1059 results about "Web transport" patented technology

The invention relates to the technical field of cloud side end computing, and discloses a cloud side end cooperative computing resource dynamic allocation method based on task-aware migration. The method comprises the following steps: acquiring real-time load characteristics and resource demand characteristics of calculation tasks in a cloud side end system, and dividing task priority queues in combination with task type identifiers; extracting historical execution records of tasks at cloud, edges and terminal nodes, constructing a task execution feature library, and generating a resource demand prediction model in combination with real-time load features; analyzing network transmission time delay characteristics of a cloud end and edge nodes, measuring real-time calculation capability fluctuation data of terminal equipment, and establishing an inter-node resource collaboration degree evaluation matrix; generating an initial migration strategy according to the prediction model and the evaluation matrix, monitoring actual resource occupancy deviation of the task, forming a final decision in combination with a node resource state correction strategy, triggering cross-node migration, and synchronously updating the priority queue and the evaluation matrix.

The invention relates to a feature defense method and system in a network transmission process, and the method comprises the steps: intercepting a network transmission data flow in a migration channel of a virtual machine in real time, and building a bidirectional flow mirror image pipeline; performing deep protocol analysis and recombination on the original transmission message in the mirror image pipeline to obtain a structured traffic log of complete load information and metadata labels; based on a preset traffic feature set, extracting a memory paging transmission time sequence feature and a disk data block check code distribution feature from the structured traffic log, and constructing a first detection sub-vector; according to the invention, a high-precision virtual machine migration security protection system is realized.

The invention provides a resource scheduling control method and system for a big data server, and the method comprises the steps: constructing a multi-dimensional resource portrait module, collecting the CPU, memory, network, storage I / O load and task queue length of each node in real time, and predicting a resource demand trend through a time sequence algorithm; extracting characteristics such as calculation intensity, data dependence, memory requirements, network transmission quantity and the like; adjusting the weight coefficients of the resource utilization rate, the task completion time and the energy consumption efficiency according to the system load and the historical effect; establishing a bipartite graph model by taking a resource trend as a node feature and a task vector as an edge feature, and calculating a matching score through graph convolution and a multi-objective optimization function; the scheduling scheme is synchronized by adopting a consistency algorithm; automatic rollback and reallocation are carried out when resources are detected to be insufficient; and optimizing a weight coefficient and a network parameter through reinforcement learning. Through the method, the system resource utilization rate can be improved, the task execution efficiency is improved, the overall scheduling effect stability is improved, and the system fault recovery time is shortened.

Systems and methods are disclosed for preserving patient privacy while allowing health data to be analyzed, managed, and stored in different geographical areas. One method for managing cross-border health data while preserving patient privacy includes: receiving a DICOM object from a hospital computing device for analysis; generating a unique case identifier for the DICOM object; validating the received DICOM object; if, based on the validation, the received DICOM object is valid, anonymizing the received DICOM object; updating the anonymous DICOM object to include the unique case identifier; compressing the updated DICOM object; and sending the compressed DICOM object to at least one data analysis web service(s).

The invention relates to the technical field of industrial Internet of Things, and discloses a low-delay industrial Internet of Things data transmission system based on a 5G network. The system comprises a plurality of functional modules such as a data acquisition module, a data preprocessing module, a network transmission optimization module and a congestion control module. The data acquisition module acquires a heterogeneous data set, the preprocessing module performs standardization processing, the network transmission optimization module selects an optimal channel and node, and the congestion control module predicts flow and adjusts a transmission strategy. In addition, the system also has the functions of security encryption, heterogeneous data synchronization, dynamic spectrum allocation and the like. Through cooperative work of the modules, the system realizes low-delay and high-reliability transmission of industrial Internet of Things data, effectively processes heterogeneous data, guarantees data security, improves spectrum utilization efficiency and energy efficiency, enhances fault tolerance and compatibility of the system, and is suitable for various industrial scenes.

