19results about How to "Efficient configuration" patented technology

The invention provides a rock-soil geological survey analysis method and equipment, and belongs to the technical field of soil survey, and the method specifically comprises the following steps: according to the coincidence degree of matched sampling pressure intervals of different soil types, combining the soil type data of the sampling pressure intervals belonging to the matched sampling pressure intervals; determining an identification processing method of taking the sampling pressure interval as an alternative pressure interval, utilizing the alternative pressure interval and the sampling analysis processing data of the alternative pressure interval, and combining the overlapping degree of the matched sampling pressure interval of the soil type and the alternative pressure interval; and the sampling processing method of the soil type in different alternative pressure intervals is determined, so that the sampling processing accuracy is improved.

This invention provides an adaptive configuration method for distribution network protection devices based on the fireworks algorithm, belonging to the field of operation and maintenance technology for energized distribution networks. The method includes: acquiring the status of circuit breakers at the distribution network site; generating a protection topology matrix based on the circuit breaker status; and using the fireworks algorithm to generate an optimal protection configuration strategy based on the protection topology matrix. The adaptive configuration method for distribution network protection devices based on the fireworks algorithm provided by this invention improves upon the fireworks algorithm itself, combining its data processing characteristics to obtain the optimal configuration scheme for distribution network protection devices, and ultimately achieves efficient configuration of the on / off states of each circuit breaker at the distribution network site.

The application relates to a display device, which comprises a main chip, a signal conversion circuit and a display platform. The main chip outputs a 16-channel V-by-One signal carrying a target picture; the signal conversion circuit comprises a first signal conversion module, a second signal conversion module and a signal splicing module; the first signal conversion module is connected with the main chip and is used for converting the 16-channel V-by-One signal into a 16-channel LVDS differential signal; the second signal conversion module is connected with the first signal conversion module and is used for converting the 16-channel LVDS differential signal into a plurality of 4-channel first HDMI signals; the signal splicing module is connected with the second signal conversion module and is used for splicing the plurality of 4-channel first HDMI signals to output a second HDMI signal, and the bit number of the second HDMI signal comprises 10 bits; the display platform is connected with the signal conversion circuit and is used for receiving the second HDMI signal to display the target picture. The application can convert the 16-channel V-by-One signal into the 10-bit second HDMI signal at low cost.

The application provides a water supply pipe network corrosion pipe section identification and diagnosis method based on water quality inversion, the method collects water quality data and pipe section attribute information in a water supply pipe network area, determines the topological water flow direction based on the residual chlorine decay characteristics, determines the appropriate diagnosis node and target independent pipe section, monitors the water quality parameter change characteristics in the pipe section, combines the water quality change amount and the quantitative evaluation model of the pipe section corrosion degree, realizes the target positioning of the corrosion pipe section and the rapid inversion diagnosis of the corrosion state, the input layer of the model is the water quality change characteristics and pipe section information between the pipe network diagnosis nodes, the operation layer adopts an algorithm based on the water quality decay characteristics and the corrosion state mapping relationship, and the output layer is the pipe section corrosion state score, when the diagnosis result is lower than the preset safety threshold, the warning information and the maintenance suggestion are generated, the application can realize the diagnosis effect with the determination coefficient exceeding 0.95, and effectively improves the safety and reliability of the operation management of the water supply pipe network.

The present disclosure signals a configuration for a synchronization signal / physical broadcast channel block (SSB) transmitted in an on-demand manner in a wireless communication system. The method can include the steps of receiving configuration information related to a synchronization signal / physical broadcast channel block (SSB) of a first cell, identifying at least one of the first cell operating as a no-SSB cell and the first cell managing on-demand SSB based on the configuration information, and performing communication in the first cell based on the configuration information.

A work vehicle is provided with drive wheels (2, 3), a work device (4) provided on a machine body frame (1), and a manipulation unit (5) provided on the upper side of the machine body frame (1), the manipulation unit (5) being on which a worker sits, the work vehicle being provided with an electric chamber (8) in which a first electric motor (30) for driving the work device (4) and a second electric motor (40) for driving the work device (4) are accommodated, and the second electric motor (40) being provided on the upper side of the machine body frame (1). The first electric motor (30) drives the driving wheels (2, 3), the second electric motor (40) drives the driving wheels (2, 3), the length direction of the first electric motor (30) is arranged along the front-back direction, the length direction of the second electric motor (40) is arranged along the front-back direction, and the first electric motor (30) and the second electric motor (40) are arranged side by side in the left-right direction. Provided is a work vehicle in which equipment is efficiently arranged in a space.

