147results about How to "Improve data processing capabilities" patented technology

The invention discloses a transformer substation unmanned aerial vehicle autonomous inspection system which comprises an unmanned aerial vehicle platform, a three-dimensional modeling module, an inspection route setting module, an autonomous inspection module, a mobile monitoring platform, an image acquisition module, an image processing module, an alarm module, a visualization module, a data storage module and a wireless communication module. Wherein the three-dimensional modeling module comprises laser radar equipment and three-dimensional modeling software, the routing inspection route setting module is used for setting different routing inspection routes according to different routing inspection modes and corresponding routing inspection rules, the autonomous routing inspection module comprises a navigation system and a positioning base station, and the mobile monitoring platform comprises a remote controller and vehicle-mounted charging equipment. The image processing module is used for processing and analyzing different types of collected images and different purposes of collected images by using different algorithms so as to timely discover abnormity and give an alarm; the method has the advantages of being good in inspection abnormity processing effect, good in positioning effect, convenient to use and good in data processing effect.

The invention relates to the technical field of medical instruments, in particular to an electromagnetic ultrasonic device for treating osteoporosis, which comprises a bed body, an electromagnetic ultrasonic probe, a data acquisition module, a data processing module and an artificial intelligence analysis module, an ultrasonic treatment assembly and an electromagnetic treatment assembly are integrated in the electromagnetic ultrasonic probe; the ultrasonic treatment assembly emits ultrasonic waves and transmits the ultrasonic waves to bones through soft tissues for ultrasonic treatment; the electromagnetic treatment assembly generates an alternating electromagnetic field to stimulate bone cells; physiological signal data are analyzed in real time through an artificial intelligence algorithm, physiological state changes are predicted, output parameters of PEMF and LIPUS are automatically adjusted to adapt to individual physiological differences, and personalized treatment is achieved.

The invention discloses an intelligent robot multi-task full-autonomous management method supporting environment interaction. The system is applied to an application software architecture of a robot, and the architecture comprises a main module, a data acquisition module, a monitoring module, an image sending module, a sensing planning module, a moving module, a view finding module, a visual navigation module and a data sending module. The method comprises the following steps: determining task types of a main module, a data acquisition module and a monitoring module as normal tasks, and determining task types of other modules as abnormal tasks; the data acquisition module is used for acquiring measurement data sensed by the sensor in real time and storing the measurement data; monitoring an instruction sent by the outside in real time by using a monitoring module; according to a preset scheduling cycle, judging whether the module of which the task type is an abnormal task meets a triggering condition or not by utilizing the main module; if yes, enabling each triggered module to execute a corresponding task; and if not, keeping each untriggered module in a blocked state and waiting for triggering. The execution efficiency of the robot can be improved.

The invention discloses an intelligent management and control system and method for a water-based sodium-ion battery energy storage power station, and relates to the technical field of new energy, and the system comprises a data collection and monitoring module, a fault diagnosis and early warning module, an automatic power generation control module, an energy management system, a safety management module, a maintenance and operation management module, and a user interface and report module. According to the intelligent management and control system for the water-based sodium-ion battery energy storage power station, by introducing an advanced machine learning algorithm and enhanced data processing capability, the intelligent management and control system for the water-based sodium-ion battery energy storage power station can realize more accurate real-time monitoring and faster response capability, so that the operation efficiency and safety of the power station are remarkably improved; operation and maintenance cost is reduced, and stability and reliability of the power grid are enhanced. Besides, the optimal management of the system can deal with market changes more effectively, the economic benefits and environmental sustainability of the power station are improved, and important support is provided for energy transformation.

The invention relates to a distributed self-adaptive signal control method considering downstream traffic pressure conduction influence, which comprises the following steps of: estimating the number of queuing vehicles at an entrance lane of a downstream intersection to obtain real-time information of a downstream traffic state; constructing a signal control agent considering the body and traffic states of a plurality of downstream intersection entrance lanes, bringing the number of queuing vehicles into an input state and a reward function of the agent at the same time, and covering all possible signal phase combinations in an action set; a correction coefficient is introduced to adjust a control scheme selection strategy of the intelligent agents, a deep reinforcement learning framework based on a near-end strategy optimization algorithm is constructed, and the intelligent agents continuously optimize the control strategy through a distributed training method; and outputting an optimal control scheme by using the trained intelligent body, and adaptively controlling the intersection signal lamp. Compared with the prior art, the method can achieve the coordination control optimization of the traffic of the whole road network under the condition that only a small number of agents are deployed in the road network.