The invention provides a vehicle-mounted data grading processing method, system, device and medium, the method is cooperatively realized by a cloud end and a terminal device, and the method specifically comprises the following steps: the cloud end generates a structured configuration file containing an acquisition signal, a data type, a transmission condition, a priority and a compression rule based on a service scene, a first processor of the terminal equipment analyzes a received structured configuration file to generate an acquisition white list, a second controller filters controller messages according to the white list, executes double verification of cyclic redundancy check and counter tamper-proofing, and transmits valid data passing the verification in a hierarchical manner according to priorities, and a cloud terminal performs hierarchical decompression analysis on the received data and sends the analyzed data to a server. A historical data supplement mechanism is triggered when the data is abnormal, and the terminal equipment responds to the request to upload data in a specified time period and performs compensation analysis; according to the method, the collection flexibility is realized through dynamic configuration, and the problems of high computing power pressure of terminal equipment, non-uniform network transmission distribution and low cloud computing power utilization rate are solved.

The invention relates to the technical field of booster station monitoring systems, and discloses a booster station operation and maintenance work video auxiliary monitoring system comprising a three-dimensional perception interaction layer used for collecting equipment state data and providing a man-machine interaction interface and connected with an edge intelligent fusion layer through a wired or wireless transmission channel; and the edge intelligent fusion layer is used for locally analyzing and caching the state data. Through standardized interface interconnection of the three-dimensional perception interaction layer, the edge intelligent fusion layer and the cloud collaborative management layer, a collaborative working mode of data acquisition, local analysis and cloud optimization is formed, the architecture design breaks through the dependence of a traditional scheme on cloud centralized processing, data preprocessing sinks to the edge layer, the network transmission pressure is effectively reduced, and the network performance is improved. The local intelligent analysis capability can still be maintained when the network fluctuates, and compared with the delay problem caused by full data uploading in the prior art, the system response real-time performance and the availability under the network disconnection scene are remarkably improved.

The invention provides an electric power wireless local area network multi-domain data processing method and system based on credibility certification, and the method comprises the steps: firstly calling a credibility certification model to carry out the credibility certification of terminal equipment, generating a terminal certification data set containing equipment identity and the like, obtaining a cross-domain original data flow, extracting the characteristics of equipment operation and the like through multi-mode characteristics, and carrying out the multi-mode certification of the terminal equipment; the method comprises the following steps: carrying out weighted fusion on credibility of equipment operation state characteristics based on a terminal authentication data set, carrying out dynamic association analysis on the credibility and network transmission quality characteristics to generate a cross-domain association characteristic set, and carrying out spatio-temporal context aggregation on the cross-domain association characteristic set and service operation semantic characteristics by utilizing a pre-trained multi-domain collaborative analysis model; and finally, according to the multi-domain collaborative optimization strategy set, dynamic resources of service domain nodes are reconfigured, and a network optimization execution instruction set is generated and fed back to terminal equipment to trigger trusted communication link upgrading operation. And effective multi-domain data processing and network optimization of the electric power wireless local area network are realized.

The invention relates to the technical field of audio and video emergency transmission, and discloses an audio and video low-delay return method and system in an extreme environment. The method comprises the following steps: acquiring original multi-modal data of audio and video acquisition equipment in a target area, and analyzing a data state of the original multi-modal data; and meanwhile, available network transmission links are monitored, and the quality is evaluated. Self-adaptive coding parameters are generated in combination with the link quality and the data state, dynamic coding is executed on original data, and a coding stream suitable for redundant transmission is formed. And carrying out cooperative distribution transmission based on the network link set and the coded stream to generate return data. According to the generation process, a device and energy management instruction is formed and issued to the acquisition and relay device. According to the method, the network state and the content characteristics are optimized in a dynamic coding link in a collaborative manner, and the audio and video quality, the real-time performance and the system energy efficiency which are transmitted back in an extreme environment are improved through a feedback closed loop for transmitting a result to equipment management.

The invention is suitable for the technical field of toll station management, and provides an expressway toll station remote seat guarding and special situation vehicle handling system, which comprises a front-end sensing layer, a rear-end sensing layer and a control layer, the lane equipment comprises a photoelectric sensor, an infrared height limit alarm, a license plate recognition camera, an ETC antenna, an acousto-optic warning ball and a self-service equipment sensor; the network transmission layer is connected with lane equipment, a sentry box cabinet, a machine room core switch and a monitoring center through an optical fiber network; the remote control layer is composed of a remote seat center, and the remote seat center can carry out video monitoring, visual intercom and remote control; and the abnormity alarm layer is used for carrying out early warning on vehicle detention, vehicle height exceeding, ETC passing faults, toll evasion vehicles and handrail abnormity. The vehicle state can be sensed in real time, data are gathered to a remote seat center through a network transmission layer, an information island is broken, and special conditions can be automatically processed.