The application provides an interval event matching method and system of a content-based publish / subscribe system, through constructing a predicate disjoint set and an optimized partition model thereof, and integrating a learning index of a range query recursive model index in each partition, high-speed, stable and verifiable matching of events to a subscription set under multi-attribute interval predicates is realized; in particular, the traditional memory-intensive matching is reconstructed into a calculation-intensive process mainly based on model reasoning, while correctness and completeness are ensured, average latency is reduced and long tail delay is inhibited, and key modules such as partition and coverage optimization, model training and online reasoning, error boundary control and limited correction, and accurate back matching of residual set subscription are included.

The application discloses a kind of tube plate laser cutting equipment and its using method, it is related to laser cutting machine technical field, in tube plate laser cutting equipment, pipe material warehouse, machine tool and plate material warehouse are sequentially arranged along X axis direction, pipe material warehouse is equipped with pipe material feeding mechanism, plate material warehouse is equipped with plate material feeding mechanism, machine tool moves along X axis direction by X axis mechanism;The lower portion of portal frame is also equipped with pipe material lifting mechanism, and the pipe material feeding mechanism is movably connected with the portal frame along the Y axis direction;Pipe material feeding mechanism, plate material feeding mechanism, X axis mechanism, pipe material lifting mechanism, pipe material feeding mechanism, Y axis mechanism, Z axis mechanism and laser cutting mechanism are electrically connected with host computer;The method is: after host computer receives the feeding command of pipe material or plate material, host computer drives machine tool to move to plate material or pipe material feeding station, and the pipe material or plate material feeding mechanism is fed to machine tool.The application can improve the degree of automation of pipe material and plate material feeding, and is beneficial to improve feeding efficiency.

The application discloses a kind of set up and release of collaborative optimization system of port loader scheduling, it is related to port scheduling technical field, including the following steps: step 1, data acquisition: data set is obtained by MySQL database;Step 2, data processing;Step 3, establish set up and release of collaborative optimization model of port loader scheduling, divided into two parts of constraint condition and the construction of objective function;In the present application, intelligent scheduling, efficient collaboration: according to the complex field conditions of gas transport set up and release, establish set up and release of collaborative optimization mathematical model of port loader scheduling under matching scene, the optimal loader configuration and controllable release vehicle can be accurately calculated, to ensure the efficient use of resources, through the system not only can significantly improve the efficiency of field operation, but also can promote the collaboration and smoothness of overall operation process.

This invention relates to the field of meteorological forecasting technology, specifically a meteorological forecasting adaptive optimization method and system based on multi-algorithm fusion. This method constructs a parameter optimization framework based on multi-algorithm fusion, embedding physical constraints, and possessing adaptive capabilities, aiming to systematically solve key problems in the parameter tuning process of traditional meteorological forecasting systems. This framework achieves efficient and intelligent optimization through a series of tightly linked steps, ensuring the effectiveness and stability of the method in operational scenarios. This process integrates preceding modules into a unified platform through a microservice architecture, automating data and control flows. The evaluation system includes historical backtesting, real-time forecast testing, and extreme weather-specific testing, quantifying forecast accuracy improvement, resource consumption optimization, and cross-scenario generalization capabilities. Results are fed back to a knowledge base to form a self-optimization loop, ultimately verifying the comprehensive advantages of this method in improving forecast efficiency, ensuring physical rationality, and operational applicability.

A vehicle body structure is provided that allows for efficient configuration of crossbeams while securely supporting the seats. This includes: a vehicle body frame (2); and a battery box (10) mounted on the vehicle body frame (2). The battery box (10) has: a housing (11) for accommodating batteries; and a battery cover (12) covering the housing (11) from above. A crossbeam (4) extending along the vehicle width direction is provided on the upper surface of the battery cover (12); and a seat support frame (6) extending from the crossbeam (4) in the vehicle longitudinal direction and supporting the seats of the vehicle (1).

This invention discloses an intelligent product configuration method and system based on multi-level semantic matching, comprising: acquiring a demand dataset, extracting feature information from demand items and concatenating them to form demand text; using a text embedding model for vectorized encoding, performing an approximate nearest neighbor search in a product vector index library to obtain a first candidate product set; pairing the demand text with the feature text of the first candidate products, inputting it into a semantic re-ranking model to complete relevance modeling and outputting a matching score, and re-ranking and filtering based on the score to obtain a second candidate product set; inputting the demand text and the product information of the second candidate product set into a large language model, which performs multi-candidate joint evaluation and outputs a structured evaluation result; after parsing and verifying the structured evaluation result, generating and outputting a configuration result containing the selected product identifier. This invention achieves multi-level semantic matching and intelligent product configuration, improving matching accuracy and decision reliability.

