31results about How to "Solve the island problem" patented technology

The invention discloses a network security situation early warning method and system based on a knowledge graph, and relates to the technical field of network security, the method establishes a normal behavior reference model of a network node through the combination of the knowledge graph and a deep learning algorithm, and enhances the accurate identification and real-time early warning capability of abnormal behaviors. Through an unsupervised learning algorithm, historical data of each node is learned and modeled, and a normal behavior reference value is formed. In the real-time monitoring process, deviation calculation is carried out on the current access behavior of each node and the reference value of the current access behavior, a deviation degree value is obtained and compared with a set deviation threshold value, and abnormal nodes deviating from normal behaviors are identified and marked. The deviation degree model combines key factors such as a transmission protocol and data transmission duration, and can sensitively detect tiny deviation of the node in communication frequency or authority, so as to quickly adapt to a dynamic network environment.

The invention provides a real-time ship navigation route planning method based on augmented reality, and the method comprises the steps: collecting various environmental data around a ship in real time, and carrying out the preprocessing of the various environmental data; processing video data through a convolutional neural network, extracting environment features, extracting dynamic features through a long-short-term memory network, extracting spatial features through the convolutional neural network, extracting meteorological features by using a two-layer multi-layer perceptron, and fusing to obtain fused features; a generative adversarial network is utilized to generate various sea conditions and meteorological scenes, risk assessment is carried out, a risk map is generated, an avoidance strategy is generated, and a route is adjusted to avoid a high-risk area; in combination with the real-time environment perception data and the historical navigation data, dynamically adjusting the navigation route by adopting a reinforcement learning algorithm to obtain an optimized navigation route; the display is performed through real-time synchronization of AR display and a navigation system in combination with augmented reality technology superposition. According to the scheme, the safety and navigation efficiency of the ship are improved.

The invention discloses a BIM-based whole house intelligent control system. The system is mainly formed by mutual cooperation of a BIM model data integration unit, an Internet of Things access unit, a control and management unit, an energy consumption analysis and optimization unit and a user interaction and platform integration unit. The invention provides a BIM-based whole house intelligent control system, and the system achieves the deep fusion of a BIM model (a building information model) and intelligent household equipment (i.e., Internet of Things equipment), thereby achieving the bidirectional data interaction between the BIM model and the household Internet of Things equipment, achieving the equipment management, energy consumption optimization, automatic control and remote operation and maintenance, and achieving the intelligent control of the whole house. And the living experience of the user and the equipment management efficiency are improved.

The invention relates to the technical field of intelligent chemical engineering, and discloses an intelligent chemical engineering construction safety and quality detection method based on big data, and the method comprises the following steps: 1, installing a monitor and a sensor; step 2, intelligent analysis; step 3, predictive maintenance; step 4, risk assessment; step 5, quality control; step 6, safety management; 7, accident prevention; 8, remote real-time management is carried out; step 9, decision support; step 10, intelligent reporting; and step 11, displaying an interface. According to the intelligent chemical engineering site construction safety and quality detection method and system based on big data, through real-time monitoring and risk assessment, the intelligent chemical engineering site system can improve the safety management level of a construction site and reduce accidents, and the system can predict potential safety risks and take measures to avoid the potential safety risks by utilizing predictive maintenance and accident prevention technologies; and by using big data and an intelligent optimization algorithm, the resource allocation and the construction process are optimized, and the construction efficiency is improved.

The invention discloses a standardized operation and maintenance management method and system based on substation scene dynamic fusion, belongs to the technical field of substation operation and maintenance management, and aims to solve the problems of information islanding, low operation and maintenance efficiency, insufficient decision basis and the like. The Internet of Things technology is utilized, various sensors are deployed in a transformer substation, data such as equipment states and environmental parameters are collected in real time, preliminary processing is carried out through edge computing equipment, noise and redundant information are removed, a big data platform is established, the preprocessed data are stored and managed in a centralized mode, an advanced data fusion algorithm is applied, and the data fusion efficiency is improved. Data from different sources and in different formats are dynamically fused, meanwhile, the fused data are deeply mined and analyzed through an artificial intelligence algorithm, potential faults and risks are recognized, the information island problem is effectively solved, and the real-time performance and accuracy of data processing are improved.