The embodiment of the invention discloses an intelligent traffic cooperative control optimization method, device and equipment based on quantum key distribution and digital twinning, and relates to the technical field of intelligent traffic. The method comprises the following steps: transmitting traffic data and spatial information through the quantum secure communication network, and constructing a traffic digital twin mapping model based on the traffic data and the spatial information; the traffic digital twin mapping model is configured to map to obtain a physical traffic system operation state corresponding to the traffic data and the spatial information; accessing the digital twin mapping model into a quantum computing environment, and generating a traffic control strategy based on the operation state of a physical traffic system by using a preset quantum algorithm; and transmitting the traffic control strategy to traffic equipment in a physical traffic system for execution, synchronously transmitting the traffic control strategy to a digital twin mapping model for simulation execution, and optimizing and adjusting the traffic control strategy according to a difference comparison result of a feedback actual execution result and a simulation execution result.

The invention discloses an explosion-proof and intrinsic safety type combined feeder switch state monitoring method based on big data, and relates to the technical field of industrial electrical equipment state monitoring and fault diagnosis, and the method is realized based on a three-level architecture constructed by an edge computing node, a region computing node and a cloud platform. Comprising the following steps: S1, collecting multi-source sensing data of a feeder switch in real time by an edge computing node, and performing feature extraction and fusion calculation on the multi-source sensing data; according to the method for monitoring the state of the explosion-proof and intrinsic safety type combined feeder switch based on the big data, the contradiction between the real-time performance and the accuracy in multi-source heterogeneous data fusion processing is effectively solved, abnormity can be found in the first time, early warning can be triggered, and the reliability of a diagnosis conclusion is improved; and the accuracy and foresight of fault diagnosis are ensured. According to the grading processing mechanism, computing resources are reasonably distributed, the network transmission load is greatly reduced, and the system can stably operate in a complex industrial environment.

The invention relates to the technical field of Internet content distribution, and discloses a distributed edge cache acceleration method based on PCDN, comprising the following steps: step I: terminal node access and resource initialization, which includes node registration and authentication, resource information reporting and node classification and label management; step II, hierarchical caching strategy and content storage, wherein the hierarchical caching strategy and content storage comprises content popularity grading, cache writing strategy and cache replacement and elimination; and step III, dynamic content scheduling and distribution. According to the distributed edge cache acceleration method and device based on the PCDN, the content popularity and regional distribution are pre-judged in advance through a deep learning model, and bandwidths and resources of different networks are integrated through a network fusion technology, so that the purposes of reducing the number of times of source returning requests, breaking through the transmission limitation of a traditional single network (for example, only depending on a cellular network) and improving the transmission efficiency can be achieved. The effects of node contribution traceability and automatic execution excitation are achieved.

The invention relates to a multi-dimensional aging test data analysis system and method, and aims to realize real-time acquisition and intelligent analysis of multiple performance indexes in the aging process of electronic products. The system comprises an information acquisition module, a test scheduling module, a data processing module, an analysis module, an abnormity judgment module, a report module and a communication module. Cooperative work among the modules is realized based on task driving and data circulation, accurate association of test data is realized through bar code binding, and unified analysis is performed in combination with multi-source information such as USB read-write performance, network transmission state and display resolution. The system realizes multi-task concurrent acquisition through a resource-aware scheduling strategy, and the analysis module identifies performance abnormity and outputs a structured report by combining preprocessing, feature extraction and time sequence prediction. According to the method, the test automation level and the anomaly recognition accuracy are improved.

The invention discloses a lightweight three-dimensional data format generation method suitable for ship model labeling, which comprises the following steps of: exporting a three-dimensional model file from ship design software, extracting a model attribute information file of the three-dimensional model file, analyzing the three-dimensional model file and the model attribute information file, and calculating to obtain attribute value information of a geometric body model in a model; the attribute value information of the geometry model is integrated and then converted into a lightweight data exchange format, a lightweight data exchange format file is converted into a binary format, and a lightweight three-dimensional data format file is obtained through transcoding and compression; and the lightweight three-dimensional data format file is stored in a database after being subjected to name matching based on the model attribute information. The volume of the lightweight three-dimensional data format file is small, only key data of the reduced model are reserved according to the characteristics of the ship model, and binary coding conversion and compression are performed on the file, so that the volume of the lightweight three-dimensional data format file is much smaller than that of a model file in a general format, and storage and network transmission are greatly facilitated.