The invention discloses a trusted system for realizing digital asset right confirmation through an agricultural block chain technology, and belongs to the technical field of computer programs. User data verification, data storage, data right confirmation, data cleaning (redundancy), data comparison and data classification operations are realized in a distributed bookkeeping mode, data storage in a data lake is realized, the stored data is subjected to ownership certification, data distribution of digital asset right confirmation is carried out on the data (group) subjected to right confirmation certification, and data distribution is carried out on the data (group) subjected to right confirmation certification. A verification algorithm proves ownership, use right and management right of data assets, ownership confirmation of the data is achieved, traceable trace information is generated, and records generated in the test process comprise the whole process node of user operation. The core algorithm adopts the most advanced computer algorithm model to build the whole system in the aspects of safety, data intelligent classification, data cleaning and data right confirmation, and it is ensured that the trust of a user to the system in the using process reaches 100%.

The invention discloses an AI computing power enabling subsystem which comprises heterogeneous computing architecture software used for supporting development of self-defined operators of developers; the AI framework software is used for being provided for the step 2 to construct the AI large model, and the AI computing power enabling subsystem is set to be in a mode of combining the heterogeneous computing architecture software and the AI framework software, so that the capability of each functional unit of the heterogeneous computing architecture, the capability of each functional unit of the AI framework, the capability of each functional unit of the heterogeneous computing architecture and the capability of each functional unit of the AI framework can be simply and effectively realized. According to the method, the AI computing power enabling engine is comprehensively formed according to the comprehensive performance optimization scheme of the heterogeneous computing architecture and the AI framework, the data processing capacity of an AI chip can be optimized, the throughput rate of an AI computing cluster subsystem is increased, and developers are helped to improve the development and training efficiency. According to the AI computing power enabling subsystem, through the arrangement of heterogeneous computing architecture software and AI framework software, a developer can be effectively enabled to focus on adjustment, optimization and improvement of an artificial intelligence algorithm.

The invention discloses a laboratory operation table with a poison gas leakage protection function, relates to the technical field of laboratory equipment, and aims to solve the problems of poison gas monitoring lag, monitoring blind area and lack of real-time risk assessment in an existing laboratory. The operation table comprises a main experiment table, a poison gas sensor module, a data acquisition module, a central control system, an alarm module and a gas exhaust structure. The poison gas sensor module monitors the poison gas concentration around the experiment table in real time, the data acquisition module transmits monitored data to the central control system, and the system calculates a poison gas risk index through a specific algorithm and triggers an alarm when the poison gas risk index exceeds a safety threshold value. The system also has a poison gas leakage prediction function, and a laboratory ventilation system can be intelligently adjusted to reduce risks. The display and recording module provides real-time monitoring and data archiving functions and supports remote monitoring and data analysis. By integrating multiple functional modules, comprehensive protection of laboratory poison gas leakage is achieved, and the safety and adaptability of the laboratory environment are improved.

The invention discloses a photovoltaic power generation energy efficiency analysis method and device suitable for a cigarette factory and a storage medium, and belongs to the technical field of photovoltaic power generation. The method comprises the following steps: acquiring historical generating capacity data and real-time monitoring data of a photovoltaic power generation system; inputting the historical generating capacity data and the real-time monitoring data into the trained gradient boosting tree prediction model for generating capacity prediction, and obtaining the theoretical generating capacity of the photovoltaic power generation system in a future period of time; acquiring the actual generating capacity of the photovoltaic power generation system in the corresponding future time period; the actual generating capacity and the theoretical generating capacity are compared and analyzed, and energy efficiency evaluation is completed; wherein on the basis of a countercurrent protection data rejecting mechanism, if the real-time monitoring data is in a countercurrent protection state, the related real-time monitoring data is rejected. According to the method, historical data, real-time monitoring data and a machine learning algorithm are combined, and accurate evaluation of the energy efficiency of the photovoltaic power generation system is realized through accurate power generation capacity prediction and a countercurrent protection data rejection mechanism.

