Abstract
Geographical modeling has been recognized as a powerful way to solve complex geographic problems. However, its wide applicability is increasingly hindered by its complexity in domain knowledge required and the procedures involved. In this chapter, we argue that domain knowledge plays a key role in making geographical modeling intelligent. Domain-knowledge-based intelligent geographical modeling would not only solve wide geographical problems in an easy-to-use manner on the premise of the effectiveness of the built model specific to the application context, but also contribute to research in artificial intelligence.
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Acknowledgements
This work was supported by the National Key R&D Project of China (Grant No. 2021YFB3900904), the National Natural Science Foundation of China (No. 41871362), and the 111 Program of China (No. D19002). Supports to A-Xing Zhu through the Vilas Associate Award, the Hammel Faculty Fellow Award, and the Manasse Chair Professorship from the University of Wisconsin-Madison are greatly appreciated.
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Qin, CZ., Zhu, AX. (2022). Towards Domain-Knowledge-Based Intelligent Geographical Modeling. In: Li, B., Shi, X., Zhu, AX., Wang, C., Lin, H. (eds) New Thinking in GIScience. Springer, Singapore. https://doi.org/10.1007/978-981-19-3816-0_19
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DOI: https://doi.org/10.1007/978-981-19-3816-0_19
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