candidate instance set; determining a target micro-service instance based on the real-time load index of each instance in the security candidate instance set; and sending the work order task request and the target micro-service instance to a load balancing layer. According to the invention, the allocation capability of the load balancer to the work order task request in the micro-service architecture is improved.

The application discloses a task processing method and device based on fine-tuning of a large language model, equipment and a medium. The method comprises the following steps: based on a constructed training data set, a context-aware fine-tuning algorithm is trained by using a multi-task parallel scheduling strategy; wherein the context-aware fine-tuning algorithm is based on the LoRA parameter fine-tuning between tasks; based on the context-aware fine-tuning algorithm, a fine-tuned large language model is obtained; and multi-modal data of a target task is input into the large language model for processing, and a task processing result is output. The application proposes a LoRA fine-tuning method based on task dependency, which is called a context-aware fine-tuning algorithm, guides the model to learn the implicit causal logical relationship between tasks, improves the adaptability and generalization ability of the model to complex reasoning tasks, supports a distributed collaborative processing mode, significantly improves the model deployment efficiency and response speed, and adapts to the edge deployment requirements of low latency and low power consumption.

The invention discloses a task processing method and device based on a fine-tuning large language model, equipment and a medium. The method comprises the following steps: training a context-aware fine-tuning algorithm by adopting a multi-task parallel scheduling strategy based on a constructed training data set; wherein the context-aware fine tuning algorithm performs LoRA parameter fine tuning based on a dependency relationship between tasks; obtaining a fine-tuned large language model based on the context-aware fine-tuning algorithm; and inputting multi-modal data of a target task into the large language model for processing, and outputting a task processing result. The invention provides a LoRA fine tuning method based on a task dependency relationship, which is called a context-aware fine tuning algorithm, guides a model to learn an implicit causal logical relationship between tasks, improves the adaptability and generalization ability of the model to a complex reasoning task, supports a distributed cooperative processing mode, remarkably improves the model deployment efficiency and response speed, and improves the robustness of the model. And the method is suitable for low-delay and low-power-consumption edge deployment requirements.

A plurality of concepts is identified from utterances of a user of a service using a set of machine learning models. The plurality of concepts includes a primary concept representing an offering included in a catalog of the service, and a non-primary concept which provides additional information about the offering. A logical relationship is inferred among a pair of concepts using the set of machine learning models. A service order for the service is populated based at least in part on the relationship.

This invention discloses a method for generating ladder diagrams for programmable controllers based on a large language model, belonging to the field of programmable controller technology. It uses a first large language model to structure the logical control requirements, including I / O inputs, control logic relationships, and I / O outputs, described in natural language. The generated structured logical control requirements are then processed by a pre-trained base large language model to obtain an I / O allocation table and intermediate IL (Intermediate Language) code. The I / O allocation table represents variable information and is converted into a first element in a specific format. The intermediate IL code is logical control information organized based on the variables in the I / O allocation table. The association relationships of ladder diagram controls represented by an Object-Oriented View (AOV) network are generated by traversing the intermediate IL code, and the relative position information of the ladder diagram controls is injected during the generation process. The AOV network is then traversed to generate a second element in a specific format. The first and second elements are merged and assembled to form a file of the target ladder diagram code in a specific format.

This invention provides a method, apparatus, device, and medium for personalized configuration of delivery confirmation methods, including: constructing a multi-dimensional attribute library for packages; extracting package attributes corresponding to a target package based on the constructed multi-dimensional attribute library; constructing a feature vector for the target package based on the package attributes of the target package and the logical relationships between the attributes; and completing intelligent matching and decision-making of delivery confirmation rules based on the feature vector of the target package, combined with the global attribute weights corresponding to each package attribute of the target package and a digital delivery confirmation rule library. This invention addresses industry pain points such as rigid processes, insufficient intelligence, significant system performance shortcomings, and poor adaptability to complex scenarios in traditional logistics delivery confirmation models. Through a complete technical system encompassing multi-dimensional attribute modeling, weighted intelligent matching, LLM for complex scenarios, high-frequency rule caching, and high-concurrency traffic control, it achieves precise personalized configuration of delivery confirmation methods and efficient and stable system operation.