{"product_id":"mechanism-driven-explainable-urban-spatio-temporal-prediction-von-jingyuan-wang-und-jiahao-ji","title":"Mechanism-Driven Explainable Urban Spatio-Temporal Prediction","description":"\n                                \n                \u003cp\u003eUrban environments generate massive streams of spatio-temporal data, yet accurately predicting urban dynamics remains a fundamental challenge due to complex human mobility patterns, evolving environmental conditions, and distributional shifts across time and space. Mechanism-Driven Explainable Urban Spatio-Temporal Prediction offers a comprehensive and innovative framework that integrates physical mechanisms, causal modeling, and information-theoretic principles into modern deep learning methods, enabling more interpretable, reliable, and generalizable spatio-temporal forecasting.\u003c\/p\u003e\n                                \n                \u003cp\u003eThis monograph presents a unified perspective across intrinsic and extrinsic factors that shape urban mobility. It introduces a gravity-inspired potential energy field model to capture intrinsic behavioral mechanisms at both regional and road-network scales, bridging discrete and continuous temporal modeling through differential equation networks. Beyond intrinsic mechanisms, the book proposes a causal basis-vector representation to model spatio-temporal distribution shifts caused by unknown confounders, enhancing robustness under varying scenarios. Furthermore, it develops a theoretically grounded information-theoretic decomposition framework that reduces the complexity of mixed urban data distributions and pushes the predictive performance beyond existing limits.\u003c\/p\u003e\n                                \n                \u003cp\u003eCombining theoretical foundations, methodological innovations, and extensive empirical studies on real-world urban traffic datasets, this book provides a rigorous yet accessible resource for researchers in spatio-temporal modeling, intelligent transportation systems, machine learning, and urban computing. It also serves as a valuable reference for practitioners seeking interpretable and mechanism-aware prediction models for smart city applications.\u003c\/p\u003e\n                            \n            \u003cdiv class=\"aw-variant-hidden-subtitle-div\" id=\"aw-variant-subtitle-9789819206612\"\u003e\u003ch3\u003e\u003c\/h3\u003e\u003c\/div\u003e","brand":"Autorenwelt Shop","offers":[{"title":"Hardcover - 9789819206612","offer_id":58930280890693,"sku":"9789819206612","price":192.59,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0940\/0622\/files\/73461_8590dd92-5cc5-4f92-8a52-c48ded576392.jpg?v=1787201010","url":"https:\/\/shop.autorenwelt.de\/products\/mechanism-driven-explainable-urban-spatio-temporal-prediction-von-jingyuan-wang-und-jiahao-ji","provider":"Autorenwelt Shop","version":"1.0","type":"link"}