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Santosh Kumar Sharma

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Open access Aug 2026

An Integrated Multimodal Deep Learning and Reinforcement Framework for Intelligent Travel Demand Forecasting

An end-to-end, monolithic framework that pairs the learning of multimodal representations with a spatio-temporal graph neural network, a Transformer-based forecasting module, a causal inference layer, and a Q-learning recommender to provide a replicable base to adaptable, understandable model of travel behavior in smar...

Santosh Kumar Sharma, S. Chander, Piyush Gupta · 0 citations
Review Open access Aug 2026

Hybrid Deep Learning and Machine Learning Framework for Intelligent Travel Demand Forecasting

An intelligent framework is developed as a hybrid one, where four complementary learners are used to operate in parallel: a spatio-temporal graph neural network (ST-GNN) to represent dependencies between travel zones, a Transformer to represent long-horizon temporal patterns, an LSTM to represent sequential mobility dy...

Santosh Kumar Sharma, S. Chander, Piyush Gupta · 0 citations

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