50674results about How to "Improve convenience" patented technology

The invention belongs to the technical field of artificial intelligence, and relates to a power document intelligent question and answer method and system based on a large language model. The method comprises the steps of obtaining document data according to a preset period; preprocessing the document data to obtain an adaptive document; constructing a vector retrieval library through an embedded model according to the adaptive document; obtaining a user query question, inputting the user query question into a vector retrieval library, performing retrieval based on a vector similarity retrieval method and a keyword retrieval method to obtain related text blocks, and screening out the most related text block from the related text blocks through a two-stage rearrangement technology; a user queries the question and the most relevant text block and inputs the question and the most relevant text block into the large language model to obtain preliminary intelligent answer information; and correcting the preliminary intelligent answer information based on a preset self-provincial inversion mechanism to obtain final intelligent answer information. Multiple rounds of questions and answers and context understanding are supported based on a correction mechanism, context consistency can be kept in continuous query of complex technical questions, and the accuracy of multiple rounds of questions and responses is ensured.

The invention discloses an electric power facility visual monitoring system and method, and relates to the technical field of electric power facility operation and maintenance, the system comprises the following components: a multi-source heterogeneous data acquisition module, a multi-source heterogeneous data processing module, a real-time risk assessment and maintenance strategy adjustment module and a visual display module; according to the method, the electric parameters, the environment data, the image video data, the audio data and other multi-source heterogeneous data are integrated, the intelligent fusion algorithm and the association analysis model are utilized, the potential association relationship among different types of data is deeply mined, and therefore the operation condition of the electric power facility can be reflected more comprehensively and accurately, and the operation efficiency of the electric power facility is improved. According to the method, the accuracy and integrity of monitoring data are improved, the system can timely find and pre-judge potential risks, powerful decision support is provided for operation and maintenance personnel, and safety risks and maintenance cost increase caused by incomplete or inaccurate monitoring are effectively avoided.

The invention belongs to the field of energy efficiency optimization in industrial production, and discloses a dynamic energy efficiency optimization method and system based on artificial intelligence and machine learning, and the method comprises the steps: collecting energy consumption data and environment parameters in real time through a sensor network and Internet of Things equipment; cleaning, screening and standardizing the collected data; constructing an energy efficiency prediction model and an optimization model based on a machine learning algorithm; training the prediction model and the optimization model by using historical data, and adjusting model parameters; and the trained model is utilized to analyze and predict data acquired in real time, and production parameters are dynamically adjusted to realize optimization of energy efficiency. According to the method, key parameter changes in the production process can be accurately predicted and optimized, dynamic adjustment of production parameters is achieved, an optimal production adjustment strategy can be automatically made, scientificity and efficiency of production decision making are improved, and the method has remarkable technical and economic effects in the field of industrial production.

The invention relates to a data access method and system of an intelligent Internet of Things gateway. The method comprises the following steps: performing feature matching and protocol identification on a plurality of sensors and terminal equipment connected to the intelligent Internet of Things gateway by using an equipment feature library to obtain an equipment protocol type; analyzing the original data to obtain standardized data; performing encryption processing to obtain an encrypted security data packet and an encrypted session key; performing multi-factor transmission channel selection to obtain an optimal transmission channel combination; and based on the optimal transmission channel combination, sending the encrypted security data packet to the Internet of Things platform, verifying the received data confirmation information based on a consensus algorithm, and outputting a data access state report through a data visual interface and an AI voice assistant. The processing strategy can be dynamically adjusted according to the equipment characteristics, the data characteristics and the network environment, and the flexibility and adaptability of the system are improved.

The invention relates to the technical field of digital twinning, and discloses an AGV path optimization method and system based on digital twinning, and the method comprises the steps: carrying out the data standardization processing of AGV real-time coordinate data, environment obstacle distribution data and cargo storage position data, and constructing a storage environment state matrix; aGV task time parameters are calculated, and a task evaluation matrix containing task timeliness indexes and task priority coefficients is obtained; performing multi-target parameter calculation on the AGV motion energy consumption coefficient and the task weight coefficient, and establishing an AGV path optimization target function; performing path planning analysis by adopting a path exchange operator, a path insertion operator and a path inversion operator to generate an AGV initial path set; according to the AGV optimal path planning method and system, the flexibility and the optimization effect of path planning are improved, and the convergence speed and the quality of path optimization are remarkably improved.

