501results about How to "Reduce communication costs" patented technology

The invention provides a visual project management method and system based on task tracking, and relates to the technical field of project management, and the method comprises the steps: collecting project risk information through employing a context awareness technology, generating a risk propagation network, and calculating a risk diffusion coefficient; performing hierarchical analysis on project requirements based on the risk diffusion coefficient to obtain a task decomposition scheme, constructing a task transmission chain based on the task decomposition scheme and generating a visual task relation graph, and generating a task state transition rule and an alternative task path based on an early warning state of a task node, meanwhile, constructing a task elastic scheduling mechanism and storing the task elastic scheduling mechanism into a rule database; and identifying a preorder task node and a post-order task node on the task transmission chain, sending the task reconstruction instruction to the preorder task node and the post-order task node to realize dynamic task adjustment, updating the risk propagation network according to an adjustment result, and optimizing the risk diffusion coefficient.

The invention discloses a BIM-based indoor decoration simulation display method and system, and relates to the technical field of indoor decoration, and the system automatically calculates an optimal furniture placement position through an algorithm by using modeling information in a BIM technology. The algorithm not only considers the distance between the furniture and collision detection, but also comprehensively considers the actual demand of the indoor space, so as to ensure the reasonable utilization and functionality of the indoor space. The intelligent layout algorithm can avoid a crowded or disordered layout condition, and ensures that the indoor space is full of vitality and not crowded by optimizing the placement position and the space utilization rate of furniture. The overall attractiveness and comfort of the space can be improved, and residents can live and work more pleasantly. The system simulates reflection, refraction and diffuse reflection processes of light on the surface of an indoor decoration object by using a light tracing technology. The system carries out detailed analysis on illumination conditions of different areas.

The invention relates to the technical field of network switching, in particular to a satellite land network switching method and system for a ship, and the method comprises the following steps: carrying out the real-time tracking of the current position of the ship based on a GIS system, calculating the distance between the current position of the ship and an adjacent satellite and land network access point, and comparing the distance data with historical network performance data. According to the invention, real-time GIS tracking and BDS verification are used, the ship position is accurately monitored, and the access point distance and network performance data are dynamically analyzed, so that the prediction of the network access opportunity is more accurate and timely, the response speed of traditional network switching is optimized, the timeliness of switching is improved, and the network access time is shortened. Data transmission interruption caused by network delay or instability is avoided, real-time signal intensity monitoring and congestion information analysis are combined, the optimal network can be intelligently selected in multiple network environments, continuity of data service is ensured, experience is remarkably improved, and manual operation is reduced through the automatic network switching process.

The invention discloses a visual network freight platform transportation transaction management system. The system comprises an order management module, a vehicle scheduling module, a transportation monitoring module, a transaction settlement module and a visual display module. Each module has innovative functions, such as order intelligent classification, vehicle optimization scheduling algorithm to minimize comprehensive cost, real-time monitoring and accurate settlement. The corresponding management method adopts advanced technologies to ensure efficient operation of each link, including block chain recording, intelligent contract settlement and the like. The whole system realizes efficient management, real-time monitoring and convenient visualization of transportation transaction of a freight platform, and improves the efficiency and quality of logistics transportation; according to the visual network freight platform management system, efficient and accurate order management is realized, vehicle scheduling is optimized, the cost is reduced, comprehensive and real-time transportation monitoring is guaranteed to be safe, safe and accurate transaction settlement is realized, convenient and visual display is convenient to make decisions, and the logistics transportation efficiency, quality and user experience are improved.

The invention relates to the technical field of big data and the field of financial science and technology, and discloses a data dependency relationship confirmation method, which comprises the following steps of: importing metadata information containing a field name, a data table name and data source information into a data processing module to obtain a target field name, and retrieving a target field in the metadata information by utilizing the data processing module to confirm a data dependency relationship. Determining an upstream data source and a downstream data destination of the target field; generating upstream and downstream data link diagrams of the target field, wherein the upstream and downstream data link diagrams are used for identifying a flow relation of data, a data generator and processing logic; and analyzing a dependency relationship between the target field and the upstream and downstream fields based on the link diagram, and further determining a data table on which the target field depends and owner information of the data table. According to the method, through automatic analysis and link diagram generation, the original complex process needing manual query and processing is simplified, the data dependency relationship is clearer, the communication cost and query time of developers are reduced, and the data use accuracy and processing efficiency are effectively improved.