According to the FPGA dynamic allocation device and method based on the server cluster, the field programmable characteristic of an FPGA can be greatly utilized, FPGA hardware is rewritten in real time, and the FPGA resource utilization rate and the operation efficiency of a server are greatly improved. The system comprises a data acquisition module, a controller, a first memory, a second memory and an FPGA device, the data acquisition module collects information, wherein the information comprises current time, user access habits, current server resource consumption conditions and to-be-executed task contents; the first memory stores FPGA engineering files in a binary code stream form, and each engineering file is a solution for accelerating a demand scene of a server cluster; the second memory stores an instruction program, and the instruction program directs the controller to download a specified FPGA project file into a specified FPGA device; and the controller downloads the FPGA project file to a specified FPGA device.

The invention relates to the technical field of electronic expansion valve control, and particularly discloses an electronic expansion valve control method based on a deep dynamic fuzzy neural network, and the method comprises the steps: obtaining the operation data of a heat pump unit; normalizing the operation data of the heat pump unit to obtain normalized operation data of the heat pump unit, and dividing the normalized operation data of the heat pump unit into a training set and a test set; constructing a deep dynamic fuzzy neural network model, and optimizing various parameters of the deep dynamic fuzzy neural network model by using a genetic algorithm and the data in the training set to obtain a trained deep dynamic fuzzy neural network model; and inputting data in the test set into the trained deep dynamic fuzzy neural network model for prediction so as to output an optimal control strategy of the electronic expansion valve. The deep dynamic fuzzy neural network model is used for effectively controlling the electronic expansion valve, so that the overshoot of the heat pump system is small, the response speed is high, and the operation performance of the system is improved.

The invention relates to the technical field of integrated energy system control, in particular to an integrated energy system monitoring control method and an operation system, data is collected in real time, data preprocessing is carried out, a distributed computing architecture is utilized, data collection tasks are dispersed to a plurality of computing nodes, and a memory carries out classified storage on the data; the database server analyzes and processes the data, and establishes and optimizes an economic operation mode optimization model SOM and a safe operation mode optimization model EOM; and the optimized control scheme model parameters are fed back to a control end in real time, the scheme parameters are analyzed and calibrated and fed back to a processor, and the processor issues a detailed operation parameter command to the energy consumption equipment, so that the energy consumption equipment adjusts the operation parameters to achieve an optimized operation state. And the data processing capability, the communication reliability and the data storage and management efficiency of the system are improved, so that the efficient, stable and optimized operation of the comprehensive energy system is ensured.

The invention relates to the technical field of intelligent manufacturing and data processing, in particular to a multi-level simulation optimization and quality control method and system for a production process, and the method comprises the steps: carrying out the intelligent analysis of a production task through an adaptive neural network, and generating task function data; carrying out multi-level simulation optimization on the geometric dimension, the material performance and the production process based on the task function data; the simulation optimization result data and the task function data are stored in a block chain, and data verification and processing are performed through an intelligent contract; a quality control instruction is generated based on the simulation optimization result and the task function data, the state of the production line is monitored in real time, and dynamic adjustment is carried out; through multi-level simulation optimization and intelligent quality control, the efficiency of the production process and the product quality are remarkably improved.

This specification provides a data processing method, device and computing device based on a brain-like accelerator card. Before specific implementation, the brain-like accelerator card can be installed on the target computing device according to the preset installation rules; then, according to the preset construction rules, a program container image that matches the brain-like accelerator card and is compatible with the host machine's environment, software and hardware resources, permissions, etc. is prepared. During specific implementation, multiple associated algorithms related to the requested target data processing are first determined; then the image identifiers of the corresponding multiple target algorithm application container images are determined; based on the image identifiers of the multiple target algorithm application container images, a target computing device deployed with a brain-like accelerator card is constructed and called according to the target image parameter group, and target data processing is performed by running multiple target algorithm application container images. This can simplify the installation and use process of the brain-like accelerator card, and use the brain-like accelerator card to efficiently and accurately complete target data processing.