The invention relates to the technical field of nondestructive testing of power equipment, and discloses an X-ray nondestructive testing method for crimping quality of a strain clamp of a power transmission line. The method comprises the following steps: fusing a topological structure, operation and maintenance records and meteorological data to generate an intelligent detection task list; the pose of the X-ray device is automatically calibrated, and multi-angle transmission imaging is carried out; performing standardization processing on the image, and inputting the image into a pre-trained multi-scale convolutional neural network to realize pixel-level defect segmentation; and calculating a crimping quality comprehensive evaluation index in combination with the three-dimensional defect depth and the service degradation factor, and generating a graded early warning signal to be pushed to an operation and maintenance platform. According to the method, through full-process closed-loop management, the detection precision, efficiency and response speed are remarkably improved, and safe and reliable operation of the power transmission line is guaranteed.

A multi-model power system inertia probabilistic prediction method based on porcupine optimization and adaptive kernel density estimation includes the following steps: acquiring power system inertia-related characteristic variables, constructing a data sample set for inertia prediction, and building a CNN-BiLSTM-MHAM deep learning model based on the data sample set; optimizing key hyperparameters of the model using the porcupine optimization algorithm based on the constructed CNN-BiLSTM-MHAM deep learning model to obtain optimized model structure parameters and inertia prediction results; constructing an error database based on the error between the inertia prediction results and actual values; and using the constructed error database, probabilistically modeling the prediction error using the adaptive bandwidth kernel density estimation method, and generating the probability interval for inertia prediction by combining the Bootstrap resampling method, thereby realizing the quantification and probabilistic expression of the uncertainty of the inertia prediction results. This method not only significantly improves the accuracy of power system inertia prediction but also more effectively characterizes the uncertainty and probability distribution characteristics of inertia fluctuations.

This application discloses a human resource allocation method and system based on multi-source employment demand, relating to the field of knowledge graph technology. The method includes: acquiring employment task types and multi-dimensional task demand information; obtaining family-of-tasks and family-of-task demand information; and extracting neighboring task groups and neighboring task demand information groups; generating multi-dimensional capability parameters; processing and acquiring human resource matching degree, matched human resource information, and matched multi-dimensional capability parameters; and extracting neighboring human resource information groups and neighboring multi-dimensional capability parameter groups; performing derivative task matching analysis to obtain derivative human resource matching degree; and optimizing human resources based on the human resource matching degree and derivative human resource matching degree to obtain optimal human resource information for allocation. This application solves the technical problems of existing human resource allocation methods lacking the ability to predict potential derivative tasks and exhibiting information silos between the human resource database and the task database, leading to low matching efficiency and accuracy.

This invention discloses a drone swarm monitoring system and method, relating to the field of drone swarm collaborative operation technology. The method includes: continuously sensing the state of several preset task areas, acquiring the state values ​​of each area and constructing a time-series sequence; calculating the state change rate and acceleration of each area based on the sequence; calculating a dynamic task priority value by combining the historical task execution frequency of each area; generating a drone swarm task allocation scheme based on the priority values ​​of all areas, combined with the location, urgency, and resource requirement constraints of the task areas, using a preset optimization model to achieve load balancing; planning flight paths for each drone, driving the swarm to execute tasks, and supporting dynamic reallocation based on real-time feedback.

This invention discloses a reinforcement learning-based method for optimizing the performance of FAS-assisted satellite-to-ground communication. In air-to-ground communication, when the direct path is blocked by obstacles, the signal is transmitted through a mixture of reflection from moving scatterers and the direct path. This invention describes the communication environment between the mobile transmitter and the ground user through geometric stochastic modeling, establishes a dynamic optimization framework based on FAS, couples satellite motion characteristics with adjustable FAS parameters to construct a three-dimensional channel model, designs an improved Memetic PPO reinforcement learning algorithm to dynamically optimize the FAS configuration set at the ground user in the discrete action space through a local search mechanism, and jointly optimizes channel capacity and modeling accuracy to generate the optimal strategy. This method reveals the nonlinear relationship between satellite motion and channel characteristics, significantly improves communication performance in complex obstruction environments, provides a new method for dynamic channel optimization of satellites, and has significant application value.

This invention discloses a collaborative management method and system for intelligent industrial worker communities, belonging to the field of intelligent management technology. The method includes: deploying IoT sensors within the worker community to continuously collect environmental data, worker feedback, and production management data; fusing and analyzing these data to generate dynamically updated worker group profiles and individual demand preference models; based on this model, mining behavioral chains and spatiotemporal trajectories to perform dynamic demand prediction for the worker group; and conducting demand collision analysis and adaptive scheduling management based on the prediction results and the current production plan. This invention solves the technical problem that existing worker community management models cannot accurately coordinate production needs with workers' living needs, leading to unreasonable resource allocation, low management efficiency, and insufficient worker satisfaction. It achieves the technical effect of dynamically matching worker needs with production scheduling through intelligent collaborative management, optimizing resource allocation, and improving management efficiency and worker satisfaction.