The invention discloses a detection laboratory total factor digital twinning model construction method and an intelligent operation and maintenance system, and relates to the field of digital twinning, and a total factor digital twinning model comprises a detection laboratory physical object model, a detection laboratory virtual model, a total factor data model, a data interaction model, a learning decision model and an operation and maintenance management model. Real-time mapping is kept between the physical object model and the virtual model of the detection laboratory; the total element data model is used for collecting, inputting, processing and updating multi-source heterogeneous data in the digital twinborn model of the detection laboratory; the data interaction model carries out fusion transmission on real-time data among the models; and meanwhile, the learning decision-making model performs autonomous decision making and diagnosis, and functions are integrated and displayed through the operation and maintenance management model, so that the intelligent operation and maintenance level of the detection laboratory is further improved. The whole detection process of the detection laboratory is digitalized, the communication cost of the detection test process is saved, the manpower and time cost is saved, and the detection efficiency is improved.

The invention discloses a code review method, system and device, a storage medium and a program product, and the method comprises the steps: cleaning a to-be-reviewed code snippet, and obtaining an incremental code snippet and position information; vectorizing the incremental code snippets; semantic query is conducted on the vectorized incremental code snippet data based on an ES database according to the cosine law, development rules of similar semantics are obtained and ranked from high to low according to similarity values, and a preset number of first several snippets are obtained; recombining cue words, wherein the recombining cue words comprise incremental code snippets and a preset number of development rules; and sending the recombined cue word to a general generative large model to obtain an examination suggestion. The code snippets to be examined are pushed to the gilab warehouse by a developer, and are cleaned by the gilab warehouse through webhook triggering. According to the review method, the whole process is automatic, the review efficiency is high, review can be conducted according to the development rules in the team, knowledge sharing is achieved, the review result is objective, and the problem that the text exceeds the upper limit is avoided.

The invention discloses a satellite cluster management system and method for a space-based computing system. The satellite cluster management system provided by the specification comprises a plurality of satellites and a ground station, and each satellite is used for storing the satellite information of the satellite, establishing communication with other satellites according to a preset rule so as to transmit the satellite information of the satellite to other satellites, and receiving and storing the satellite information transmitted to the satellite by other satellites. And the ground station is used for acquiring the satellite information of each satellite contained in the satellite cluster by communicating with any satellite.

The invention discloses a federated learning communication method, system and device, and the method comprises the steps: receiving a quantization model parameter and an inverse quantizer sent by each first client participating in the current round of federated aggregation in any round of federated aggregation of transverse federated learning; adopting an inverse quantizer corresponding to the target client to inversely quantize the quantization model parameter corresponding to the target client to obtain a reduced model parameter; and after the restoration model parameters corresponding to the first clients are obtained, aggregating the restoration model parameters of the first clients to obtain aggregated model parameters, and feeding back the aggregated model parameters to the first clients. Therefore, the federal learning communication efficiency is improved.

The invention relates to a dual-controller communication system and method, a computer product, equipment and a storage medium. The dual-controller communication system comprises a first controller and a second controller, wherein the first controller comprises a first processor and a first non-transparent bridge; the second controller comprises a second processor and a signal relay device; the input end of the first non-transparent bridge is connected with the output end of the first processor, the output end of the first non-transparent bridge is connected with the input end of the signal relay device, and the output end of the signal relay device is connected with the input end of the second processor. By adopting the system, the communication cost of the first controller and the second controller can be reduced, and the reliability of the system is improved.

The invention provides a GPU (Graphics Processing Unit) calculation method for computational fluid mechanics simulation. The GPU calculation method comprises the following steps: building a hybrid programming framework based on a CPU / GPU heterogeneous system; an OpenFOAM-GPU data structure is established; chemical calculation is migrated to the GPU; migrating the thermal physical quantity calculation task from the CPU to the GPU for execution; memory copy logic is improved, and the data exchange frequency between a GPU memory and a CPU in the calculation process is reduced; a two-dimensional array structure originally used on a CPU is reconstructed into a one-dimensional array structure suitable for GPU parallel computing; the problem that a numerical simulation method needs to consume a large number of computing resources due to the fact that the parallel efficiency is not high and the data communication problem between the CPU and the GPU is solved, the number of communication times between the CPU and the GPU is reduced, the communication cost is reduced, and the parallel computing efficiency and the data throughput are improved.