The present invention provides a production traceability and transaction collaboration method and system for an MES system, which relates to the technical field of production traceability, including using graph database technology to construct a production process knowledge graph, mapping the fused multi-source heterogeneous data to the entities and relationships of the knowledge graph; based on a time series graph algorithm, establishing a dynamic time series association in the knowledge graph to form a traceable production process chain; based on a knowledge graph and anomaly detection model, constructing a transaction trigger mechanism to automatically identify production transactions that need to be collaboratively processed and obtain transaction collaboration records; using a reinforcement learning algorithm to establish a multi-agent collaborative decision-making model, which can adaptively allocate tasks and resources according to the current production status and historical experience; through a sequence-to-sequence model enhanced by an attention mechanism, converting unstructured collaboration requirements into executable workflows; and automatically generating a multi-dimensional production analysis report based on the traceable production process chain and transaction collaboration records.

The invention relates to the technical field of intelligent medical treatment, and discloses a pancreatic cancer evolution simulation and dynamic intervention system based on multi-model driving, and the system comprises a multi-source data fusion module which is used for accessing and processing patient data, and forming a multi-dimensional feature set; the model fusion construction module is integrated with a model coupler and can construct a patient-specific integrated calculation model; the twinborn calibration generation module is used for generating pancreatic cancer digital twinborn matched with the initial state of the patient; and the evolution simulation and intervention module is used for running the pancreatic cancer digital twins, simulating the natural evolution trajectory of the tumor and carrying out quantitative simulation on the input virtual treatment scheme effect. According to the method, by constructing the patient-specific digital twins, normal form transformation from static diagnosis to dynamic prediction is achieved, and a quantitative evaluation basis can be provided for selection of clinical treatment schemes.

The invention discloses a data asset management system based on a drilling full-service data platform, and the system comprises four-transverse three-longitudinal frame division, four transverse represents the process of data capitalization, and three longitudinal represents a support system for the construction of the drilling data platform, through the construction of the data platform, the construction of the drilling data asset management system is realized, and the construction efficiency of the drilling data asset management system is improved. Unified acquisition and standard storage of data are formed, a unified data sharing service and a unified application architecture system are provided, the problem of information islands is effectively solved, and closed-loop management of data generated by business and data service business is promoted. The advanced big data technology is adopted, mass data are converted into high-quality data assets, informatization is promoted to be converted from management and control to an enabling role, deeper business insight is provided for the drilling industry, and high-quality development of businesses is assisted.

The present invention relates to a method and system for training a federated active learning model, which combines federated learning with active learning, and can fully utilize a large amount of unlabeled data of each participant for collaborative model training under the premise of protecting data privacy. In each round of federated learning training, the global model obtained by federated learning is used to guide local data labeling, thereby improving labeling efficiency and overcoming the data island problem to a certain extent. A hybrid sampling strategy is proposed based on loss prediction and feature space distance in selecting informative samples for active learning, which can select high-quality samples and reduce labeling costs; reducing sample labeling costs can improve the accuracy and generalization performance of the model.

The invention relates to the technical field of medical systems, in particular to a cardiovascular operation nursing intelligent shift change system and an implementation method thereof, comprising a receiving end, an information sending end, an output end, an information acquisition end, an electronic signature end and a management end; the identity information and the state of a patient are confirmed through the output end, the two-dimensional code generator, the second recognition device and the first recognition device, so that the first patient information and the second patient information are confirmed, and the behaviors that the first patient information and the second patient information are manually filled in to be inconsistent and manually modified when a doctor receives the patient are avoided; the output end confirms the information of the medical instruments, omission of the instruments is avoided, omission of the instruments in an operation is avoided, influence on the operation quality is avoided, and economic loss is avoided; the state data of the second patient is acquired through the information acquisition end, so that the second patient is confirmed and matched with the actual illness state, the state of the patient during receiving is ensured, and the safety of the patient is ensured.

