7results about How to "Guaranteed execution efficiency" patented technology

The invention provides a business process intelligent configuration and security execution method, system and device, and the method comprises the steps: converting a natural language demand into a BPMN 2.0 process model based on a large language model and an enterprise knowledge base; the service rule description is converted into a Grouping script through multi-level security compiling; the process and the script are executed in the Flowable process engine integrated with the security sandbox, and execution data are collected; and calculating a process health score based on the data, generating and implementing an optimization suggestion, and feeding back a result to the knowledge base. The problems that a traditional process system depends on manual coding, the script safety is poor, and continuous optimization is lacked can be solved. The full-link automation and intelligentization of the business process from design, execution to optimization can be realized, the development efficiency and the system security are greatly improved, and the process has the self-evolution capability through closed-loop feedback.

The invention discloses a fire station regional rescue system, which relates to the technical field of fire emergency rescue, and comprises a data acquisition module for acquiring a fire station resource state and jurisdiction alarm information; the model updating module analyzes the alarm information and generates a structured event vector so as to dynamically update the digital twin data model; the scheme generation module is used for generating a recommendation scheme containing a predicted dynamic combination, a route and time through calculation of an optimization engine on the basis of real-time resources and the updated model; the instruction confirmation module generates an action instruction set containing elastic parameters according to the confirmation scheme and issues the action instruction set to the terminal, and the terminal autonomously plans a microscopic path based on the parameters and local environment data; the data actual measurement module collects action actual measurement data; and the feedback adjustment module calculates the deviation between the actually measured data and the predicted data and adjusts the parameters of the digital twin model according to the deviation. According to the method, dynamic optimization decision, terminal elastic execution and model closed-loop self-learning are realized, and the accuracy, adaptability and overall efficiency of rescue response are improved.

The invention belongs to the technical field of water conservancy projects, and provides a dam mass data distributed processing method based on a cloud computing architecture, which comprises the following steps: S1, performing unified access and standardized description on multi-source heterogeneous dam monitoring data, and generating a structured data object with a spatio-temporal index; s2, performing adaptive data fragmentation and distributed storage optimization based on space-time attributes and access features of the data objects; s3, according to the characteristics and resource requirements of the computing tasks, constructing a dynamic extensible parallel computing workflow; s4, in the process of executing the parallel computing workflow, implementing resource flexible scheduling and task migration based on load feedback; and S5, performing multi-dimensional aggregation on the processing result, and feeding back to the data storage layer.

The invention relates to the technical field of computers, in particular to a production scheduling optimization method and system based on a dynamic algorithm engine, and the system comprises a data processing module which comprises a preprocessing unit used for preprocessing collected order basic data to output order features; the scheduling solving module comprises a function construction unit used for constructing a scheduling optimization objective function; the disturbance recalculation module comprises an evaluation unit used for determining an influence domain of scheduling execution abnormity according to real-time industrial production resource constraints; the schedule judgment module is used for determining whether the stability of the production schedule meets the requirement or not according to the fluctuation characterization value; the delay adjusting module is used for determining a transmission delay coefficient between scheduling processes according to the updating frequency of the recalculation scheduling scheme; and the penalty factor adjusting module is used for determining the dynamic load penalty factor of the high-load equipment in the scheduling optimization objective function solution according to the conflict rate of the production resources in the production scheduling plan. According to the invention, the stability of production scheduling is improved.

The invention provides an inter-system integration method and device based on configured zero codes, a graphical arrangement front end is constructed by adopting frameworks such as Vue, a back-end execution engine is constructed based on Spring Boot / Cloud, and a complete nodal process configuration and execution system is formed. According to the system, JSON Schema metadata is generated by automatically collecting and analyzing a Feign interface, and a user is supported to assemble integrated logic in a zero-code mode by dragging prefabricated function nodes and connecting lines; and the background models the structured JSON into a directed acyclic graph for topological sorting and static verification based on types and rules, and finally serializes the structured JSON to configure persistent storage. According to the method, visual and configured construction of integrated logic is realized, and the development threshold and the coding quantity are greatly reduced; and through built-in verification and structured storage, the reliability, maintainability and traceability of the process are remarkably improved, so that business personnel or common developers can rapidly and flexibly arrange and reliably operate the enterprise-level integrated process.

The application discloses a distributed test resource scheduling method, comprising the following steps: receiving test task request information sent by at least one task node; S2: obtaining resource types required by test tasks according to the received test task request information, and acquiring working state queue information of at least one resource node meeting the resource type condition; S3: performing resource scheduling according to the test task request information and the working state queue information, generating a scheduling result in such a manner that each test task to be processed in the task node is sequentially completed and the total time is the shortest, and allocating resource nodes according to the scheduling result; sending the scheduling result to the task node, and sending at least one working request to the resource nodes allocated according to the scheduling result. Through priority scheduling, the application can still stably run various tasks when the task queue is long, and effectively guarantees the execution efficiency of the test system when long tasks and short tasks are alternately executed.

This application relates to a product search method, apparatus, device, and medium in the field of e-commerce technology. The method includes: responding to a product search request and obtaining a recall list coarsely recalled based on user-input search keywords; determining the node servers corresponding to each recalled product in the recall list, where each node server caches multiple search-related scores for some recalled products across different dimensions, the search-related scores representing the relevance between the recalled products and the search keywords in a specified dimension; sending a score calculation request to each node server to obtain the search scores calculated by the node servers for the cached recalled products, the search score for each recalled product being calculated based on multiple search-related scores for that product; and constructing a search results list by filtering products from the recall list whose search scores meet preset conditions based on the search scores. This application can quickly and accurately search for products.