The invention provides an article transportation detection method and device, electronic equipment and a storage medium, and the method comprises the steps: carrying out the information configuration according to the configuration specification file and information size of the target interface information of all operation equipment on a whole logistics line, and generating corresponding target configuration information; monitoring the working state of each operation device on the whole logistics line in real time, and determining an upstream device and a downstream device in a to-be-transferred state; detecting information of an interface to be detected between the upstream equipment and the downstream equipment by using the target configuration information; and if the to-be-detected interface information passes the detection, executing article transportation between the upstream equipment and the downstream equipment. The logistics area control system is used for monitoring, the data monitoring precision is improved, the target configuration information is used for detection, the data processing capacity is improved, goods are transported only after detection, and potential risks are avoided.

The application provides an AI computing power allocation method, system, device, storage medium and program product, and relates to the technical field of data processing. The AI computing power allocation method determines the corresponding target AI algorithm model based on the service demand of the target reasoning service in real time, and then dynamically matches the target computing power resource used to load the target AI algorithm model by combining the processing demand of multiple AI algorithm models, the preset adaptability rules of various heterogeneous computing power resources, and the current use state of the various heterogeneous computing power resources, so as to realize dynamic allocation of AI computing power resources, avoid computing power resource overload or idling, improve computing power resource utilization, reduce task reasoning delay, and thus improve data processing capability.

The invention provides a data processing device. The data processing device comprises a housing; the signal processing piece is arranged in the shell; the display assembly comprises a display module and a display frame, the display module is arranged on the display frame, the display frame is rotatably arranged on the shell, so that the display assembly has an unfolded display position and a folded closing position, and the display module is electrically connected with the signal processing part; the adjusting assembly comprises a rotating part and a telescopic mechanism, the rotating part is rotatably arranged on the shell, the display frame can drive the rotating part to rotate when rotating, the first end of the telescopic mechanism is movably arranged on the rotating part, and the second end of the telescopic mechanism can move downwards. The distance between the side, provided with the display assembly, of the shell and the supporting face is increased. Through the technical scheme provided by the invention, the problems that the heat dissipation efficiency of a processing device in the related technology is low, a gap between the bottom of the processing device and a desktop is small when a display screen is turned on, and heat dissipation is affected due to no air circulation can be solved.

The utility model provides a vehicle machine, a vehicle machine system and a vehicle. The utility model relates to the technical field of vehicles. The vehicle machine comprises a micro-control unit, a tire pressure monitoring module, a power supply module, a communication module, an antenna module, a central processing unit, an information interaction module, a video module and an audio module, the micro-control unit is in communication connection with the tire pressure monitoring module; the micro-control unit is in circuit connection with the power supply module; the micro-control unit is in communication connection with the communication module; the communication module is in communication connection with the antenna module; the communication module is in communication connection with the central processing unit; the micro-control unit is in communication connection with the central processing unit; and the central processing unit is in communication connection with the information interaction module, the video module and the audio module, so that the efficiency of information transmission between the vehicle machine and the vehicle networking communication box is improved.

The invention discloses an asynchronous online control method, which comprises the following steps of: S1, initializing an equipment end, and entering a to-be-distributed network state; s2, the mobile terminal performs network distribution by adding equipment; s3, after receiving the distribution network information, the equipment end is connected with the double cloud platforms in sequence, judges whether the connection is successful or not, and correspondingly and dynamically returns to the step S1 based on at least two levels of judgment results until the double cloud platforms are connected successfully; s4, adding equipment by using an applet; and S5, using a multi-platform control device. According to the asynchronous online control method, the Jingdong cloud is connected firstly, and then the long rainbow cloud is connected, so that the problem of insufficient resources caused by repeatedly using mqtt to apply for resources is solved, three-in-one control is realized, three-in-one of double clouds and an applet combines the advantages of two cloud platforms, and higher compatibility and expansibility are provided by using the flexibility of the applet, so that the asynchronous online control is realized. And better resource integration can be realized, and the data processing capability is improved.

The present invention discloses a method, device, equipment and fan muffler design for a server fan, including: determining a target insertion loss spectrum after the muffler is installed at a preset position according to the characteristic frequency of the server hard disk; the muffler includes a sound cavity; obtaining a correction curve, the correction curve being an insertion loss spectrum curve after a shell without a sound cavity is installed at a preset position; obtaining a target transmission loss spectrum of the muffler according to the target insertion loss spectrum and the correction curve; obtaining the size parameters of the muffler according to the target transmission loss spectrum. The size parameters of the designed muffler can accurately match the noise component of the hard disk resonance frequency, effectively solve the impact of noise resonance on hard disk performance, enable the hard disk to operate in a low-noise environment, and avoid the influence of resonance on the normal operation of the precision components in the server hard disk.