A barrier gate management system comprises a barrier gate management server, a barrier gate control mechanism for controlling opening and closing of a gate rod, and a near field communication device, the near field communication device sends an instruction signal to the barrier gate control mechanism, and the near field communication device sends the instruction signal to the barrier gate control mechanism corresponding to the near field communication device side. The method comprises the following steps: (S1) responding to an off-network barrier gate opening and closing request of a vehicle user side intelligent equipment terminal, and receiving first identity data and a barrier gate opening and closing instruction request sent by the vehicle user side intelligent equipment terminal by the near field communication equipment; (S2) the near field communication equipment locally verifies first identity data of the vehicle user, and sends a barrier gate opening and closing instruction to a barrier gate control mechanism according to a local verification result and a barrier gate opening and closing instruction request sent by a user side intelligent equipment terminal; and (S3) the near field communication equipment returns an identity verification result and / or an authorized passing state to the vehicle user side intelligent equipment terminal. When the parking area has the network disconnection scene, communication interaction with the near field communication equipment is carried out through first identity data sent by the vehicle user side intelligent equipment terminal, so that opening and closing of the barrier gate in the network disconnection scene are completed; the problems that in the prior art, in a network interruption scene, vehicle access of a user is blocked, manual rod lifting is needed, and the user experience feeling of property and vehicle users is poor are solved.

The invention belongs to the technical field of physiological signal analysis, and discloses a physiological signal analysis method and system based on a multi-scale cross guidance neural network, and the method comprises the steps: obtaining and segmenting a physiological signal into a plurality of data partitions; a plurality of parallel convolutional neural network sub-modules with different scales are adopted to carry out high-dimension mapping on the physiological signals of the data partitions to obtain nonlinear vectors, correlation among the different convolutional neural network sub-modules is learned and quantized into weight vectors, parallel operation is carried out on the nonlinear vectors based on the weight vectors, and the physiological signals of the multiple data partitions are obtained. Performing point convolution operation on a parallel operation result to obtain an information vector; decoding the information vector to obtain a feature vector; and carrying out physiological signal analysis by utilizing the feature vector. The method has classification and regression capabilities at the same time, does not need to re-optimize hyper-parameters when being generalized to different tasks, is light in design, can be deployed on edge equipment, and has good accuracy and effectiveness in different clinical scenes.

This invention relates to the field of photovoltaic power generation fault diagnosis technology, and in particular to a photovoltaic array fault diagnosis system and method based on artificial intelligence. By encrypting and preprocessing multi-source data, a multimodal dataset is constructed, providing a comprehensive and collaborative data foundation for subsequent analysis. The collaborative diagnosis model can analyze the battery and inverter status in parallel. By combining circuit equivalent models, spatial adjacency relationships, and theoretical power models for calculation, the diagnosis results have physical interpretability. A physical consistency verification rule based on power flow analysis is introduced to cross-validate and logically fuse the preliminary diagnosis results, generating reliable comprehensive fault diagnosis results. This approach solves the technical problem in existing technologies that focus on independent analysis of single components such as photovoltaic cells or inverters, lacking effective fusion and collaborative utilization of multi-source heterogeneous data, which limits the accuracy of diagnosis results.

The invention discloses an industrial equipment data acquisition and forwarding system and method based on multi-protocol adaptation, and the system comprises a protocol adaptation layer which is used for interacting with various types of industrial equipment and is integrated with a plurality of protocol drive plug-ins; the data standardization processing layer is used for receiving and analyzing the original data message, mapping the data of the original data message according to a preset mapping rule and converting the data into a unified data model; the data routing forwarding layer is used for receiving the standardized data objects of the data standardization processing layer and forwarding the standardized data objects meeting matching conditions to corresponding output channels according to a rule engine with the pre-configured matching conditions; and the configuration management module is used for configuring and managing the protocol adaptation layer, the data standardization processing layer and the data routing forwarding layer. According to the invention, the target path of the data is changed from hard coding to configurability, and the forwarding and storage paths of the data are configured through the configuration rule, so that the method is more flexible.

The embodiment of the invention discloses a data interaction method and device, a terminal, a storage medium and a program product, and relates to the technical field of terminals. The method comprises the steps that application data of a second application client side are obtained from a second application server side through a first application server side, the first application server side is used for providing services for a first application client side, and the second application server side is used for providing services for the second application client side; the first application client and the second application client run in an operating system, and the first application server and the second application server run in a trusted virtual machine; according to the application data of the second application client, through the first application server, calculating to obtain a calculation result required by the first application client; and returning a calculation result to the first application client through the first application server. By adopting the method provided by the invention, the problem of data islands between different applications in the terminal can be solved, and the data security can be guaranteed.

