675results about How to "Rapid deployment" patented technology

The invention belongs to the technical field of image classification neural networks, and discloses a lightweight image classification neural network architecture system based on knowledge distillation. The invention provides a lightweight image classification neural network architecture system based on knowledge distillation. The lightweight image classification neural network architecture system comprises a data set preprocessing module, a teacher model preprocessing module, a subnet model construction module, a personalized training module, a real loss calculation module, a distillation loss calculation module, a total loss calculation module and a student model construction module. The invention provides a lightweight neural network architecture system based on knowledge distillation, and designs a brand new training mode by using the superiority of knowledge distillation for teacher model weight extraction: the knowledge distillation of teacher and student models is combined with a deep compression method; the system for constructing the lightweight network can be used for training various complex image classification neural networks so as to improve the network performance.

The invention discloses a short text clustering method and device based on a large language model, and belongs to the technical field of natural language processing, and the method comprises the steps: converting a short text into vector representation, and carrying out the preliminary clustering of the vector representation through a clustering algorithm, and obtaining an initial category; for all the corresponding short texts in each initial category, generating an abstract by using a large language model, generating a plurality of theme titles for summarizing the core meanings of the texts according to the abstract, respectively taking the theme titles as sub-titles, inputting the plurality of sub-titles into the large language model, and carrying out theme combination to obtain a parent title, constructing the parent title and the child titles into a hierarchical theme system; the large language model allocates to-be-classified short texts to one or more categories according to the hierarchical topic system to complete short text clustering; and performing quality evaluation and error pattern analysis on a short text clustering result to optimize a clustering algorithm and a large language model. According to the method, the theme of the short text can be automatically found and classified, and the classification accuracy and efficiency are improved.

The invention discloses an ecological environment commanding and dispatching system and method based on audio and video fusion, and relates to the technical field of ecological environment dispatching. The commanding and dispatching platform is in communication connection with a data acquisition module, a data preprocessing module, an event detection and identification module, a severity evaluation module, a commanding and dispatching module and a resource management module, and all the modules are in electric signal connection; the data acquisition module is used for collecting real-time audio and video data from various sensors and monitoring equipment which are deployed in advance. According to the invention, through real-time monitoring and automatic detection technologies, abnormal events are identified at the first time, and an early warning mechanism is started immediately, so that compared with traditional manual inspection, the time for finding the abnormal events can be shortened, in addition, the automation characteristic of the system reduces delay caused by human factors, and the system is more convenient to use. Therefore, resources and personnel can be quickly mobilized in emergency, and the influence of events can be effectively controlled and relieved.

The invention discloses a dam safety monitoring agent system based on a multi-dimensional large model and digital twinning, and belongs to the technical field of safety monitoring of water conservancy and hydropower engineering. According to the method, a cognitive decision kernel is used as a core innovation module, multi-source data is collected by relying on a sky-ground hydraulic engineering integrated sensor network, cross-modal data fusion and anomaly recognition are achieved through a multi-dimensional large model cluster, and multi-physics coupling simulation is completed in combination with a digital twinborn body; the cognitive decision kernel generates an optimal combination scheme through case retrieval and measure unit adaptation degree calculation, a control instruction is output after digital twin rehearsal verification, and finally closed-loop control of dam safety real-time early warning, autonomous decision making and efficient disposal is achieved through an autonomous response mechanism. The problems of data island, passive response, expert dependence and the like of a traditional monitoring system are solved, the dam safety management intelligent level and the emergency response capability are remarkably improved, and the method has wide engineering application value.

The embodiment of the invention relates to the field of large model facilities, and discloses a Serverless large model reasoning service system, method and equipment and a medium. Receiving an inference service creation request sent by a user, and forwarding the inference service creation request to a corresponding cluster; processing the north-south traffic of the cluster; converting the reasoning service creation request into an object, and configuring a running environment; according to the object, a Pod is created, the Pod is used for controlling a model service workload, the Pod comprises a user container, and the user container is constructed based on a basic mirror image comprising an operating system, a Supervisor and a Docker and is used for running a large model service; and the queue agent is responsible for processing routing, load balancing and request queuing of an incoming request based on a lightweight agent Sidecar. The technical problem that large model reasoning service deployment is difficult can be solved at least.