The invention relates to the technical field of traffic regulation and control, in particular to an intelligent traffic regulation and control method based on the 5G cloud computing terminal technology, and the method comprises the steps: obtaining real-time traffic data, and transmitting the real-time traffic data to an edge computing node through a 5G network; preprocessing the real-time traffic data, and uploading the data to a cloud; the method comprises the following steps: constructing a dynamic graph neural network to analyze global traffic, recognizing a congestion sub-graph through node clustering, outputting a congestion probability, judging whether the traffic is congested according to the congestion probability, if so, scoring driving behaviors of vehicles in a congested area, analyzing the congested area to recognize a congestion type, and if not, judging whether the traffic is congested or not. And according to the congestion type and the driving behavior score, generating a differentiated regulation and control strategy, issuing the differentiated regulation and control strategy to each execution device through a 5G network, and guiding the vehicle to drive out of the congested road section by executing the differentiated regulation and control strategy. Therefore, the problems of lack of driving behavior analysis, lack of pertinence of regulation and control strategies and the like in the prior art are solved.

The invention, which relates to the technical field of information and communication, discloses an intelligent operation and maintenance monitoring system for a machine room, comprising a state monitoring module, an abnormity early warning module, a data acquisition module, a load evaluation module and a control module. The state monitoring module acquires temperature distribution state data information and vibration state data information in real time; the abnormity early warning module performs correlation analysis on the data, judges whether the server is normal or not and sends out an early warning signal; the data acquisition module acquires memory state data information and network transmission state data information of the server after receiving the early warning signal; the load evaluation module analyzes the load condition of the current server in combination with the trained load degree evaluation model; and the control module judges whether the server is in overload operation or not according to the current server load condition, generates a corresponding control instruction and executes the control instruction, so that stable operation and operation and maintenance efficiency of the server are guaranteed.

The invention relates to a distributed unmanned ship cluster collaborative awareness and control integration method and system in a high sea condition environment. The method comprises the steps of equipment installation and distributed communication network construction; task target and environment information is collected and subjected to preprocessing, space-time calibration and data fusion, fused data is transmitted and shared through a distributed communication network, and a distributed Kalman filtering algorithm is used for joint data processing; on the basis of an unmanned ship dynamics model containing interference factors, a model prediction control algorithm is adopted to carry out rolling optimization control input, hierarchical path planning is carried out through an improved A * algorithm and a dynamic window method, cooperation among unmanned ships is kept through a cooperative control protocol, and control parameters are automatically adjusted according to sea conditions; and constructing a collaborative optimization objective function, adjusting collaborative perception and collaborative control strategies according to the minimum value of the objective function, and performing closed-loop feedback optimization on the collaborative perception process. Compared with the prior art, the sensing accuracy, the control stability and the collaborative operation efficiency of the unmanned ship cluster in a high sea condition environment can be effectively improved, and the ability of the unmanned ship cluster to cope with a severe sea environment is remarkably enhanced.

The invention relates to the field of intelligent tunnel equipment management, and provides an intelligent tunnel equipment management method and system based on edge computing, and the method comprises the steps: deploying an edge computing node, and collecting the operation state data and environment parameter data of tunnel equipment; preprocessing the operation state data and the environment parameter data to obtain a preprocessed data set; identifying the preprocessed data set through an edge computing node to obtain equipment abnormal state data, and generating a local control instruction; transmitting the high-priority data to a cloud server through a communication network based on a hierarchical transmission rule; the high-priority data is compared with historical data, optimal operation parameters of equipment are calculated in combination with tunnel traffic flow and environmental conditions, and an optimized regulation and control strategy is obtained and transmitted back to an edge computing node; and according to the optimized regulation and control strategy and the real-time energy consumption data, adjusting calculation resource allocation, and switching an equipment operation mode. According to the invention, the real-time performance of intelligent tunnel equipment management and the energy utilization efficiency are improved.

