Anil Kumar

Multi-Model Traffic Congestion Prediction Using Diffusion Convolutional Recurrent Neural Networks with Transformer Based Fusion and Dual-Channel CNN for Multimodal Learning

Traffic congestion prediction focuses on evaluations upcoming road traffic states by analyzing past and real-time data such as vehicle velocity, traffic throughput and road occupancy. However, many existing models have limited adaptability to rapidly changing urban traffic conditions. To address these limitations, the...