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Artificial neural networks

Global Polynomial Pinning Synchronization of Coupled Reaction-diffusion Inertial Neural Networks via Dual Event Triggered Markov-switched Control

Researchers at Nazarbayev University have made a significant breakthrough in the field of information and data encoding and encryption. The team, led by Dr. Ardak Kashkynbayev, has developed a novel method for achieving global polynomial pinning synchronization (GPPS) in coupled reaction-diffusion inertial neural networks (CRDINNs) with proportional delays. This method,

Traffic accidents

Trajectory Data-based Model Predictive Control of Adjacent Intersection Signal Control Under Traffic Accident Scenarios

In a critical study, researchers at the University of Shanghai for Science and Technology have developed a highly scalable model predictive control strategy for traffic accident scenarios. The proposed method, which utilizes vehicle trajectory data generated during an accident, offers technical support for maintaining traffic flow stability and smoothness when