6 results about "Adaptive traffic control" patented technology

The invention discloses a multi-source heterogeneous data synchronization system, and relates to the field of computer information management application. The system fuses key technologies such as flow dynamic regulation and control, self-adaptive load balancing and intelligent semantic mapping. Through a real-time network state monitoring and self-adaptive flow regulation and control algorithm, the data transmission rate is dynamically adjusted according to the server resource utilization rate, the data priority and the network bandwidth, data backlog and system overload are avoided, and the robustness and the real-time performance of a synchronization task are remarkably improved. The intelligent field mapping engine is based on semantic analysis, word vector representation and a machine learning model, automatically recognizes field semantic consistency of heterogeneous data sources, generates an optimal mapping rule and dynamically optimizes a mapping result, the manual configuration cost is reduced, and the mapping accuracy rate reaches 98% or above. The system has high expandability and self-learning ability, is suitable for a large-scale multi-source heterogeneous data integration scene, and provides an efficient, intelligent and self-adaptive full-stack solution for a data synchronization task.

This invention discloses an intelligent traffic management system based on spatiotemporal sequence features, belonging to the field of intelligent traffic management technology. The system includes a data fusion and spatiotemporal sequence management module for real-time acquisition of multi-dimensional traffic data and data preprocessing; a spatiotemporal causal chain modeling and source analysis module for modeling spatiotemporal causal chains, assessing the causal strength of road events, and implementing causal control decisions; a traffic state prediction and intelligent control module for predicting traffic states and comprehensively analyzing traffic control needs; an anomaly detection and adaptive optimization module for assessing traffic anomalies and implementing adaptive traffic control measures; and an intelligent feedback and self-evolution module for comprehensively analyzing control benefit feedback and automatically implementing optimization strategies. This invention solves the problem of untimely traffic control in complex traffic environments where the superposition of multiple minor traffic anomalies makes it difficult to automatically perform intelligent source tracing of traffic event causal chains.

The invention relates to the technical field of traffic planning, and discloses an urban traffic optimization and planning method and system based on artificial intelligence data processing, and the method comprises the steps: collecting a time sequence perception data flow of a target intersection, and carrying out the extraction of an occupancy state tensor based on a time window, and obtaining the occupancy state tensor of the target intersection in the time window; using the occupancy mode analysis model to output occupancy mode probability distribution of the target intersection in the time window; and outputting the lane traffic capacity of the target intersection by using a lane traffic capacity calculation function which is corrected by introducing dynamic factors of a temporary parking type occupation reduction factor and a queuing type occupation delay factor, and dynamically adjusting a short-time traffic control strategy of the target intersection. According to the invention, through time sequence perception and occupation mode analysis, the temporary parking and queuing occupation modes are distinguished, and the traffic capacity of the lane is dynamically quantified and corrected, so that the short-time traffic control strategy is adjusted in real time, and refined and adaptive traffic control and optimization under complex disturbance conditions in a city are realized.

The invention provides a data processing method and device, electronic equipment and a storage medium, the method comprises the steps that in response to release of target content, a model identifier matched with the target content is acquired, the model identifier corresponds to at least one processing model, and each processing model is used for determining label information of the target content under a specific type; constructing a request message based on the model identifier, sending the request message to a corresponding target processing model through a message queue, and receiving model result information returned by the model; and finally determining a content label of the target content according to the model result information. According to the method, plug and play of an algorithm model is realized by constructing a standardized interface, asynchronous decoupling and traffic peak clipping are realized by means of a message queue, and intelligent retry, link tracking and adaptive traffic control are combined, so that the model access cost is reduced, and the anti-concurrency capability and stability are improved.

This application relates to the field of traffic scheduling technology and discloses a method and apparatus for traffic control processing of credit reporting inquiries. One method for traffic control processing of credit reporting inquiries includes: obtaining a calling mode by adapting the mode of the credit reporting inquiry period during the traffic control scheduling process; calculating the real-time traffic deviation for the real-time time window of the calling period when the calling mode is a traffic clearing mode; combining the real-time traffic deviation with steady-state deviation data for adaptive traffic control scheduling to obtain adaptive traffic control parameters; finally, sending the adaptive traffic control parameters to the calling task; and executing the calling task to realize the credit reporting inquiries from the credit reporting platform by the resource organization. This achieves dynamic adaptive traffic control during the credit reporting inquiries process, which helps the resource organization clear the credit reporting inquiries traffic.

The invention discloses a high-speed traffic flow prediction and traffic control method based on machine vision, and relates to the technical field of data analysis, comprising the steps of analyzing the historical traffic flow change trend of each road, quantifying the traffic state of each road, and constructing a traffic scene recognition model for monitoring a high-speed traffic network; screening attention attribution data sets of all road traffic scenes in the monitored high-speed traffic network, generating probability distribution vectors of all the road traffic scenes by using Bayesian prior, substituting the probability distribution vectors into the high-speed traffic space-time convolution topology network, and predicting traffic flows of all the road traffic scenes in the short-time monitored high-speed traffic network; and based on a plurality of known traffic control action sets of the expressway, constructing an adaptive traffic control function of the expressway, and generating an optimal control strategy of each road in the expressway traffic network. The method has the beneficial effects that the road network operation efficiency is comprehensively improved, and meanwhile, the actual feasibility and economical efficiency of the management and control strategy are ensured.