The invention provides a textile defect positioning method, which comprises the following steps: according to an extracted defect feature map, fusing feature maps of different scales, extracting multi-scale defect features, and comprehensively depicting space distribution and combination information of defects; aiming at the condition that multiple flaws exist at the same time, a multi-task learning model is constructed, flaw detection, classification and positioning tasks are carried out at the same time, and a back propagation algorithm is adopted to optimize the multi-task learning model; positioning the defect area by adopting an image segmentation algorithm, obtaining the contour of the defect area according to the positioning result of the defect area and by adopting a Canny edge detection algorithm, and calculating the area and position information of the defect; and based on an evaluation result, a dynamic threshold adjustment algorithm is adopted, a defect judgment threshold is adjusted according to a production batch and a product type, and a threshold parameter is dynamically updated by analyzing historical data and a current production condition.

The invention discloses a road traffic signal control system and method, and the method comprises the steps: collecting real-time data through a sensor, a camera and a geomagnetic device, combining historical data with emergency analysis, and predicting a flow mode and a change trend; green light time distribution is dynamically optimized, a fixed timing, inductive and adaptive control strategy is adopted, and traffic light duration and priority adjustment is achieved; through regional cooperation and linkage control, green wave bands and branch intersection red light optimization are set, and peak period traffic signals are intelligently dispatched. A machine learning model is used to predict a flow peak value, environment and accident detection data are combined, a signal lamp period is dynamically adjusted, vehicle waiting time, traffic efficiency, carbon emission and traffic satisfaction are evaluated, and a traffic control strategy is comprehensively optimized. According to the road traffic signal control system and method, the traffic flow in different time periods is predicted by adopting the flow prediction model based on big data analysis and machine learning, and the signal period is adjusted in advance.

The invention provides an EDA software implementation method and system for memory IP layout optimization, and relates to the technical field of memorizers, the method comprises the following steps: receiving a memory IP design parameter and an optimization target input by a user, and calling a matched basic unit module from a pre-established hierarchical memory IP library according to the design parameter; an initial memory IP layout scheme is generated based on the basic unit module, the initial memory IP layout scheme is rapidly evaluated by utilizing a neural network model, a plurality of optimized layout candidate schemes are generated by adopting a genetic algorithm, and each optimized layout candidate scheme comprises different basic unit arrangements, metal layer use strategies and buffer insertion positions; performing parallel simulation on the optimal layout candidate scheme, and selecting an optimal layout scheme; and performing post-simulation verification on the optimal layout scheme, wherein the post-simulation verification comprises static time sequence analysis, dynamic power consumption analysis and electromagnetic compatibility analysis.

The invention relates to a traffic flow prediction optimization method based on an intelligent optimization algorithm, which is applied to the technical field of traffic flow prediction. The system comprises a multi-modal data acquisition and fusion module, a hybrid deep learning prediction module, an intelligent parameter optimization module, an integrated learning module, a multi-scale error correction module, a prediction result analysis and visualization module, a distributed learning and privacy protection module and the like. Wherein the hybrid deep learning prediction module adopts an attention mechanism to fuse models such as CNN, Transform and LSTM, and introduces an adaptive error correction mechanism, so that the prediction precision is remarkably improved; the intelligent parameter optimization module accelerates the model search efficiency by using technologies such as quantum computing and swarm intelligence optimization; the integrated learning module and the adversarial training strategy enhance the robustness and generalization of the model; and the multi-scale error correction module adopts a time sequence decomposition and self-adaptive online learning method to improve the accuracy of long-term and short-term prediction.

The invention relates to the technical field of law enforcement intelligent alarm, in particular to a multi-mode intelligent analysis method and system based on law enforcement supervision. The method comprises the following steps: acquiring a law enforcement scene video file from a law enforcement supervision recorder platform, and performing audio and video segmentation and law enforcement behavior information identification analysis to obtain law enforcement scene audio behavior information data and law enforcement scene image behavior information data; performing timestamp and spatial position extraction processing on the law enforcement scene video file, performing multi-modal time-space synchronization association analysis, and performing law enforcement behavior sequence connection processing and event behavior intention recognition analysis at the same time to obtain law enforcement scene event behavior intention information data; and obtaining a preset law enforcement event behavior knowledge graph, and carrying out behavior normative score calculation and nonstandard behavior intelligent alarm optimization analysis to generate a law enforcement scene event nonstandard behavior optimization suggestion report. According to the invention, the accuracy of law enforcement nonstandard behavior supervision alarm can be improved.