The invention relates to a near-electricity construction operation safety early warning method and system, and belongs to the field of near-electricity construction operation equipment early warning, and the method comprises the steps: scanning a power transmission and transformation project construction site through three-dimensional laser, and forming a high-precision laser point cloud three-dimensional data model; quickly dividing an electrified body and a non-electrified body in the three-dimensional laser point cloud model, and carrying out attribute hooking on the safe distance range and the electrified body; rTK positioning sensors are installed on an operator and a construction machine, and high-precision real-time positioning and spatial distance measurement of the operator and the machine are achieved through Beidou RTK; real-time space distances between operators, machines and electrified bodies are monitored on the basis of a safety distance detection algorithm, reminding in different modes such as safety warning and prohibition warning is set according to requirements of safety operation regulations, and it is ensured that the operators, machines and the like keep enough safety distances from the electrified bodies.

The invention discloses an emergency fire fighting question answering method and system based on the AI large language model technology and a storage medium, and relates to the technical field of artificial intelligence, the emergency fire fighting question answering system comprises a front-end module, an AI preprocessing thread pool, a knowledge base module and a large model calculation engine module, the AI preprocessing thread pool receives a service request sent by the front-end module, and sends the service request to the AI preprocessing thread pool; different task threads are distributed, a knowledge base of a corresponding region category is automatically called according to the region category input by a service request to perform content similarity retrieval, knowledge content data obtained through retrieval and the corresponding service request are sorted and then uniformly sent to the large model calculation engine module supporting parallel processing to perform analysis and calculation, and the large model calculation engine module is used for performing analysis and calculation on the knowledge content data and the corresponding service request. By using the technical means of the invention, the user does not need to think what the keyword of the current question is, and can completely organize the question, directly ask the question, automatically query the local professional knowledge base and give professional and accurate answers according to the actual situation of the site, so that real barrier-free communication is realized.

The invention relates to a simulation test platform for a 1553B bus of a spacecraft, which is suitable for stand-alone test and system test of a 1553B bus interface of a satellite model, and comprises an application layer, a communication layer and a data interface connected with the application layer and the communication layer, the application layer comprises a main control module, a database module and a user interaction module; the communication layer comprises a non-periodic data communication module and a periodic data communication module. The method can be suitable for ground tests of multiple satellite models at the same time, the research and development cost is saved, great convenience is brought to the satellite ground tests, and therefore the development progress of the satellite models is effectively guaranteed.

The invention provides a virtual power plant distributed data anomaly diagnosis method based on a deep neural network, and relates to the technical field of artificial intelligence, and the method comprises the steps: obtaining the multi-modal data of each distributed energy of a virtual power plant, and obtaining the processed distributed data; modeling each node of the virtual power plant and the relationship thereof into a graph structure to obtain a multi-time-scale spatio-temporal feature vector; pre-training is carried out by constructing a self-supervised learning task, and effective features between different time scales and modal data are extracted; generating a normal data distribution model by using a generative adversarial network, and summarizing abnormal data samples into a comprehensive data set; obtaining a multi-task optimization model through sharing characteristics among tasks; a final optimized anomaly response system is obtained, and then the task of virtual power plant distributed data anomaly diagnosis is completed through the anomaly response system. According to the method, efficient anomaly diagnosis and response processing of the distributed data of the virtual power plant are realized, and the method has remarkable technical advantages and practical application value.

The invention discloses a concentrator dynamic routing method and system. The method comprises the following steps: storing an equipment code of each collector to a remote monitoring terminal; the concentrator obtains the equipment coding information of all collectors in the jurisdiction of the concentrator from the remote monitoring terminal; constructing a hierarchical routing network according to the broadcast response condition between the concentrator and the collector; and dynamically selecting a relay node for a lower-layer collector according to the communication quality evaluation score. According to the invention, all collector nodes can be automatically identified and layered, and a flexible and adjustable network topology is constructed; dynamically selecting an optimal relay node by adopting a comprehensive calculation method of multi-dimensional communication quality parameters; when a communication environment or an equipment state changes, automatic reconstruction of a hierarchical routing network and dynamic optimization of a relay node are supported. The method can effectively improve the communication efficiency and network stability between the concentrator and the collector, and is widely applied to the fields of intelligent meter reading, industrial control, environment monitoring and the like.