The invention discloses a model parameter updating method and system based on graph federated learning, and relates to the field of federated learning and graph neural networks, and the method comprises the steps: completing the training of a graph convolutional neural network through employing a federated learning frame, and enabling the training to be capable of training a model on a graph distributed on a plurality of clients; a neighbor feature aggregation function is used, so that the clients do not need to communicate in each training iteration, and the communication burden is remarkably reduced; an aggregation mechanism based on an attention mechanism is used, a server is allowed to dynamically allocate weights for each local model participating in training, and the robustness and accuracy of the model are improved.

The invention relates to the technical field of big data processing and analysis, in particular to a visual SQL generation method and system for FLINK real-time data processing, and the method comprises the following steps: data source management, which is used for managing a data source classification directory; the data type management is used for converting various database management data types; the visual SQL configuration is used for combining and adjusting a data source, a database and a data table in the data source management system and data type information in the data type management system in a visual mode, and finally generating an SQL capable of being executed in an Flink environment; the visual SQL generation method and system for FLINK real-time data processing have the advantages that the technical threshold is lowered, non-technical users can easily define data processing logic, complex Flink codes do not need to be written, and the threshold for using Flink is lowered; the development efficiency is improved, the data processing flow is simplified through a visual operation interface, the development period is shortened, and the development efficiency is improved.

The invention discloses a DAG-based cross-fragmentation point-to-point energy transaction optimization method, and belongs to the technical field of cross-fragmentation transaction processing. Comprising the following steps: defining a cross-fragment transaction; describing a dependency relationship among a plurality of sub-transactions based on a directed graph (DAG) structure; constructing a coordination layer based on a DAG account book, and selecting a node with the highest reputation value to serve as a DAG committee member; and carrying out transaction verification, cross-fragment transaction forwarding and verification during forwarding on the nodes serving as DAG committee members. According to the method, the optimistic strategy is adopted to process the cross-fragmentation transaction in parallel, and the cross-fragmentation transaction is decomposed into a plurality of sub-transactions in combination with a DAG structure, so that the atomicity and consistency of the transactions are ensured; in a high-frequency transaction scene, the throughput and the processing rate of the system are remarkably improved, and the transaction delay is effectively reduced; a DAG committee is formed in cross-fragment internal nodes, a DAG account book is maintained, efficient cross-fragment transaction processing is achieved, dependence on a trusted third party is eliminated, and communication and verification cost is remarkably reduced.

The invention discloses a traffic police dynamic gesture recognition method and system based on vehicle-mounted federal learning, and the method enables a key feature extraction model and a preset global model to be combined as a traffic police gesture recognition model shared by vehicle-mounted terminals of a whole network, and facilitates the improvement of the gesture recognition precision of the traffic police. Different vehicle-mounted terminals are organized to train the models based on the collected traffic police gesture image data through vehicle-mounted federal learning, and then each vehicle-mounted terminal only shares model update data instead of original training data, so that the data privacy of vehicle users is protected, the communication cost for uploading mass data to a central server is saved, and the user experience is improved. Meanwhile, real-time traffic police gesture image data dispersed in different vehicle-mounted devices are fully utilized in vehicle-mounted federation learning, training data from vehicle-mounted images have different observation angles, different environment conditions and the like, the diversity of model training data is enriched, and the training efficiency is improved. And thus, the adaptive capacity of the trained traffic police gesture recognition model in a variable traffic environment is enhanced.