The invention provides a digital twinning method and system based on industrial automation, computing equipment and a storage medium. The method comprises the following steps: acquiring real-time operation parameters from a physical system; based on the real-time operation parameters and a preset physical model, constructing a digital twinborn body of the physical system in a virtual environment; simulating the operation state of the physical system by using the digital twin, and predicting the performance of the physical system under different working conditions to generate a simulation result; comparing the simulation result with the obtained actual operation data of the physical system so as to evaluate the digital twin body and obtain an evaluation result; adjusting the physical model according to the evaluation result so as to update the digital twin; and performing fault prediction and / or optimizing operation parameters of the physical system by using the updated digital twin. According to the technical scheme provided by the invention, the digital twin can be continuously optimized and the physical model can be adjusted.

The invention discloses a remote regulation and control LED lighting system based on the Internet of Things, and relates to the technical field of LED lighting systems, comprising an LED lighting equipment module which comprises an efficient lamp, a microcontroller, an Internet of Things communication module, a remote control terminal module supporting multi-protocol and encryption, having Mesh networking, a multi-terminal control, having multiple functions and innovation formulas, and a sensor module; the intelligent LED lighting control system has the advantages that environment information is collected, the data management and analysis module stores and analyzes data, energy-saving management and the like are achieved, all the modules work cooperatively, and the functions of remote intelligent regulation and control, fault self-inspection, butt joint with other systems and the like of LED lighting are achieved. Through collaborative innovation of multiple modules, remote intelligent regulation and control of LED lighting are realized, the lighting quality and user experience are improved, energy is saved, consumption is reduced, the system has the functions of fault self-checking and alarming and the like, the reliability and compatibility of the system are improved, and the diversified requirements of modern lighting systems are met.

The invention relates to the technical field of data processing, in particular to an intelligent logistics platform management system and method based on multi-source data. The method comprises the following steps: acquiring cold-chain logistics order data; performing multi-type cargo temperature control demand processing on the cold-chain logistics order data to generate cargo temperature control demand data; performing multi-node temperature control task decomposition on the cold-chain logistics order data through the cargo temperature control demand data to generate multi-node fine temperature control task data; performing cold chain abnormal feature analysis according to the multi-node fine temperature control task data to generate abnormal temperature control processing scheme data; and carrying out transportation-junction point temperature control correction according to the abnormal temperature control processing scheme data, and carrying out cold chain quality weighted scoring to generate logistics quality scoring data. According to the invention, through cold chain task decomposition and cooperation of multiple transportation nodes, intelligent cold chain logistics management is realized, and the temperature control management efficiency and cargo quality guarantee of cold chain logistics are improved.

The invention discloses an efficient flight control system of a low-altitude manned unmanned aerial vehicle based on tilting composite wings, and relates to the technical field of unmanned aerial vehicle control systems. The low-altitude manned unmanned aerial vehicle efficient flight control system based on the tilting composite wings comprises an initialization and pre-check module, a vertical take-off and landing control module, a transition flight control module, an obstacle avoidance and path planning module and a landing control module. Through integration of vertical take-off and landing, smooth transition to cruise, intelligent obstacle avoidance, path planning and other modules, autonomous and efficient flight in a complex environment is realized, and the application scene of the unmanned aerial vehicle is greatly widened. Meanwhile, the accurate flight control and data post-processing analysis capability not only guarantees the safety and comfort of passengers, but also promotes the continuous optimization of the system performance through the real-time performance evaluation and feedback mechanism. In addition, the aerial refueling / charging technology is supported, the cruising ability is prolonged, and the task execution continuity and flexibility are enhanced.

The invention provides a multi-sealing method and system for a high-vacuum die-casting die based on topological optimization, and relates to the technical field of die structures.The multi-sealing method comprises the steps that a sealing structure parameterized model is established, geometric parameters and boundary conditions of a cavity wall face are obtained, an initial design domain is constructed, and grid units are divided; carrying out topological optimization calculation based on a multi-objective function considering contact stress distribution, and iteratively optimizing the relative density of grid cells by adopting an SIMP method; and according to the obtained topological configuration of the sealing structure, multiple sealing structure design is carried out, a three-dimensional entity model is constructed, and the sealing performance is verified through finite element analysis.