The invention discloses a data management method, system, equipment and medium for an integrated data medium, and relates to the technical field of data management, and the method comprises the following steps: starting a data import task, obtaining enterprise resources and customer relationship data according to a set mode and parameters, and storing the data in a distributed file system HDFS in a block manner in a directory and file form, processing the required data by adopting a parallel processing mode to generate a final result; and learning a data correlation mode of the enterprise resource and customer relationship from the final result, and obtaining an association relationship between the enterprise resource and customer relationship data. According to the method, the data in the distributed file system is read and processed in a parallel processing mode, the final result is generated through aggregation of the processed key value pairs, high data processing efficiency is achieved through parallel processing, and the accuracy and efficiency of data retrieval by a user are greatly improved.

The invention discloses a special job electronic ticket configurable management method and system based on digital analysis, and the method comprises the steps: building a shared task library and a standard template, executing a general configuration operation, carrying out the risk prediction of a special job according to the priority order of a task item list, and determining a general task item; sequentially adding different general task items into all associated special job electronic tickets in batches to obtain a plurality of intermediate tickets; the method comprises the steps of calculating the comprehensive association degree of intermediate tickets, determining a parallel configuration task set and a linkage configuration task set comprising mother tickets and sub-tickets, executing personalized configuration operation comprising parallel configuration of the parallel configuration task set and linkage configuration of the mother tickets and the sub-tickets of the linkage configuration task set, and generating a plurality of to-be-approved target special job electronic tickets. According to the invention, electronic ticket configuration can be carried out from different angles of the task association ticket and the ticket linkage task, the configuration rationality is improved, and the operation efficiency and the resource utilization rate are improved.

The invention discloses a kitchen induction cooker range Internet of Things automatic power-off fire protection device which comprises an integrated machine shell, the integrated machine shell is a cavity shell of a rectangular structure, an installation assembly is arranged on the integrated machine shell and fixed to a building, a control wire connector is arranged in the integrated machine shell, and the control wire connector is connected with a power supply line of an induction cooker range; the invention relates to the technical field of kitchen fire fighting, and discloses an internet-of-things automatic power-off fire fighting device for a kitchen induction cooker, which is designed and integrated with various sensors according to the characteristics of the induction cooker, realizes a fire fighting strategy taking prevention as a main part, comprehensively monitors the kitchen environment, can quickly decide a processing means according to various environmental parameters of the kitchen induction cooker, and improves the fire fighting efficiency. Rapid and automatic power-off is realized through controlling the wire connector, and through linkage of the central controller and external Internet of Things equipment, alarm multi-level performance is improved, linkage with intelligent kitchen equipment is realized, and the problem of information isolated island is solved.

The embodiment of the invention provides a latent guest mining method and related equipment, and belongs to the technical field of latent guest identification. The method comprises the steps of obtaining platform behavior data of a first object; the platform behavior data is obtained by performing identity unification on original behavior data which are obtained from a plurality of different platforms and are associated with the first object; performing feature extraction according to the platform behavior data to obtain a car purchase behavior feature and a social behavior feature of the first object; the vehicle purchase behavior characteristics are related to individual vehicle purchase behaviors; the social behavior characteristics are related to group vehicle purchasing behaviors; determining an individual purchase intention of the first object based on the car purchase behavior characteristics; determining a group purchase impact of the first object based on the social behavior features; analyzing based on the individual purchase intention and the group purchase influence, and determining the customer state of the object; according to the embodiment of the invention, the automobile sales conversion rate can be effectively improved through the technical means of unification of multi-platform data identities and individual group double-aspect analysis.

