20 results about "Dynamic database" patented technology

This invention relates to the field of fire protection planning technology, specifically a method for fire station layout and fire equipment configuration based on GeoAI. The method includes: acquiring spatial data related to building identification and constructing a multi-source dataset; determining fire rescue demand points and types based on socio-semantic segmentation using a visual language model, and constructing a dynamic database of fire stations and fire equipment; establishing a comprehensive demand paradigm for fire rescue equipment and decomposing its equipment subsets; determining the optimal pairing of fire rescue demand points with multiple fire stations and evaluating the comprehensive weighted response time; identifying areas with weak fire rescue coverage and determining the initial locations of each candidate fire station; iteratively optimizing the locations of candidate stations to determine the proposed fire station layout scheme; optimizing the spatial layout and equipment configuration of fire stations in conjunction with fire rescue response capabilities; and outputting the fire station layout and fire equipment configuration scheme. This invention achieves differentiated and refined configuration of fire station site selection and equipment, providing a scientific basis for fire protection planning.

The application relates to the technical field of geotechnical engineering, and particularly discloses a power transmission engineering pipe pile uplift bearing capacity intelligent prediction method and system, the method comprises the following steps: determining the limit uplift bearing capacity of each pipe pile in a preset sample area; acquiring the real-time load and pile head displacement of each pipe pile in an operation stage, and fitting a load response quantity; determining a coefficient distribution map according to the limit uplift bearing capacity of each pipe pile and the load response quantity thereof; receiving a user-inputted to-be-installed area, matching the coefficient distribution map in a dynamic database, and predicting the limit uplift bearing capacity based on the coefficient distribution map and pipe pile installation information; on the basis of predicting the limit uplift bearing capacity, actual use conditions are acquired through a sensor in an actual application stage, a dynamic influence coefficient determined by an area is generated, and the prediction results of subsequent same-type areas are corrected, so that the prediction accuracy is improved at a very low cost.

This invention relates to the field of battery management system technology, and discloses a power battery system and method based on user interaction upgrades. The system includes: S1, constructing a deeply coupled architecture between an interaction management unit and a battery management unit; S2, constructing a dynamic database; S3, dynamically adjusting the liquid cooling pump power and PTC heating threshold based on driving habits and ambient temperature and humidity data; S4, constructing a two-layer architecture of local edge computing nodes and a public cloud; S5, using an LSTM neural network to analyze historical charge-discharge curves and predict cell lifespan; S6, displaying a degradation degree map through an IMU interface, supporting user scanning to replace degraded cells and automatically configuring topology parameters; and S7, establishing a three-dimensional decision matrix of user settings, environmental perception, and battery status to dynamically optimize charging strategies. This application solves the problems of traditional systems such as lag in interaction, insufficient intelligence, maintenance difficulties, and data synchronization bottlenecks, reducing maintenance costs, extending battery pack lifespan, and achieving collaborative full-cycle management.

This invention discloses a dynamic database platform and implementation method for wind power equipment failure mode and impact analysis (FAM). Built on a B / S architecture, it includes a server-side and a user-side. The server-side comprises a database layer and a functional processing layer. The database layer stores wind power equipment failure analysis data from expert, enterprise, and personal databases in a hierarchical manner. The functional processing layer acquires, parses, structures, and updates the status of multi-source failure-related information. By incrementally acquiring, semantically parsing, and mapping text data from different sources, candidate failure modes and impact analysis records are generated. Combined with a manual review mechanism, continuous updates and flow of failure analysis data are achieved, thereby supporting the accumulation and application of wind power equipment failure knowledge and improving the completeness and maintainability of failure analysis results.

This invention belongs to the field of network security technology, specifically relating to automated penetration testing methods, systems, equipment, and media. Addressing the shortcomings of existing automated penetration testing methods, such as low testing efficiency or low testing accuracy, this invention adopts the following technical solution: an automated penetration testing method, comprising: S1, constructing a multi-layered database, where the first layer is a static knowledge base and the second layer is a dynamic database, modeling the online state for a single session; S2, dual-channel retrieval of the static knowledge base to obtain a candidate set of appropriate size; S3, based on the dynamic database, performing a single-step three-dimensional linear scoring on each candidate action in the candidate set to select the optimal candidate action; S4, executing the optimal candidate action for testing; S5, if the test fails, recording the reason label and adjusting the labels of similar candidates; if the test succeeds, improving the statistical data of similar actions. The beneficial effects of this invention are: improved testing efficiency and accuracy.

This invention discloses a dynamic prediction method for tunnel water inflow, belonging to the fields of tunnel engineering and hydrogeology. The method first constructs an initial hydrogeological conceptual model; then establishes a dynamic database integrating geological, geophysical, monitoring, and meteorological data; furthermore, it establishes a dynamically coupled prediction model that combines a physical numerical model and a machine learning proxy model; utilizing newly revealed data during construction, it dynamically inverts and updates model parameters through a data assimilation algorithm; the updated model is then used for probabilistic water inflow prediction and risk level classification; finally, the results are visualized and a feedback loop is formed. This invention, through a dynamic update mechanism, enables the prediction model to continuously approximate real geological conditions, solving the problems of low accuracy and poor adaptability of traditional static prediction methods, and significantly improving the ability of tunnel construction to cope with water inflow risks.