The invention discloses an immersive interactive system and method integrating pet robot perception and AR rendering, and the system carries out the visual-inertial combined mapping and anchor point generation, the coding and network transmission of visual frames and spatial data, the synchronous decoding and coordinate system alignment of a terminal side, virtual object anchoring, and spatial mapping and AR rendering through a robot side. User intention analysis, control issuing and robot control, and low-delay synchronization, timeline alignment and closed-loop consistent maintenance are carried out; according to the method, the first visual angle image collected by the front camera of the pet robot can be utilized, the augmented reality technology is combined, and the user is substituted into the visual angle of the robot, so that the user can'personally feel 'the observation and action process of the pet robot, and the immersion and immediacy of human-pet interaction are remarkably enhanced; and human-machine-virtual object ternary space interaction is realized.

The invention relates to the technical field of audio and video processing, and provides an intelligent card pause prevention optimization method and system for audio and video playing. According to the method, firstly, a playing state data set is collected in real time, and the playing state data set comprises code stream parameters, hardware resource occupation data and network transmission state parameters; then, constructing a play load association graph based on the data set, and describing a mutual influence relationship among parameters; then, generating a dynamic resource allocation strategy according to the play load association map, and adjusting a hardware resource allocation proportion and a network transmission priority; and finally, executing the strategy, continuously monitoring the data change, and dynamically adjusting the strategy to maintain the playing fluency. Therefore, through multi-parameter correlation modeling and dynamic optimization, accurate prevention of lagging is realized, and the audio and video playing experience is improved.

The invention provides a logistics storage life management method based on radio frequency tag identification, and the method comprises the steps: obtaining an article identifier and initial life data stored by a passive radio frequency tag attached to an article from a radio frequency tag reader-writer of a target storage partition in response to an article life evaluation request; corresponding environment parameters, signal intensity and position information are called from the storage module, and abnormal records are read; the calculation module determines a life information set based on the data and reports the life information set to a superior management system; and after verification is correct, generating a service life detection packet for the packaging environment parameters, the signal strength, the position information and the service life adjustment rule of each article, and transmitting the service life detection packet to a storage terminal through a wireless sensor network. According to the invention, precise and automatic management of the service life of the stored goods can be realized, the inventory turnover efficiency is improved, and the deterioration loss is reduced.

The invention discloses a mobile intelligent safety supervision device based on multi-mode perception and edge calculation, and the device comprises a camera which is a high-performance dual-camera with adjustable height and visual angle, is fixed on a telescopic aluminum alloy support, integrates a loudspeaker and a voice communication function, and supports the autonomous network and 4G bidirectional communication; the edge intelligent gateway is used as a core computing unit, supports a neural network algorithm to analyze audio and video data, and realizes real-time identification of security behaviors; the Beidou positioning module is integrated on the edge intelligent gateway and provides centimeter-level high-precision positioning; the data storage module is used for large-capacity data storage and supporting storage and retrieval of audio and video streams and analysis data; the network transmission module is a multi-protocol network transmission module and supports WiFi, 4G and wired network transmission; and the power supply module is high in capacity and adopts a pluggable battery design. Omnibearing high-definition video monitoring can be realized, and the requirements of real-time communication and real-time early warning between project responsible personnel and on-site construction personnel are met.

The invention relates to the technical field of data communication, and discloses an intelligent agent high-speed bus implementation method and system based on an FPGA and a dynamic smoothing technology. The method comprises the following steps: constructing a single handshake message through a lightweight protocol, adjusting network indexes by adopting an exponential smoothing method, constructing a pipeline processing unit in an FPGA card by utilizing a VHDL, realizing key updating and encryption processing, constructing a three-layer adaptive structure connection subsystem, and optimizing algorithm parameters and resource allocation according to a running state. And a high-performance bus communication system is formed. On the premise of ensuring the communication security and reliability, the network transmission delay is remarkably reduced, and the data throughput is improved, so that the communication system can meet the requirements of emergency linkage and large data volume transmission in a scene (such as a rail transit station-level system) with a high real-time requirement.

The attack vectors for some denial-of-service cyber attacks on the Internet's Domain Name System (DNS) are bad, bogus, or unregistered domain name DNS requests to resolve domain names that are not registered in the DNS. Some other cyber attacks steal sensitive data by encoding the data in bogus domain names, or domain names otherwise not registered in the DNS, that are transferred across networks in bogus DNS requests. A DNS gatekeeper may filter in-transit packets containing DNS requests and may efficiently determine if a request's domain name is registered in the DNS. When the domain name is not registered in the DNS, the DNS gatekeeper may take one of a plurality of protective actions. The DNS gatekeeper drops requests determined not to be legitimate, which may prevent an attack.