The invention relates to the technical field of water affair management, and discloses a modularization-based intelligent water affair light application rapid building system, which comprises a template library management module, which is used for storing and managing a plurality of preset function templates, and each function template is used for executing a specific function in water affair management; the parameter configuration module communicates with the template library management module and is used for performing parameterization configuration on the selected function template according to user requirements, and the parameterization configuration comprises data source configuration, operation parameter setting and output option selection; and the system combination and deployment module is used for combining the function templates subjected to parameterization configuration into a complete application system, and deploying the application system into a running environment through a containerization technology and a Kubernetes arrangement tool. Through modular design and template library management, the system can be rapidly configured and deployed according to different water affair management requirements, the construction time of the system is greatly shortened, and the system adapts to rapidly changing business requirements.

The invention provides a two-stage training method for a lightweight Chinese-English bilingual large language model. The method comprises the following steps: step 1, collecting and preprocessing Chinese-English training data; the preprocessing process comprises special mark clearing, sensitive data clearing, data duplicate removal, advertisement removal and formatting processing; 2, performing first-stage high-resource language training, namely performing model training by using English; 3, second-stage bilingual mixed training is carried out, and the Chinese data and the English data are mixed for second-stage training by adopting language migration training; wherein the step 3 comprises the following steps: step 31, performing word list expansion; and step 32, language migration training. The bilingual processing capability can be improved.

The invention relates to the technical field of robots, and provides a Robomaster multi-sensor fusion decision-making-based sentry robot which comprises a chassis, a holder, an actuator module, a sensing module, a lower computer and an upper computer. The lower computer comprises a receiving module, a decision module, a distribution module and a motion control module; the upper computer comprises a laser radar navigation module and an image recognition processing module; the decision-making module is used for performing corresponding processing on the received data fusion robot according to the situation faced by the robot; and the distribution module is used for directly sending the received sensing data of the sensing module and the data of the judgment system to the laser radar navigation module and the image recognition processing module. According to the scheme, through multi-sensor fusion and a low-computing-power control system, a complex environment can be sensed more comprehensively, low-delay image processing and path planning are achieved, multiple independent and mutually decoupled modules are integrated, and high expansibility and stability are achieved.

The invention belongs to the field of software testing, and relates to an ROS 2 software package defect detection method based on a large language model and coverage rate guidance. According to the method, function information is extracted from a to-be-tested program, and a regular expression is used for analyzing function definition, parameter characteristics and other information; the method comprises the following steps: presetting verification standards related to a to-be-tested program, and extracting physical constraints and document constraints from the verification standards; integrating the extracted function information, physical constraint and document constraint into accurate information, filling a cue word template with the accurate information, inputting the cue word template into a large language model, and generating an initial test seed; a mutation strategy is introduced, and diversified mutation operation is performed on the generated seeds, so that test cases with higher diversity are generated; optimizing the test case by adopting a coverage rate guiding mechanism, and guiding to generate a new test case by monitoring the coverage rate in real time; through a defect verification mechanism, dominant defects such as program crash and the like can be detected, and hidden defects such as violation of physical constraints or violation of document constraints and the like can be identified.

The invention discloses a text log management method and device based on an embedded system, equipment and a medium. According to the text log management method based on the embedded system, a storage medium is provided, the storage medium is divided into storage areas, and the storage areas are divided according to partitions; the management method comprises a writing method, a quick retrieval method and a data reading method. The method can be conveniently applied to an embedded system with relatively few hardware resources, the contradiction between embedded system development and large-capacity log data storage requirements is solved, meanwhile, the requirement that field maintenance is simple and easy to use can be met, and the method can be suitable for various storage media, occupies few system hardware resources, can be rapidly deployed, and has high practicability. And the method also has the advantages of quick retrieval, sequential writing, data reading, automatic coverage, few occupied resources and the like.