Embodiments of the present application provide a data processing method and device for low-resource languages, equipment and storage medium. The method comprises: obtaining prompt data to be processed corresponding to a first language; inputting the prompt data to be processed into a preset target language model to obtain a corresponding processing result; wherein the target language model is obtained by training a preset language model based on a first loss, a second loss and a third loss; the first loss is used to indicate the adjustment of the parameters of a first semantic alignment key layer in the preset language model; the second loss is used to indicate the adjustment of the parameters of a second semantic alignment key layer in the preset language model; the third loss is used to indicate the adjustment of the parameters of a plurality of network layers contained in the preset language model, and the third loss is determined based on the difference between the predicted language response text output by the preset language model and the corresponding response text label. In this way, the data processing performance of the model for low-resource languages can be significantly improved.

The utility model belongs to the technical field of taper hole measurement, and particularly relates to a portable railway vehicle taper hole measuring instrument. The device mainly comprises two dial gauges which are respectively installed on a T-shaped workpiece, the T-shaped workpiece comprises a first installation rod and a second installation rod, and the dial gauges can be installed on a long-dimension section or a short-dimension section through fastening bolts and are used for measuring standard long and short taper holes. Besides, the first mounting rod comprises a fixed sleeve and a movable rod, and the movable rod can be inserted into the fixed sleeve and locked through a limiting knob so as to adapt to measurement of taper holes with different lengths. In order to meet the measurement requirements of different apertures, an extension rod can be installed on the measuring rod of the dial indicator. According to the utility model, the selected dial indicator has a Bluetooth wireless transmission function, so that manual intervention is reduced, and a worker can more intuitively know the measurement result of the taper hole. The device has the advantages of simple structure, convenient operation, high measurement precision and the like, and is suitable for on-site rapid measurement of railway vehicle taper holes.

This invention discloses a joint optimization method and system for task offloading and resource allocation based on SAGIN. It collects task and scheduling information through a SAG-IoT system; utilizes the task data and scheduling information to achieve optimal association between UAVs and IoT devices based on a matching game algorithm, and makes optimal decisions for task offloading to maximize the computational performance of the SAG-IoT system; based on optimal association, optimal task offloading decisions, and maximizing the computational performance of the SAG-IoT system, it constructs an online offloading framework based on deep reinforcement learning, constructing a path from input X(t) to optimal action x. * The low-complexity mapping strategy (t) is based on repeated interactions between different modules and a random environment, iterating and running sequentially to achieve joint optimization of task offloading and resource allocation. This invention achieves optimal computational performance while stabilizing the system queue. In addition to utilizing binary computation offloading, the optimization framework can also be extended to online partial computation offloading strategies consisting of multiple independent subtasks.

The invention discloses an event execution process creation method and device, equipment, a medium and a product. The method comprises the steps of obtaining a plurality of process nodes on an event execution process in response to an operation of triggering and creating the event execution process by a user; for a process node of the event execution process, creating a node control corresponding to the process node; acquiring node data corresponding to the node control; the node data comprises a control name, a control type, input data, output data and a precursor control name; storing the node data in a storage space corresponding to the node control according to a preset format; according to the input data, the output data and the precursor control name corresponding to each node control, determining a calling relationship between different node controls; and associating each node control based on the calling relationship to generate an event execution process. According to the embodiment of the invention, the low-code data platform is flexibly arranged, the data processing capability is improved, and the low-code data development accuracy is improved.

The invention discloses a genetic correlation algorithm between animal combined gametes, which comprises the steps of collecting pedigree data of animal individuals, acquiring phenotype data of the individuals, preprocessing the pedigree data, associating the phenotype data with the pedigree data, constructing input data required by genetic correlation analysis between the gametes, and deploying a distributed computing framework. The method comprises the steps of designing and building a distributed storage system, developing a parallelized genetic correlation algorithm, distributing genetic correlation calculation tasks to a plurality of nodes in a distributed calculation cluster for parallel processing, integrating and summarizing genetic correlation results obtained by calculation of the distributed calculation nodes, and performing statistical analysis and visualization on the results. Performance optimization and tuning are carried out on a distributed computing system, an algorithm is tuned and optimized according to actual requirements, indexes such as computing complexity and memory consumption are optimized, the effect of a breeding scheme is monitored and evaluated, and adjustment and optimization are carried out according to requirements.