The present application relates to greenhouse gas emission management and coal bed gas exploitation technical field, disclose a kind of coal bed gas exploitation intelligent emission reduction system and method based on dynamic carbon footprint accounting, system includes data perception layer, dynamic database layer, accounting engine layer and decision control layer, data perception layer real-time acquisition full life cycle energy consumption and emission data, dynamic database layer is based on measured data dynamic update emission factor, accounting engine layer calls dynamic factor, real-time calculation product carbon footprint, decision control layer generates and executes emission reduction strategy according to accounting result, and can be warned when emission is over standard.This application corrects general emission factor through measured data, significantly improves the accuracy and timeliness of accounting;Build a closed loop of "monitoring, accounting, early warning and control", realize the change from passive reporting to active emission reduction;And by tracing the emission to single well and single process, support fine management and process optimization.

This invention relates to the field of inquiry screening technology, and particularly to an inquiry screening method and system. The method includes: acquiring the dialogue between the inquiry initiator and the respondent, extracting the inquiry questions and corresponding response content, integrating them to obtain inquiry records, creating a term set composed of several fixed and dynamic keywords, and clustering the inquiry records into a fixed database and a dynamic database; upon receiving a new inquiry, identifying keywords and converting them into standard sentence structures, traversing the term set, and querying in either the fixed or dynamic database, sequentially calculating the similarity between the standard sentence structure and the inquiry record. This invention, through effective inquiry screening, not only automates the processing of repetitive questions and provides precise manual service for complex questions, but also improves the accuracy of responses and optimizes the user experience for initiators through similarity matching and order completion score evaluation, providing reliable data support for inquiry management.

The application provides a dynamic database connection pool adjustment method and system, and relates to the technical field of computers, which comprises the following steps: collecting running state data of a target dynamic database connection pool in real time and sending the data to a configuration center; based on the received running state data of the connection pool, the configuration center determines a connection number adjustment index in combination with a current connection request of the target dynamic database connection pool; based on the connection number adjustment index, the configuration center dynamically updates the maximum connection number of the connection pool and notifies a connection pool module to update. Through the use of the configuration center to collect the running state data of the target dynamic database connection pool in real time, the combination of the connection request to calculate the connection number adjustment index, and the dynamic update of the maximum connection number of the connection pool by using the connection number adjustment index, the service capacity of the connection pool to the outside is effectively improved, and the stable operation of a business system is ensured.

The application discloses a bridge full-life-cycle carbon emission reduction cost efficiency optimization method and device based on reinforcement learning, computer equipment and a readable storage medium, comprising: acquiring carbon emission data, cost data and optional scheme parameters of each link of the full-life-cycle, and constructing a dynamic database; constructing an optimization model based on the database, and defining unit economic carbon reduction efficiency as an objective function; constructing a reinforcement learning environment, initializing a strategy network, and iteratively training through a reinforcement learning algorithm to solve optimal strategies of each link; and running the optimal strategy in a verification set, and outputting total full-life-cycle carbon emission, economic cost and link carbon reduction efficiency analysis results. The application realizes multi-link collaborative optimization by combining dynamic database real-time data updating and reinforcement learning, and provides intelligent and low-carbon full-life-cycle decision support for bridge engineering.

This invention provides a precise control and monitoring system for the primary coolant charge in a nuclear power plant, comprising the following functional modules: a data acquisition module, which collects primary loop temperature and pressure data, calculates the coolant charge mass using a zoned accumulation method, and constructs a dynamic database; an anomaly identification and trend analysis module, which calculates the rate and acceleration of mass charge change, identifies abnormal consumption, and judges its development trend; a state prediction and risk assessment module, which calculates the predicted mass charge mass for subsequent monitoring cycles based on abnormal consumption; and an early warning response and control module, which determines the remaining time before the predicted mass charge mass reaches a safety threshold, thereby determining the risk level and generating control commands. This invention achieves high-precision charge mass calculation through a zoned accumulation method, introduces both rate and acceleration indicators to achieve early identification and trend judgment of abnormal consumption, and automatically classifies risk levels based on the remaining time, realizing a shift from post-accident response to pre-accident early warning.