The invention relates to the field of construction planning visualization, in particular to a construction planning visualization method and system for a refuse transfer station. The method comprises the following steps: acquiring a satellite positioning map and a refuse transfer station design drawing of a to-be-developed area; image detail reconstruction is carried out on the satellite positioning map, road space distribution fitting is carried out, and a regional road distribution network is constructed; performing surrounding building positioning calculation on the detail optimization reconstruction satellite image based on a regional road distribution network, performing an optimal site selection decision, and extracting an optimal address region image; carrying out transfer station key feature point identification on the refuse transfer station design drawing, then carrying out three-dimensional point cloud modeling, and constructing a transfer station three-dimensional structure model; and according to the optimal address area image, carrying out corresponding foundation accurate matching on the transfer station three-dimensional structure model, carrying out spatial positioning mapping, and constructing a transfer station address twinborn model. According to the method, the operation efficiency of the transfer station is improved, and the rationality of building planning is enhanced.

The invention provides a building measurement method and system based on an intelligent robot, and relates to the technical field of intelligent robots, and the method comprises the steps: deploying the intelligent robot to a to-be-measured building area; determining a final driving path of the intelligent robot according to the layout of the to-be-detected building area; the intelligent robot automatically runs along the final running path, and acquires three-dimensional point cloud data, image information and geographic position information of the building environment by using an internal sensor assembly; and processing the three-dimensional point cloud data, the image information and the geographic position information of the building environment, including point cloud splicing, denoising, registration and surface reconstruction, to generate a three-dimensional model of the building. By automatically collecting and processing data, the building three-dimensional model and the detailed measurement report are efficiently generated, the measurement precision and efficiency are improved, and the labor cost is reduced.

The invention belongs to the technical field of path planning, and particularly relates to a robot path planning method based on an RRT improved algorithm, and the method comprises the steps: obtaining environment space information needing path planning, defining parameters, and obtaining the minimum distance between a coordinate point and an obstacle; a bidirectional random tree is constructed and initialized, and sampling points are obtained through a sampling function; finding a nearest neighbor point, selecting a new node, carrying out safety distance judgment, and if not, carrying out sampling again; generating a discretization path; setting a cost function during local node expansion; performing loop iteration to generate discrete point cost, taking a minimum cost value, searching an optimal node and inserting the optimal node into the current tree; an overall path Path after local optimization is obtained; and discretizing the whole Path, setting a cost function of nodes during global planning, selecting the node with the minimum cost for reconnection, and finally obtaining a smooth and effective optimal path. According to the method, the optimality and smoothness of the path are effectively improved.

The invention relates to the technical field of electrical digital data processing, and provides a task scheduling optimization method and system based on collaborative analysis. Initializing task information of the target task, and disassembling the target task into a task set composed of a plurality of sub-tasks; performing priority ranking on the sub-tasks according to the emergency degrees, the important parameters and the resource requirements of the sub-tasks; obtaining current execution resources through a resource manager to generate an execution unit set, and generating a collaborative strategy in combination with the priority ranking of the subtasks; and according to the priority ranking and the collaborative strategy, calculating a target value of each task scheduling mode in the intelligent scheduling algorithm to select the scheduling mode, and finally arranging the sub-tasks to the corresponding execution units. Through fine task disassembly, priority ranking, real-time resource monitoring and an intelligent scheduling algorithm, the accuracy and efficiency of task execution are improved, and the flexibility and expandability of the system are enhanced.

The invention belongs to the technical field of front-end development, and particularly relates to a React framework-based tree component optimization method fusing virtualization rendering and increment rendering. Comprising the steps of S1, data preprocessing; S2, dynamic virtualization rendering: dynamically calculating a node index range in a visible area according to a real-time scrolling position of a user viewport, only rendering nodes in the range, and realizing seamless lazy loading of data through scrolling event monitoring; s3, intelligent incremental updating: identifying changed nodes through a state change comparison algorithm, and executing local re-rendering only for the changed nodes based on a component life cycle control mechanism of a React framework; and S4, lazy loading cooperative control. The method aims at solving the problems in the aspects of performance, memory management, user experience and the like when a tree component in a React ecological system processes large-scale data, and is widely applied to various Web application program development scenes needing to display and operate a large-scale tree data structure.