The invention discloses a whole-tray warehouse-out system and method, and belongs to the technical field of cigarette manufacturing, and the system comprises a stacking robot, a cigarette carton temporary storage channel, a cigarette carton backflow channel, a latent AGV, an elevator, a tray on-line device and a whole-tray warehouse-out line; wherein the latent AGV is used for moving to a designated goods location of an ex-warehouse cache region to carry finished cigarette trays and carrying the finished cigarette trays to the tray online device, moving to a designated goods location of a target floor to carry the finished cigarette trays, descending to an ex-warehouse floor through the elevator and then carrying the finished cigarette trays to a connection platform on the same floor; then the tray is carried from the connection platform to the tray on-line device; and the whole-tray delivery line provides a conveying channel for the finished cigarette trays, so that the finished cigarette trays can be conveyed to a delivery area for whole-tray loading and delivery. According to the invention, accurate tracking and management of goods are facilitated, and the accuracy and efficiency of delivery of the whole pallet are improved.

The invention belongs to the technical field of informatization security and secrecy, and particularly relates to an encrypted optical disc illegal external connection alarm tool which comprises a recording and printing tool recorded in an optical disc in an encrypted mode and an internet detection module. And automatically associating a specific website after the recording and printing tool is opened, and judging that the compact disc is used illegally if the association is successful. According to the invention, information security management can be enhanced, the management efficiency is improved, the information security cost is reduced, comprehensive monitoring and timely alarm of the secret-related optical disk are realized, and the security and confidentiality of the secret-related information are greatly improved.

The invention discloses a distributed sonar buoy monitoring system. The system comprises a plurality of buoy monitoring nodes; the plurality of buoy monitoring nodes are deployed at different positions of a monitoring area in a distributed manner; each buoy monitoring node comprises an underwater sound data acquisition module, an underwater sound data transmission module, an underwater sound data processing module, a message transceiving module and an antenna transmission module; the underwater sound data acquisition module is used for acquiring underwater sound data in an area to be monitored and transmitting the underwater sound data to the underwater sound data processing module through the underwater sound data transmission module; the underwater sound data processing module comprises a processing unit; the processing unit is used for receiving and processing the underwater sound data and transmitting the processed underwater sound data to the message receiving and transmitting module; and the message receiving and transmitting module is used for receiving the processed underwater sound data and transmitting the processed underwater sound data to the shore-based terminal through the antenna transmission module, so that the shore-based terminal receives the processed underwater sound data. According to the invention, rapid acquisition and processing of underwater sound data in a large range are realized.

The invention discloses a data-mode-driven artificial intelligence model construction method for mineral product prediction, and relates to the field of earth science, and the method mainly comprises the steps: determining source, transportation and storage substitution indexes according to a mineralization system; assembling a multi-source earth science data set; constructing a source, transportation and storage branch artificial intelligence model; establishing a power law function between the ore deposit space distribution density and the key ore control element distance; adding the power law function into a hidden layer of the artificial intelligence model, and constructing a metallogenic mode constraint artificial intelligence model; inputting the multi-source earth scientific data set into a source, transport and storage branch artificial intelligence model, and extracting a source, transport and storage alternative index layer; and inputting the layers into a metallogenic mode constraint artificial intelligence model, and delineating a metallogenic prospective area. By implementing the data-mode driven artificial intelligence model construction method for mineral product prediction, the interpretability and generalization ability of the artificial intelligence model for mineral product prediction can be improved, and the precision of predicting the metallogenic prospective area is improved.

The invention discloses a photovoltaic-energy storage-charging multi-stage scheduling and market bidding optimization method and a photovoltaic-energy storage-charging multi-stage scheduling and market bidding optimization device. The method comprises the following steps: constructing a data-driven random environment model reflecting photovoltaic output, electricity price fluctuation and charging load uncertainty by adopting a mode of combining time sequence clustering and a non-homogeneous Markov chain based on historical operation data; modeling a scheduling and bidding problem of the optical storage and charging integrated station into a multi-stage Markov decision process model which comprises day-ahead decision and joint optimization of multiple intra-day rolling adjustment; a deep reinforcement learning algorithm is utilized to train the network, and a strategy regulation and control network which can adapt to various uncertain scenes and meet equipment physical constraints is obtained; and deploying the trained strategy regulation and control network in an energy management system to realize global coordinated scheduling and bidding of the optical storage and charging integrated station. According to the method, the economic benefit is remarkably improved, the robustness is greatly enhanced, the decision is globally coordinated and optimized, the real-time decision capability is strong, and the expandability and portability are good.