The application discloses a 3D printing solid waste sound barrier carbon emission reduction prediction method based on machine learning, establishes a low-carbon scenario and a baseline scenario respectively, and further constructs a carbon emission reduction model of the low-carbon scenario compared with the baseline scenario, wherein the carbon emission reduction model comprises a multi-source dynamic database for storing carbon emission factors at various stages and a unit mileage carbon emission reduction calculation model; engineering parameters of carbon emission influencing factors are selected to construct original feature data and normalization is performed, and the association between the engineering parameters and total carbon emission is established; finally, a combination model is constructed based on multiple single machine models which are trained, according to different weighting modes, and the combination model is trained through a training set, and a combination machine model is used to capture complex nonlinear relationships, so that the prediction speed is fast and the precision is high.

This application relates to the field of information technology, specifically to a method and system for generating SQL for dynamic database schemas oriented towards low-code configuration. The method includes: scanning the database's data model, establishing mapping relationships between the physical layer, logical layer, and natural language layer, and constructing a multi-level schema linker; providing a semantic configuration panel in a low-code interface to integrate configuration information into the multi-level schema linker; receiving natural query language, inputting it into a Text-to-SQL model, and obtaining several SQL drafts; generating confidence scores for each SQL draft based on the multi-level schema linker, and displaying the associated confidence scores of several SQL drafts; providing a low-code SQL editor for user interaction, correcting the SQL drafts based on user corrections and feeding them back to the Text-to-SQL model, and submitting the SQL based on user submissions.

This invention belongs to the field of data processing and management technology, specifically relating to a multi-dimensional integration and intelligent management method for silkworm germplasm resources. It aims to solve problems such as data fragmentation, non-standardized processing, low classification accuracy, and insufficient intelligence in existing management practices. The method includes: collecting multi-source raw data according to four dimensions and binding them with unique traceability identifiers; forming a standardized dataset through outlier processing, standardization transformation, and integrity verification; integrating and generating a complete data archive, extracting single-dimensional core features and cross-dimensional correlation features; constructing a dynamic database after improving K-means clustering classification; and building an intelligent management platform to achieve full-process control and periodically iteratively optimizing the model. The system includes corresponding linkage modules, with the unique traceability identifier as the core associated data. This achieves deep integration and standardized management of multi-source data, improves classification accuracy and management intelligence, and forms a closed-loop mechanism.

The invention relates to a vehicle state regulation system for limiting emissions, having a state detection unit (1), a database unit (2) and a control and evaluation unit (3), wherein the state detection unit (1) is configured to provide state data, wherein the database unit (2) has a static database module (2.1), a dynamic database module (2.2) and a data management module (2.3), wherein the static database module (2.1) has static data on causal relationships with respect to emissions independent of the drive train, wherein the dynamic database module (2.2) has variable data with respect to emissions independent of the drive train, wherein the control and evaluation unit (3) is configured to obtain the state data from the state detection unit (1), to obtain the database data from the database unit (2), to determine an emission budget and a target emission value by means of a calculation module (3.1), to provide an optional preliminary control instruction, to assign a predictive emission characteristic value to the control instruction, to select a final control instruction from the optional preliminary control instruction depending on the predictive emission characteristic value and a target emission characteristic value by means of an evaluation module (3.2), to output the final control instruction to an actuator unit (4), to influence the vehicle state. The invention furthermore relates to a road vehicle having such a vehicle state regulation system and to a method for vehicle state regulation.

A testing environment that simulates the stringent authentication process, and / or processes required for real world use of health care applications that deal with confidential patient information is disclosed. The testing sandbox environment may include a SMART on FHIR application, a FHIR server, a backend service including one or more processing devices, an identity management service, a dynamic database, and / or one or more user computing devices operatively coupled over a network.

The invention discloses a method for predicting vehicle dynamic response under settlement deformation driven by physical data, and belongs to the technical field of rail transit engineering.The method comprises the following steps that S1, a coupling dynamics database is constructed; s2, data preprocessing; s3, designing a model architecture; s4, performing model training; and S5, model application. According to the method for predicting the dynamic response of the vehicle under the settlement deformation driven by the physical data, the dynamic response of a plurality of parts of the vehicle can be rapidly predicted, the method fits the actual working condition, it is ensured that the prediction result conforms to the physical law, the model interpretability is improved, the prediction precision is improved, and meanwhile, the method is expanded to a composite settlement deformation scene and meets the engineering requirements.

The application relates to a survey drilling data asset value evaluation method and system fusing space-time dynamic factors, which comprises the following steps: multi-source heterogeneous drilling data acquisition and intelligent preprocessing; drilling data asset encapsulation and dynamic database updating; four-dimensional dynamic value quantitative evaluation; dynamic reevaluation triggering and iteration; and evaluation result asset adaptation output. The application solves the problems of traditional methods, such as dependence on manual work, large standardization deviation, and separation of stock and incremental data processing, greatly reduces the cost of manual intervention, shortens the database delay from several days to minutes, and meets the real-time management requirements of data assetization.

A method of managing a dynamic database for providing a personalized service includes obtaining user input information from an electronic device; obtaining, from the user input information, context information that relates to the personalized service, wherein the context information includes implicit information determined based on the user input information; and updating the dynamic database based on the context information.