The invention relates to a cellular network switching method and device, equipment and a storage medium. The method comprises the following steps: detecting whether current equipment meets a switching condition or not; the switching condition is a condition for switching a wireless network used by the current equipment to a cellular network; if the switching condition is met, identifying the operating system type of the current equipment; according to the method, the Socket object is created in different modes for different operating systems, cellular network communication is carried out based on the Socket object, the mode is not limited by a system kernel, the network transmission effect is improved, meanwhile, the wide applicability is achieved, and through the mode, when the wireless network quality is poor and communication fails, the communication efficiency is improved. The cellular network is automatically switched for communication, so that the negative influence on data transmission when a single network goes wrong is greatly relieved, and the user experience is improved.

The invention provides a VR game data synchronous transmission method based on a 5G network, and the method comprises the steps: obtaining a multi-type data stream generated during the operation of a VR game, extracting scene rendering data and player interaction data from the multi-type data stream, separating a feature value of each data type, and obtaining a data priority sequence; analyzing the real-time requirements of the scene rendering data and the interaction data according to the data priority sequence, and judging a key data packet which needs to be transmitted immediately; the method comprises the following steps: monitoring a current bandwidth fluctuation condition through a network transmission layer, calculating available bandwidth and delay parameters from network state data acquired in real time, and obtaining a resource allocation reference value in a dynamic scene; and for high-priority data packets, a dynamic resource allocation algorithm is adopted to adjust a transmission queue sequence, a resource allocation reference value is corrected through a bandwidth fluctuation parameter, and a transmission time slot allocation scheme of the key data packets is determined.

The invention belongs to the technical field of industrial safety monitoring, and provides a thermal power plant field operation safety identification alarm system, which comprises image acquisition equipment, network transmission equipment, an image identification unit and monitoring terminal equipment, the image acquisition equipment is used for acquiring video data of field operation; the image recognition unit is used for converting the video data into to-be-input image data and extracting key image data in the to-be-input image data; inputting the key image data into a target detection model to obtain an image recognition result; if the image recognition result is that the personnel violation behavior and / or the environment hidden danger state are included, determining an abnormity type, occurrence time, an occurrence place and image evidence; generating alarm information, and sending the alarm information to a monitoring terminal device; and the monitoring terminal equipment is used for displaying the alarm information and forwarding the alarm information to the mobile terminal equipment of the remote management personnel. According to the system provided by the invention, the identification precision, efficiency and convenience of the field operation safety of the thermal power plant are improved.

The embodiment of the invention provides a model service method and device and a storage medium. It is proposed to build a plurality of service instances deployed for the model service as a data transmission network. After the service instance receives the model calling request, whether model data needed by model loading exists in the local storage space or not can be inquired firstly, and if not, the needed model data can be remotely downloaded from other service instances on the basis of a data transmission network, and the downloaded model data is stored in the local storage space. Therefore, model data sharing can be realized based on the data transmission network established among the plurality of service instances, and the network transmission rate among the service instances in the data transmission network is far higher than the back-to-source downloading rate, so that even if the service instance does not have the model data required for loading locally, the service instance can not be loaded locally. Model data can also be downloaded remotely from other service instances. Therefore, the model loading efficiency can be effectively improved, so that the response efficiency to the model calling request is improved.

The invention provides a coal stockpiling method based on thermal power intelligent coal transportation, which comprises the following steps that: coal storage yard acquisition equipment acquires three-dimensional point cloud, surface texture, space coordinates, material identity and stacker-reclaimer attitude data of a coal pile, and transmits the data to an edge server through an optical fiber wireless redundant network; preprocessing the data to generate a coal seam three-dimensional digital twinborn model containing a spatial position, a component label and stacking time, and supporting virtual roaming; basic information and constraint conditions are input, a stacking plan is generated based on an optimization algorithm, and an operation instruction is generated after verification; the stacker-reclaimer receives the instruction, completes stacking according to track planning through the PLC control system and records data; the digital twin platform monitors the process, automatically alarms when abnormity occurs, updates the inventory in combination with an inventory making algorithm, and generates a report; the stacking effect is evaluated every day, algorithm parameters of the next round are optimized, and closed-loop management is formed. According to the method, the intelligence and accuracy of coal stacking are improved, and efficient operation of the thermal power coal conveying system is guaranteed.