The invention provides a power line carrier and wireless communication combined power data transmission method and system, and the method comprises the steps: collecting the operation data of terminal power equipment in real time through terminal collection equipment in a power distribution area, and adding a timestamp for the data; and the hybrid communication sub-equipment transmits the operation data with the timestamp to the hybrid communication main equipment of the substation by using the power line carrier. And after receiving the data, the main device calculates the communication distance between the power distribution area and the transformer substation according to the timestamp information, and selects a proper communication mode. And the master device continues to monitor and calculate the bit error rate, obtains parameters such as the signal-to-noise ratio, the attenuation value and the interference intensity of the communication channel, and inputs the parameters into the pre-trained support vector machine to predict the current bit error rate. And based on a prediction result, a communication distance, a load and other factors, a pre-trained reinforcement learning model is adopted to adaptively select an optimal communication mode, and the communication mode is dynamically adjusted to optimize a data transmission effect.

The invention discloses a flashover active feature recognition method for a power transmission line image, and the method comprises the steps: obtaining a historical picture, carrying out the preprocessing of the historical picture, and obtaining an image matrix, and the preprocessing comprises the first preprocessing and the second preprocessing; a sliding window technology is applied to the image matrix, the value of each window is calculated, the maximum value of the mean value of the windows is obtained, first judgment is conducted on the maximum value of the mean value of the windows, and a lightning flashover track is obtained; according to the method, the average brightness value and distribution in the lightning flashover track are extracted, the lightning flashover track is subjected to second judgment, lightning flashover is obtained, operation and maintenance personnel can understand the monitoring result more easily, and therefore operation and maintenance work can be guided more effectively.

The invention discloses a federated learning-based power load prediction system and a training method thereof, the system comprises a server, a client, an encryption and decryption module and a storage and processing module, and the method adopts a federated learning framework to realize distributed training and optimization of a power load prediction model. According to the method, a plurality of clients are allowed to locally train the power load prediction model, the model parameters are sent to the server for aggregation and updating, and the data set is distributed at each client locally, so that the risk that the data is illegally accessed or leaked is reduced, and the user experience is improved. According to the method, the LSTM neural network model is adopted to predict the power load, the characteristics of the time sequence data can be fully utilized, the prediction accuracy is improved, the regularization hyper-parameters are optimized by utilizing the Bayesian optimization algorithm in the prediction process, the performance of the model can be further improved, and the prediction result is more accurate.

The invention discloses an intelligent intercepting gate control method and system based on three-dimensional decision, and relates to the technical field of intelligent control, and the method specifically comprises the steps: obtaining pipeline water inlet data, and carrying out the preprocessing of the pipeline water inlet data, and obtaining the preprocessing data; inputting the preprocessed data into a TransConv-LSTM (Long Short Term Memory) model, and outputting a predicted value of the ammonia nitrogen content; obtaining uncertainty distribution of the ammonia nitrogen content predicted value based on an uncertainty model; generating a control instruction according to the ammonia nitrogen content predicted value, the uncertainty distribution of the ammonia nitrogen content predicted value and a preset gate action condition; and controlling the closure gate to act based on the control instruction. According to the method, the accuracy and reliability of water quality control can be effectively improved, the cost can be reduced, the data privacy can be protected, and intervention is performed in advance by predicting the future trend, so that more efficient and sustainable water resource management is realized.

The invention belongs to the technical field of federal learning, and discloses an intelligent model training method and system for distributed equipment collaborative optimization and a storage medium, and the algorithm comprises the steps that a client receives an original model sent by a server, and completes an initialization task of the model; the client carries out local training on the received initialization model based on the local data set to obtain a local training model, all basic parameters of local training are obtained through calculation, and a memory-free SR1 matrix is generated; the server randomly extracts part of clients, and the selected clients upload local model training parameters of the clients; updating an ADMM direction, and updating an internal problem; solving a variable-scale near-end mapping problem to obtain a near-end direction, and solving an external problem; and updating the global model according to the obtained near-end direction until the model training is completed. Under the condition that statistical heterogeneity exists, compared with an existing first-order composite optimization algorithm, the algorithm has the advantages that the convergence speed is higher, the convergence condition of the algorithm can be met more quickly, and progressive convergence is achieved.

The invention belongs to the technical field of federated learning, and more specifically relates to a privacy protection personalized federated learning method based on model hierarchical optimization. The method comprises the following steps: each client obtains a global model of a server side, updates a local model by using a training data set of a self-side, then performs hierarchical optimization on the local model, and determines partial model parameters to be uploaded of each client; partial model parameters to be uploaded by each client are cut, differential privacy noise is introduced, and then the model parameters are sent to a server side; the server side allocates a weight to each client according to the size of the data volume of each client, then aggregates the model parameters uploaded by each client to obtain a new global model, and sends the new global model to each client; and repeating the steps S1 to S3 until a set training round or convergence is achieved. According to the method, the problems of model performance influence and communication efficiency caused by heterogeneity in federal learning are solved while user privacy is guaranteed.