The invention provides an antenna configuration optimization method and device, a storage medium and a program product, relates to the technical field of communication, and is used for reducing the power consumption of terminal equipment in a beam scanning process. The method comprises the following steps: traversing a preset antenna number configuration scheme set, and determining an antenna number configuration scheme meeting a constraint condition as an optimal antenna number configuration scheme; the constraint condition comprises the lowest energy consumption of the terminal equipment in the target coverage area of the base station in the beam scanning process, and the signal quality of the terminal equipment in the target coverage area of the base station is greater than or equal to a preset signal quality threshold value; and optimizing the number of antennas of the base station based on the optimal antenna number configuration scheme.

The invention discloses a TSN management method and device based on software definition, a medium and equipment, and aims to realize centralized configuration and scheduling of a TSN switch by utilizing a northbound interface and a southbound interface through coordination of a centralized controller and the TSN switch. The centralized controller allows remote access and configuration parameter modification through a northbound interface so as to generate a specific configuration instruction and a scheduling strategy, and it is ensured that the network carries out efficient scheduling and bandwidth allocation according to real-time requirements; and the southbound interface is used for issuing the configuration instructions to the switch and executing functions of clock synchronization, network state monitoring, forwarding and control separation and the like. In this way, seamless connection between different network technologies is achieved, the certainty of data transmission is guaranteed, and meanwhile the data processing capacity and the utilization efficiency of bandwidth resources are improved.

The invention relates to an intelligent driving simulation data storage method and device oriented to a hybrid memory and a medium, and belongs to the technical field of intelligent driving. The method comprises the steps that simulation data are graded based on attributes of the simulation data, and grades corresponding to the simulation data are obtained; classifying the simulation data based on the access frequency of the simulation data to obtain types corresponding to the simulation data; and storing the simulation data in the DRAM or the NVM based on the preset weight, the grade and the type. According to the intelligent driving simulation data storage method oriented to the hybrid memory provided by the invention, the limitation on intelligent driving simulation under a single memory can be made up by utilizing a hybrid memory architecture formed by two storage media, namely, the DRAM and the NVM, and utilizing respective advantages of different storage media, so that the intelligent driving simulation can be realized. By optimizing the data storage strategy, the data processing capability of intelligent driving simulation is improved, so that the performance and efficiency of the simulation system are improved.

An online monitoring system for the health of municipal pipe networks based on big data, the system includes sensors for real-time collection of data on water flow, pressure, water quality, and pipe vibration, the sensors being installed at key nodes of the municipal pipe network; an integrated system for integrating data from multiple sources including satellite data, geographic information system GIS, and municipal maintenance records; machine learning and data mining techniques are used to build a baseline model of the health of the pipe network based on historical data; artificial intelligence algorithms are used to analyze the collected real-time data to predict potential problems and maintenance needs of the pipe network; a real-time monitoring platform is used to display the current status of the pipe network and evaluate its health, and when an abnormal state is detected, the system automatically sends an early warning message to the maintenance department. The present invention can accurately identify potential problems and issue alarms in a timely manner. With detailed reports and recommended measures generated by natural language processing technology, managers can quickly understand the problem and take appropriate actions.

The invention relates to the technical field of digital microfluidics, and discloses a hybrid digital microfluidics system which comprises an upper computer, a power supply, a main control unit, a programmable voltage source, a multi-way switch, a digital microfluidics chip and a micro piezoelectric pump, the upper computer is used for generating an activation signal and a liquid drop pumping signal; the main control unit is used for responding to the activation signal and activating the electrode array corresponding to the activation signal; the micro piezoelectric pump is used for responding to a liquid drop pumping signal and enabling liquid drops to flow into the digital micro-fluidic chip through the microneedle and to be adsorbed on the activated electrode array. According to the invention, the speed of an experiment and a production process is increased through an automation technology, meanwhile, errors caused by manual operation are reduced, the consistency of operation and the repeatability of a result are ensured, and the effect of liquid drop pumping in digital microfluidics is improved.