The invention belongs to the field of ocean engineering and floating body structures, discloses a modularized movable variable-structure floating body platform and an operation method thereof, and is suitable for multi-scene application of short-term or temporary operation on the sea. In the towing process of the platform, chain type arrangement is adopted, all floating body units are connected through spherical hinge connectors, water resistance is effectively reduced, towing efficiency is improved, and safe transfer is achieved through a tugboat and an auxiliary boat. After the platform arrives at a target area, the platform flexibly adjusts the floating body units through the tugboats, the auxiliary boats, the mechanical arms and the connecting rods, chain type arrangement is changed into an array type structure, stable multi-column arrangement is formed, and different operation requirements are met. Due to the modular design, the platform has high expansibility and is convenient to maintain and recombine. The marine floating body platform is flexible, low in cost and environmentally friendly, has high wind wave resistance and wide application prospects, and is particularly suitable for various temporary marine operations such as marine monitoring, equipment installation and marine emergency.

The embodiment of the invention provides an acquisition probe management system and method. The method can be used in distributed fields. The system comprises an acquisition probe deployment page management end, an acquisition proxy server end and an acquisition proxy end, the acquisition probe deployment page management end is used for providing a man-machine interaction function so as to create an operation task corresponding to operation task information based on the operation task information for an acquisition probe obtained by man-machine interaction; and sending the operation task to a collection agent server corresponding to the node, and displaying an execution state of the operation task, the acquisition agent server side is used for triggering the node to execute the operation task, and the acquisition agent side is deployed in the node; and the acquisition agent end is used for executing the operation task aiming at the acquisition probe. The method is used for achieving the effect of quickly deploying the corresponding acquisition probes to a plurality of servers and realizing unified management of the acquisition probes.

The invention discloses a defect detection system, method and device based on artificial intelligence image processing, and particularly relates to the field of image defect detection.A data acquisition module is used for obtaining image data from industrial equipment, a sensor and a camera and conducting preliminary formatting processing on the image data. The model convergence time is shortened, the utilization efficiency of training resources is improved, the generalization ability of the model is enhanced, and the performance of the model in processing a rare scene is improved; according to the method, high accuracy can be kept while computing resource consumption can be remarkably reduced, it is ensured that the defect detection system can also operate efficiently in resource-limited equipment, different hardware conditions are adapted, the application scene requirement of the system is expanded, the operation problem caused by environmental conflicts is reduced, the system safety is enhanced, and the system performance is improved. And the influence on system operation caused by external malicious software attack or resource leakage is avoided.

The invention belongs to the technical field of cloud computing, and discloses a lightweight multi-domain hyper-fusion platform construction method compatible with heterogeneous hardware resources, which adopts a lightweight hyper-fusion platform architecture compatible with the heterogeneous hardware resources, converts physical resources into virtual resources on a virtual machine based on a KVM (Kernel-based Virtual Machine), shields the difference of underlying hardware, and improves the performance of the platform. According to the method, heterogeneous storage resources are integrated based on Ceph, and storage devices of different manufacturers are integrated into a unified storage pool through a distributed storage technology without being limited by types of bottom hardware devices. Through the SDN technology, the OpenStack network service can decouple a network control plane and hardware, and unified management of different network devices is realized. Through a virtualization technology and an automatic management tool, a simplified elastic expansion solution is provided, and changes of resource demands are easily coped with.

The invention discloses a low-code platform development method and a low-code platform system, and belongs to the technical field of software development, the overall architecture design of a low-code platform is carried out based on Vue2 and TypeScript, and the method comprises the combination of modularization, data management and visual editing function modules; the system comprises a component management module which comprises a component library and user-defined component management; the visual editor is used for realizing real-time layout adjustment and attribute configuration; the user previews the modification effect in real time by dragging and adjusting the position, the size and the hierarchical relationship of the component; the data management module is used for realizing data binding, API integration and dynamic data management; and the performance optimization module comprises a virtual DOM (Document Object Model) optimization and on-demand loading mechanism. The invention provides a development environment which is high in expandability and easy to use. A complex coding process is simplified into visual operation, and cooperation between developers and non-technical users is promoted.