The invention discloses a rapid batch switching authentication method for predictability and aggregation promise proof, which realizes batch authentication of a plurality of user terminals by generating system parameters and secret keys through a trust mechanism and combining predictability promise and aggregation signature technologies. In the authentication process, the edge base station to be switched exchanges with the current communication edge base station through an encrypted message, verification information such as a pre-authentication certificate and a signature is generated through the user terminal, and identity authentication is completed step by step. The method comprises the following specific steps: a trust mechanism generates a private key, a public key, a pseudo identity and an expiration timestamp for each device; through multiple rounds of message exchange, the edge base station and the user terminal perform identity verification by using a shared key and a hash function; and finally carrying out efficient verification on a plurality of users through batch signature and aggregation commitment. According to the method, on the basis of ensuring the security, the speed of switching the authentication process is greatly improved, and the method is suitable for a large-scale network environment, especially in edge computing and mobile communication networks.

The invention discloses a distributed adaptive fault-tolerant control method for a direct-current micro-grid, and the method comprises the steps: designing a distributed adaptive fault compensator based on an extended state observer, and enabling the distributed adaptive fault compensator to be used for compensating the control input of each distributed power supply under the conditions of actuator failure, bias fault and external interference; based on a distributed consistency protocol and a self-adaptive fault compensator, a distributed secondary comprehensive performance optimization adjustment mechanism is provided, and the fault-tolerant capability, the voltage quality and the current sharing precision of the direct-current micro-grid system under the actuator fault are improved; and a Lyapunov stability proof of system convergence based on a distributed adaptive fault-tolerant control method is given. According to the method, multiple types of actuator faults are considered, so that the method is more general; upper bound or lower bound information of any fault is not needed, the difficulty of parameter configuration of the controller can be effectively reduced, and the method is more universal and practical; the distributed power supply is completely distributed, no global information is needed, only the information of the local and adjacent distributed power supplies is utilized, and the communication cost is reduced.

The invention belongs to the field of medicine, and particularly relates to a physical examination data significance analysis method based on multiple examination correction. The method comprises the following steps: firstly, carrying out transverse and longitudinal cleaning on physical examination data, then, carrying out classified analysis on the data, calculating the proportion of each disease in different classifications according to a set threshold value, finally, carrying out significance test on a statistical analysis result by utilizing a chi-square test method, and carrying out correction by utilizing a Bonferroni multiple comparison correction method. Saliency analysis is carried out through multiple comparison and correction methods of physical examination data, various physical examination indexes can be synthesized, the physical health condition level of a user can be described objectively, theoretical guidance is provided for health guidance of a doctor on a physical examination person and a physical examination item method for accurately positioning the patient, and meanwhile, the physical examination accuracy is improved. The communication cost between the physical examination user and the doctor is reduced, and the user is urged to pay more attention to the overall health condition level.

The invention discloses a parameter adaptive control method and device for frequency modulation participation of a network construction type wind power plant. The method comprises the following steps: respectively establishing an inertia adaptive curve model and a droop adaptive curve model of each wind turbine generator set; distributing a corresponding cooperative control coefficient for each droop adaptive curve model to obtain a droop adaptive curve cooperative control model of each wind turbine generator set; in the frequency modulation process from power disturbance to maximum frequency deviation of the system, the inertia coefficient and the droop coefficient of each wind turbine generator set are respectively changed according to the corresponding inertia adaptive curve model and the corresponding droop adaptive curve cooperative control model; in the frequency modulation recovery process after the system has the maximum frequency deviation, the inertia coefficient of each wind turbine generator set is maintained at the set minimum inertia coefficient, and the droop coefficient of each wind turbine generator set continues to change according to the corresponding droop adaptive curve cooperative control model; therefore, cooperative control of each wind power set in the wind power plant participating in system frequency modulation is completed.