The invention relates to the technical field of power grid planning, in particular to a charging pile planning method based on dynamic analysis. The method comprises the following steps: obtaining electric vehicle use data in a target area, and carrying out charging demand prediction analysis according to the electric vehicle use data to obtain a charging demand prediction model; based on the charging demand prediction model, performing multi-scene simulation to obtain charging demand distribution map data, multiple scenes including different traffic flows, different driving modes and different charging demand scenes; obtaining geographic information data of the target area; and constructing a spatial analysis model according to the geographic information data, and evaluating the candidate position of the charging pile according to the charging demand distribution map data, thereby obtaining position suitability score data. According to the method, different scenes are simulated, so that the adaptability and robustness of planning are enhanced.

The present invention relates to the technical field of microfluidics, and discloses a microfluidic chip, which comprises a mixing detection module, a control valve and a power module, and the mixing detection module comprises a plurality of storage cavities, a first channel, a second channel, a third channel, a common channel, a mixing cavity and a detection cavity. According to the invention, the storage cavity for providing the reagent, the channel for fluid such as the reagent and the sample to flow, the mixing cavity for mixing and reacting the fluid such as the reagent and the sample, and the detection cavity for analyzing and detecting the sample are integrated on the mixing detection module; a control valve and a power module which are used for realizing directional flow and mixed reaction of fluid in each channel are arranged as parts which can be removed relative to the mixed detection module, so that the integration degree of the micro-fluidic chip can be improved, and the volume of the micro-fluidic chip can be reduced; in addition, the installation and replacement of the mixed detection module serving as a consumable are facilitated, and the flexibility and convenience of the micro-fluidic chip in use are effectively improved.

The invention belongs to the technical field of path planning, and particularly relates to a charging path planning method for an intelligent mobile charging vehicle, and the method comprises the steps: collecting the three-dimensional data information of a charging scene through a camera and a laser radar, and constructing a three-dimensional space model; image acquisition of a charging scene is carried out through a camera and a laser radar, and a plane navigation map is established; after the mobile charging vehicle receives a charging instruction, performing global path planning based on an improved PSO algorithm to obtain an optimal path; real-time image acquisition is carried out through a camera and a laser radar, local path planning is carried out through an improved DWA algorithm, obstacles are avoided in time, and whether a target point is reached or not is verified; and the charging manipulator grabs the charging wire to perform charging operation. According to the invention, the optimization of global and local path planning is realized, the accuracy and efficiency of path planning are improved, and the charging vehicle can safely and quickly reach the target charging position.

The invention relates to the technical field of aerospace, in particular to a vertical take-off and landing airport scheduling method and system, electronic equipment and a storage medium, and the method comprises the steps: obtaining the state information of each aircraft associated with a vertical take-off and landing airport within a preset time period; and determining at least one scheduling strategy of the vertical take-off and landing airport based on the overall structure of the vertical take-off and landing airport and the state information of each associated aircraft, and performing scheduling according to the optimal scheduling strategy. According to the method, the scheduling process can be more comprehensively optimized, the urban air traffic congestion is effectively relieved, the flight delay cost is reduced, and the overall operation efficiency of the vertical take-off and landing airport is improved.

The invention relates to the technical field of ceramics, and particularly discloses a preparation method of a bamboo charcoal pot ceramic material, which comprises the following steps: weighing the following raw materials in parts by weight: 25-30 parts of bamboo charcoal powder, 20-25 parts of quartz powder, 10-15 parts of silicon carbide, 10-14 parts of a whisker readjustment-based bonding agent, 8-12 parts of albite, 7-11 parts of a magnesium oxide-doped modified filling agent and 5-10 parts of clay. According to the bamboo charcoal pot ceramic material disclosed by the invention, the bamboo charcoal powder is matched with the quartz powder, silicon carbide, albite and clay raw materials, and the impact resistance, the heat-conducting property and the wear-resisting property of the product are harmoniously improved by adding the continuous balance agent based on whisker readjustment and the filling agent modified by doped magnesium oxide and blending and matching the raw materials; and the product has remarkable cold and heat resistance and scrubbing stability.

