10 results about "Online algorithm" patented technology

The invention belongs to the technical field of petroleum and natural gas engineering, and particularly relates to a priori knowledge embedded unsupervised learning geology-engineering dessert comprehensive evaluation method, which comprises the following steps: S1, obtaining an evaluation data set of a research area, and preprocessing and standardizing the evaluation data set; s2, dividing the evaluation data set into a positive index and a negative index according to the prior knowledge, constructing positive and negative ideal points through the prior knowledge, and fusing to generate an unsupervised evaluation data set; s3, clustering is carried out on the unsupervised evaluation data set by adopting principal component analysis and an incremental online k-means algorithm; and S4, according to category labels obtained by clustering, determining geological-engineering dessert grades by adopting a standardized variable distance grading evaluation method, and carrying out segmented clustering optimization and perforation position optimization on the geological-engineering dessert grades. According to the method, a supervised evaluation effect is achieved through an unsupervised algorithm, comprehensive evaluation of the dessert of the fractured horizontal well section is achieved, and the problem of unlabeled data evaluation is effectively solved.

The application discloses a cloud measurement and control arrangement architecture, method and system based on micro services, belongs to the field of combination of spaceflight measurement and control and cloud computing, and comprises: a service arrangement architecture after cloudization of a measurement and control baseband, which adopts micro services and a layered thought, performs hierarchical and service division of the arrangement architecture, and realizes high availability, high cohesion, low coupling and scalability of the cloud baseband arrangement architecture; a customizable arrangement rule model, which realizes self-arrangement and scalability of rules, and improves richness of the micro service arrangement architecture; and open access capability of a scheduling algorithm service, which can randomly access diversified scheduling services online, forms a dynamically scalable online algorithm library, provides flexible, balanced and optimized deployment for measurement and control application arrangement, and enhances scheduling capability of the micro service arrangement architecture. The application can comprehensively realize service, diversification and open arrangement of measurement and control resources.

This invention discloses an online algorithm development method, system, and device for dynamic management of the runtime environment. Addressing the problem that current algorithm development platforms often have pre-installed algorithm components, making it difficult to expand and flexibly support rapidly changing business scenarios, this invention establishes a basic algorithm development environment, constructs algorithm components, uploads the required dependency files for the algorithm components, and obtains an environment library dependency list. It then creates an algorithm runtime environment container, selects programming language versions and corresponding dependency files from the environment library dependency list, and establishes an extended algorithm runtime environment. The extended algorithm is coded, debugged, and deployed online using an algorithm editor. During task modeling, multiple algorithm components are selected, and the training and runtime environments of the algorithm components are dynamically managed. This provides an environment expansion scheme, generating extended algorithm environments based on selected dependency packages to achieve algorithm environment expansion.

The application discloses an internet harmful event detection method, device and storage medium, constructs or updates a keyword knowledge graph, divides the knowledge graph into a plurality of subgraphs, clusters documents into harmful events by using a clustering algorithm, inserts each harmful event into a harmful story tree by updating each harmful event, or creates a new harmful story tree according to the harmful event, realizes harmful content detection and classification in mobile internet and internet, and the purpose is to find harmful events from massive webpage and document data, organizes harmful events in a reasonable harmful story tree in an online mode, proposes a two-layer webpage document clustering algorithm based on a knowledge graph, extracts harmful events from a large amount of webpage text or webpage related news, and organizes events into a story tree by using an online algorithm after new webpage and document data arrive, and is more effective than a traditional keyword-based harmful algorithm in the aspect of harmful event extraction.

The invention discloses a method and system for correcting the topological relation between a distribution network area transformer and a line, and relates to the technical field of distribution network transformer topology correction, and the method comprises the steps: obtaining a to-be-corrected area transformer in a target area, and injecting a target current signal with a preset frequency and amplitude at a preset side of the area transformer; based on a feeder terminal unit, acquiring first current signals of a plurality of section switches of the target area; extracting a high-frequency component amplitude of the first current signal, and obtaining a first signal amplitude of the section switch based on the high-frequency component amplitude; if the first signal amplitude is greater than a preset threshold value, obtaining a target line of the section switch; and correcting the topological graph of the target area based on the target line, thereby solving the problems of high cost caused by the fact that a monitoring device needs to be additionally arranged on a transformer node in a current correction method for the topological relation between the power distribution network line and the transformer area, and complexity and difficulty in compatibility caused by the fact that different threshold values and parameters need to be set in an online algorithm.