The invention provides a joint design method and system for water flow estimation and ship waterline monitoring, and belongs to the technical field of ship monitoring, and the method comprises the following steps: firstly, a shore-based center deploys an underwater robot and plans a motion path according to the needs of a monitoring task, and builds a water gauge data set for model training; when the underwater robot arrives at the nearby area of the ship, the underwater robot measures the water flow speed and direction by using a Doppler velocimeter, and predicts a future water flow velocity field in combination with the trajectory information of the underwater robot; meanwhile, the underwater robot collects a waterline image through an airborne camera, pre-processes the waterline image, and calculates the credibility of the waterline image; and further, the underwater robot corrects the attitude in real time according to water flow velocity field prediction and waterline image credibility, and joint estimation of the water flow and the ship waterline is realized. According to the invention, water flow estimation and ship waterline monitoring are combined, and stable and efficient omnibearing ship waterline monitoring is realized through the underwater robot.

The invention discloses an enterprise-level application development and data management system and method based on zero code SaaS, and relates to the technical field, application development demand information input by a user is obtained, and input keywords and output keywords are extracted from the application development demand information of the user; acquiring subscription and development information of components on the SaaS platform; giving keywords to the components on the SaaS platform; selecting an input component and an output component for a user; recommending an execution component to the user; the user uses the input component, the output component and the execution component to develop required applications by referring to a recommendation result of the execution component; the user does not need to purchase and maintain software, resource consumption of the user is reduced, and maintenance burden of the user is reduced; the user can quickly access and deploy the application program without installation and configuration; and analyzing the requirements of the user, and recommending an SaaS application development component which is most practical to the user in combination with subscription information of the user on the SaaS platform.

The invention discloses a low-altitude meteorological detection system, which comprises a lift-off detection subsystem and a ground receiving subsystem, the lift-off detection subsystem and the ground receiving subsystem carry out data transmission in a wireless communication mode, and a plurality of sensors are integrated on the lift-off detection subsystem. The system comprises a lift-off detection subsystem for acquiring temperature and humidity, air pressure, positioning and attitude information and transmitting the information to a ground receiving subsystem, and the ground receiving subsystem receives data transmitted by the lift-off detection subsystem and provides a visual man-machine interaction platform to realize real-time man-machine interaction. The device integrates three core advantages of reliability, flexibility and safety, ensures that the device can still work stably in an extremely severe environment without fear of wind and rain, shows strong environmental adaptability and durability, is light in overall weight, small in size, convenient to carry and rapid to deploy, can easily cope with individual soldier operation or team cooperation, and has a wide application prospect. And flexibility is realized.

The invention belongs to the technical field of unmanned vehicle control, and relates to an unmanned vehicle control method and device based on deep reinforcement learning, equipment and a medium. The method comprises the steps of obtaining environment information of an unmanned aerial vehicle, and constructing an initial state space; according to the initial state space, a deep reinforcement learning method is adopted, values of different actions in the initial state space are calculated through the initial first network, strategy selection is carried out, and an initial optimal action is obtained; a next first network is obtained according to the initial optimal action, and the unmanned vehicle moves at the same time; obtaining a next state space according to the environment information after the unmanned vehicle moves, obtaining a next optimal action through a next first network, and generating an action value set until a preset condition is met; and the environment information of the unmanned aerial vehicle is obtained again, the execution action of the unmanned vehicle is output according to the action value set, and unmanned vehicle control is realized. According to the invention, unmanned vehicle control without SLAM mapping can be realized.

The invention relates to the technical field of film permeability testing equipment, and provides a device and method for real-time determination of permeability of a compost covering film.The device for real-time determination of permeability of the compost covering film.The device comprises a first detection box and a second detection box, the first detection box is provided with a first inner cavity and a first opening, and the second detection box is provided with a second inner cavity; the first detection box is provided with a first inner cavity and a second opening, a first sensor assembly is arranged in the first inner cavity, the first detection box is provided with an air inlet communicated with the first inner cavity, the second detection box is provided with a second inner cavity and a second opening, a second sensor assembly is arranged in the second inner cavity, and the second detection box is provided with an air outlet communicated with the second inner cavity. The first opening and the second opening are oppositely arranged, and the first detection box and the second detection box are arranged in a fitting manner, so that the to-be-detected film can be clamped between the first detection box and the second detection box. The device for measuring the permeability of the compost covering film in real time has the advantages of being convenient to carry and operate, intelligent in induction, high in use flexibility and the like.