The invention discloses an equipment specialty affair management method and management system based on a process group, and the management method comprises the steps: (1) analyzing the business processes of all corresponding equipment management according to different equipment management businesses and equipment specialties of an enterprise, determining the relevance between the business processes, and calculating the correlation coefficient and the correlation degree; (2) determining a core process and an affiliated process according to the correlation coefficient and the correlation degree, and constructing a process group; (3) determining and configuring structured form information of a core process and an affiliated process in the process group; (4) determining a trigger mechanism and a closed-loop rule of an affiliated flow in the flow group, and establishing automatic configuration of the structured data; and (5) establishing a flow group evaluation mechanism. According to the method, the flow group taking the core flow as the center is established according to the business correlation, so that flow integration and input and output data homology are realized, repeated input is reduced, flow closed-loop confirmation work is reduced, and the working quality and working efficiency of equipment management are improved.

The invention discloses a financial service decision-making method and device, electronic equipment and a storage medium, and relates to the field of artificial intelligence or other related technical fields, and the method comprises the steps: receiving a financial service request of a user side, and carrying out the analysis of the financial service request, and obtaining the service information and the service type; calling N artificial intelligence agents based on the service type, and combining the N artificial intelligence agents to obtain an artificial intelligence decision body; inputting the service information into an artificial intelligence decision-making body, and performing service decision-making through the artificial intelligence decision-making body to obtain a service decision-making result; and obtaining a confidence value of the intelligent decision body, pushing the service decision result to the service terminal for correction when the confidence value is smaller than a preset confidence threshold, and executing the corrected service decision result. According to the method and the device, the technical problem of relatively low service decision accuracy caused by adopting a rule-based single artificial intelligence model to assist in service decision in related technologies is solved.

The invention relates to the technical field of mining equipment data communication, in particular to a mining combined feeder switch centralized man-machine interaction method, device and system. The man-machine interaction method comprises the following steps that a man-machine interface is provided through a display control device, and the man-machine interface is connected with a comprehensive protector and a camera element in each unit cavity at the same time through a communication bus and used for obtaining corresponding data information. According to the mining combined feeder switch centralized man-machine interaction method provided by the invention, the periodic data table and the non-periodic table are established, time-sharing and partition integration is carried out on the equipment data of each unit cavity, and time-sharing calling is carried out on the video image of each unit cavity, so that bandwidth occupation is effectively reduced, system efficiency is improved, and cost is reduced. The mining combined feeder switch solves the problem of information isolated island of each unit cavity of the original mining combined feeder switch, and adopts a centralized human-computer interface to display the data of all equipment, thereby being beneficial to centralized control and real-time monitoring of the running health state of the equipment.

The invention discloses a special equipment inspection data intelligent analysis method based on natural language understanding, and belongs to the technical field of special equipment safety supervision and big data analysis. The method comprises the following steps: receiving and analyzing a natural language request, and extracting a target use unit name and a risk analysis dimension; searching and constructing a device analysis group and matching a risk evaluation model; for each device in the group, extracting related data from the multi-source database; carrying out quantitative calculation by utilizing the matching model, and generating a single-equipment risk score and a risk factor label; carrying out aggregation analysis on a total-amount equipment result, and identifying an overall risk level, a dominant risk type and a high-risk equipment distribution characteristic of the unit; and finally, differential supervision suggestions are generated on the basis. According to the invention, full-process automation from natural language instructions to intelligent risk assessment and decision suggestions is realized.

The invention discloses a digital mission engineering development method based on a meta-model library. The digital mission engineering development method is used for modeling of a maritime search and rescue task complex system. The method comprises the following steps: constructing a system model for currently input maritime search and rescue task data and modeling problems based on a pre-constructed meta-model library of a maritime search and rescue task system; according to the method, standardized processes of digital mission engineering are set, including activities including scene conception, mission definition, process analysis, resource generation, experimental design, simulation deduction and evaluation optimization, the activities are refined into action sequences, each action is clearly defined, and a standard method and a working template are provided for the digital mission engineering. According to the method, the problems of incomplete scene description, unclear mission definition, nonstandard architecture design, insufficient verification and evaluation and the like during modeling of the maritime search and rescue system are solved, the standardized process of modeling of the maritime search and rescue task system is realized, the modeling speed and precision are improved, and rapid generation and iteration of system modeling in different scenes are supported.