The invention discloses a data monitoring system based on power telecontrol, which comprises a sensor module, a preprocessing module, a transmission analysis module, a data processing module, a data transmission module, a data receiving module, a data verification module, a reacquisition module and a monitoring display module, and relates to the technical field of data monitoring. According to the data monitoring system based on power telecontrol, through an intelligent transmission analysis mode, unnecessary data transmission is avoided, network resources are saved, only operation data exceeding the standard fluctuation difference are transmitted, the data transmission amount is greatly reduced, the communication cost and the system burden are reduced, and the transmission efficiency is improved; different attribute operation parameters of a plurality of time nodes in a specified period are preprocessed, an accurate fluctuation interval and a standard fluctuation difference are calculated, the operation condition of a controlled station can be reflected more accurately, and the accuracy and reliability of data processing are ensured based on scientific variance calculation and comparison.

The present invention relates to the technical field of electronic digital data processing, and specifically discloses a hierarchical federated learning method of adaptive compression coding, the method comprising: hierarchical federated learning architecture construction, edge server matching, model generation performance judgment, compression rate matching and hierarchical federated learning architecture judgment, firstly, a hierarchical federated learning architecture is constructed so that each layer can make full use of its computing resources, an edge server corresponding to a terminal device is obtained by matching, each terminal device is used to generate an environmental data training model, a corresponding compression rate is obtained according to the network transmission performance of the edge server, the edge server receives the environmental data training model of each terminal device and performs adaptive compression coding and edge aggregation in sequence according to the corresponding compression rate, a cloud server receives the edge aggregation result and performs global aggregation, and finally judges whether the cloud server to which the hierarchical federated learning architecture belongs uploads the corresponding result of the global aggregation to an environmental resource scheduling cloud platform.

The invention discloses a multi-region transportation service mode matching method and system, and particularly relates to the technical field of transportation services, and the method comprises the following steps: dividing user identities into order-sending users and order-receiving users, and respectively obtaining an order-sending requirement set of a target order-sending user and a service set of all order-receiving users in a non-order-receiving state; hard condition screening is firstly carried out, order receiving users meeting hard conditions are reserved, and then elastic condition screening is carried out; if the order receiving users meeting all the elastic conditions exist, direct matching is carried out; otherwise, carrying out portrait analysis by using K-means clustering based on the historical record of the target order issuing user, and evaluating a matching failure rate; according to a failure rate result, negotiation communication channels are successively established until consistent matching is achieved; the method can deeply understand the demand characteristics and behavior patterns of the order issuing user, provides highly personalized matching services, improves the service quality of the platform, and further enhances the loyalty and satisfaction of the user.

The invention relates to a dynamic data and page generation mode based on configuration. Comprising the steps of 1, sorting a data dictionary, and completing corresponding data model and field definition processing; 2, a data model is defined, and a system background creates a corresponding form in a relational database based on the defined data model to serve as a data storage basis; 3, defining a business model which is related to an actual business scene and is a basis of business scene operation; 4, setting a data block as a basis of Form or List; 5, defining a page; step 6, menu definition and page display; and 7, after the definition of the steps is completed and the user logs in the system, accessing and operating page data corresponding to the menu. The technical problems that in an existing technical scheme, a static page is low in reusability, low in development efficiency, low in expandability, weak in deployment capacity, high in development threshold, low in related personnel participation degree and incapable of fully participating in development, operation and maintenance, and consequently human resources are wasted are solved.

The invention relates to / belongs to the technical field of voice communication, and provides a voice calling method and system for a primary gateway and a secondary gateway. The invention aims to solve the technical problem that short number services among sub-gateways need to be distributed and managed by operators in the prior art. Comprising the following steps: acquiring and analyzing a first notify message reported by a first sub-gateway, judging whether the first notify message is an internal short number service, and if so, replying a first response code to the first sub-gateway; obtaining and analyzing a first INVITE message reported by the first sub-gateway to obtain a calling number and a first call-id, obtaining an IP address of a second sub-gateway by using the called number, and generating a second call-id through the calling number and the IP address of the second sub-gateway; and a second INVITE message is generated based on the second call-id, the second INVITE message is sent to the second sub-gateway, and the second INVITE message is used by the first sub-gateway to establish a call to the second sub-gateway.