The present application relates to the technical field of administration, in particular to a security personnel intelligent scheduling system and method based on hierarchical architecture. The system adopts five-layer architecture of data management layer, feature calculation layer, intelligent core layer, decision support layer and user interaction layer to realize business logic decoupling. The method core includes: converting requirements into structured portraits through a project analyzer; the intelligent scheduling engine adopts a multi-objective evolutionary algorithm integrating robust optimization, generates a resilient scheduling scheme capable of resisting the worst absence scenario by defining an uncertain set of personnel availability; the dynamic scheduler adopts an online algorithm with a guaranteed competitive ratio to provide real-time decisions with bounded performance for unpredictable temporary tasks. The scheme realizes the change from post-event remediation to pre-event prevention, guarantees business continuity, and provides quantifiable performance guarantees for scheduling decisions in dynamic environments.

The invention relates to the technical field of administrative management, in particular to a security personnel intelligent scheduling system and method based on a layered architecture. The system adopts a five-layer architecture of a data management layer, a feature calculation layer, an intelligent core layer, a decision support layer and a user interaction layer to realize business logic decoupling. The core of the method comprises the following steps: converting a demand into a structured portrait through a project analyzer; the intelligent scheduling engine adopts a multi-objective evolutionary algorithm fused with robust optimization, and generates a flexible scheduling scheme capable of resisting the worst absence scene by defining an uncertain set of personnel availability; and the dynamic scheduler adopts an online algorithm with competition ratio guarantee to provide real-time decisions with bounded performance for unpredictable temporary tasks. According to the scheme, shift arrangement is changed from post-event remedy to pre-event prevention, and quantifiable performance guarantee is provided for scheduling decisions in a dynamic environment while service continuity is guaranteed.

The invention provides a method for realizing flexible deployment of a target detection and tracking algorithm and a computer program product, which construct a full-link automatic process from data annotation, model training to reasoning deployment, realize rapid construction and one-button deployment of target detection, tracking and time sequence prediction algorithms, take a data warehouse as a unified entry of data, and realize flexible deployment of the target detection and tracking algorithm. The data set can be automatically annotated to obtain annotated data capable of being used for model training, and versioning control is implemented; the task management module can create a training task and implement trajectory tracking and time sequence prediction algorithm training through a selected data version and algorithm, the online algorithm is packaged layer by layer when the training task is completed, and finally, the obtained multi-layer detachable algorithm package can provide inference service for any application through online deployment at an inference end. The problems that a traditional model is long in development and deployment period and high in integration complexity are solved, and therefore flexible deployment of the target detection tracking algorithm is achieved for any application and requirements thereof.

The invention relates to the technical field of server-free computing resource scheduling, and provides a server-free computing resource scheduling method and system based on an online algorithm, and the method comprises the steps: recording whether each job experiences cold start time or not when passing through different functions in a DAG application operation process, and marking the jobs as qualified jobs and unqualified jobs; setting a time window for the DAG application; at the end of each time window, obtaining the use condition and the concurrency degree of the quantitative instances, and calculating an observation value in combination with the marking condition of the completed operation; and comparing the observed value with a performance index target value, and if the observed value is smaller than the performance index target value and a certain function uses a quantitative instance during operation processing, starting a new reserved instance for the function at the end of the time window. The operation is prevented from experiencing cold start time in the processing process, and the scheduling timeliness and reliability are very high.

The application discloses an algorithm correction method, device, system and storage medium, which are used for optimizing a product quality online detection algorithm and improving the accuracy of online detection. The method comprises the following steps: in the process of detecting the product quality value according to a preset algorithm, acquiring a first offline value of a key impurity component of the product according to a first preset time interval, and acquiring a second offline value of all impurity components of the product according to a second preset time interval; correcting a first coefficient in the preset algorithm according to the first offline value; and correcting a second coefficient in the preset algorithm according to the second offline value. By using the scheme provided in the application, the coefficients of the online algorithm are corrected by more accurate offline values, the algorithm is optimized, and the accuracy of online detection is improved.