The present invention discloses a method and system for constructing a mobile game security platform based on big data. The method collects mobile game client data, mobile game server data, and mobile game security crawler data; uses a distributed log collection system to collect the collected data and stores it in a distributed file system; uses a tree integration model and a neural network model to train the collected data stored in the distributed file system to generate a mobile game security model for identifying abnormal behaviors in the game. The technical solution provided by the present invention can identify mobile game security issues with unknown patterns, solves the problem of data islands, has good self-learning capabilities, and improves the reliability and scalability of the mobile game security platform.

The present invention belongs to the field of data processing technology, and its purpose is to provide a privacy protection method, system, device and product based on secure multi-party computing. The present invention does not require each participant to expose its original sample data, which ensures the data privacy of each participant, and can realize cross-institutional data sharing and joint computing, solving the problem of data islands; at the same time, the present invention can make full use of the computing power of the participants, and at the same time, by reducing the number of external participants, simplify the implementation and deployment of the system architecture and protocol, reduce the uncertainty risk to external entities, effectively avoid the problem of data leakage, and can be applied to scenarios where there is a certain trust basis between the participants; in addition, the present invention can help reduce the workload of each participant in the result synthesis processing.

The invention provides a method and device for constructing an additive manufacturing material database based on in-situ synchrotron radiation data, and relates to the technical field of material databases. The method comprises the steps that a relational database of laser additive manufacturing is constructed based on the synchrotron radiation principle of laser additive manufacturing, transient behaviors in the additive manufacturing process are captured in real time, the dynamic, defect evolution and phase change processes of a molten pool are monitored from microsecond to millisecond, and meanwhile a graphical user interface function is established based on the relational database of laser additive manufacturing. And a user is supported to carry out defect dynamic behavior analysis. According to the method, in-situ capture and data communication of defect dynamic behaviors in the laser additive manufacturing process can be realized remarkably through structured storage, correlation analysis and visual display, and material design, process optimization and quality control are supported.

A product quality prediction system based on federated learning includes a server and clients set up on multiple production lines. The server sends an initial product quality prediction model and fused model parameters to the clients. The fused model parameters are obtained by fusing the model parameters sent by each client. The clients include: multiple sensors for collecting product manufacturing process data; a training set construction module for acquiring sensor data and performing feature extraction to construct a local training set; a model training module for training the acquired product quality prediction model using a forward propagation federated training method based on the local training set; encrypting and sending the model parameters during training to the server and updating the local product quality prediction model according to the fused parameters; stopping training when training requirements are met to obtain a trained product quality prediction model; and a product quality prediction module for performing quality prediction based on the trained product quality prediction model.

The invention relates to an Internet geographic information processing service chain construction method, system and device. The method comprises the following steps of obtaining atomic service description information, generating a service description file, completing service registration on a slave server, and issuing the atomic service completing service registration on the Internet. Synchronizing the atomic service information issued by all the slave servers to the master server in real time, and querying and visually displaying all the atomic services through a preset service chain construction platform; and constructing a front-end service chain, analyzing the front-end service chain to obtain a service chain description file, determining the sequence and the data flow direction of the atomic services and the slave servers issuing the atomic services, respectively calling the atomic services on the slave servers, and completing cooperative computing of the atomic services. Through visual construction of the atomic service and the relation chain, the service chain construction process is simplified, the algorithm island problem is solved, and sharing and cooperative computing of algorithms on different servers of the Internet are realized.

The embodiment of the invention discloses a cluster visual monitoring and debugging system and method based on cloud edge collaboration and a medium. Comprising a data acquisition control module deployed at an edge side and used for acquiring multi-source heterogeneous monitoring data such as performance, links and logs of a cluster; a data storage module, wherein a built-in unified architecture server carries out unified modeling and storage on the monitoring data according to cluster topology; and the network data transmission module is responsible for cloud edge two-way transmission of data and forwarding of a control instruction. The cloud side comprises a container cloud platform and is used for data aggregation and instruction issuing; a cloud cluster virtual debugging environment maintained by the system serves as a digital twinborn body of a cluster and is used for high-simulation testing and change drilling; and the visual debugging module is deployed at a cloud end and / or an edge side, constructs a three-dimensional visual scene based on the monitoring data, supports state display and history playback, and directly regulates and controls cluster resources through interactive operation. According to the invention, unified integration of monitoring data, visual intelligent operation and maintenance, and simulation testing of safety are realized.