The invention belongs to the field of video monitoring systems, and particularly relates to a cascade-based multi-platform data synchronization method and system, and the method comprises the steps: designing an interface security mechanism of cross-platform data exchange; constructing a data synchronization service architecture, namely deploying corresponding data synchronization services at different levels of platforms to realize resource data synchronization, and supporting data synchronization of multi-level cascade or platform interconnection; performing data initialization synchronization; real-time synchronization of data change is realized; establishing a service heartbeat keep-alive mechanism; service multi-instance deployment is carried out, and efficient data processing and flexible load balancing are achieved. According to the invention, many defects of a data synchronization mechanism of an existing video monitoring system are effectively solved, and the stability, expansibility and data processing efficiency of the system are improved.

The invention provides a remote control method and system for an intelligent constant-voltage dimming power supply, and the method comprises the steps: obtaining historical working data, environment data and power supply attribute data of a plurality of dimming power supplies through a server, and generating a plurality of control strategy models according to the historical working data, the environment data and the power supply attribute data; sending the model to a remote control terminal; the remote control terminal generates a control instruction according to the control strategy model and sends the instruction to the power supply controller; the power supply controller adjusts working parameters of the dimming power supply according to the instruction; monitoring the working state of the dimming power supply in real time, acquiring working monitoring data, and transmitting the working monitoring data to the remote control terminal; and the remote control terminal generates a new control instruction and sends the new control instruction to the power supply controller in combination with the working monitoring data and a preset dimming curve, and the power supply controller adjusts working parameters of the dimming power supply according to the new instruction. According to the scheme of the invention, through an intelligent control strategy and a dynamic adjustment mechanism, efficient, energy-saving and safe remote dimming control can be realized, and the user experience and the reliability of equipment are improved.

The invention relates to multi-mode signal processing, and provides a signal processing method of a computer system. The method comprises the following steps: acquiring different modal signal data by using a plurality of sensors and performing timestamp synchronization; a depth time sequence alignment network and a multi-layer dynamic time warping algorithm are utilized to ensure signal time consistency; multi-modal signal features are extracted and fused through a multi-stream depth feature extraction network and a cross-modal attention mechanism; the system adopts a dynamic convolution kernel generation and meta-learning technology to carry out adaptive signal processing; noise suppression and signal optimization are carried out by using a multi-mode noise reduction auto-encoder and a generative adversarial network, and parameters are optimized and processed through closed-loop feedback control and reinforcement learning strategies. According to the method, synchronization, fusion, adaptive processing, noise suppression and real-time feedback control of multi-mode signals are realized, and the method has the advantages of high precision, high robustness and real-time performance.

The invention discloses an intelligent door and window control method and system based on indoor environment analysis, and relates to the technical field of door and window control, in the operation process of the system, temperature, humidity, illumination conditions and noise conditions are collected in real time through sensors, preference settings and operation historical records of a user are collected through voice recognition and gesture recognition, and the user experience is improved. Technical parameters provided by door and window manufacturers are used as a first data set, a second data set and a third data set to carry out preprocessing, analysis and extraction, preference setting and habits of users are recognized, an intelligent door and window control index Znkz is obtained through calculation, and the intelligent door and window control index Znkz is obtained according to indoor environment parameters and user preference information. The intelligent door and window control index Znkz is compared with a preset standard threshold value M and a preset standard threshold value N, the current environment state and user requirements are evaluated, a door and window control strategy is made, the opening and closing states of doors and windows are controlled according to instructions of the decision logic module, and a user interface used for interaction is provided.

The invention relates to a DID-based block chain data sharing and security verification method. The method comprises the following steps: a user generates a unique real-name DID through multi-factor identity authentication, generates multiple groups of public and private key pairs in an application process, and stores private key fragments in a decentralized network by adopting a secret sharing technology; a real-name DID is used as a unique user account on the block chain, and data sharing and security verification are carried out in combination with a deep learning model and an adaptive zero-knowledge proof mechanism; when the private key is lost, a public and private key pair is regenerated through biological characteristics and equipment fingerprint verification; and cross-chain data sharing and security verification are realized by using an intelligent contract and an inter-chain communication protocol, and identity authentication and data operation processes of the user on different block chains are simplified.