@inproceedings{6f1f2edacd9d436ca149c503db7a768b,
title = "An Intelligent Analysis for Rural Settlement Distribution Based on Gaussian Mixture Models: A Case Study of Kengzi Village",
abstract = "In light of the booming rural construction industry in China, the recurring problem of the 'village sameness' reflects the inadequate understanding of inherent characteristics of traditional settlements. To discern the internal logic of historic rural settlements from historical spatial data, this study proposed a machine learning method based on the Gaussian mixture model (GMM) to examine the settlement distribution sensitivity for every geographical variable, and to perform a multivariate regression analysis on the nonlinear non-monotonic relationship between variables and the land usage development potential. In accordance with the abstracted spatial rules, the model was also used for predicting the spatial trends to support regional planning activities.",
keywords = "Distribution characteristics, Gaussian mixture model, Geographic intelligence, Machine learning, Rural settlements",
author = "Xi Yang and Fuan Pu and Guiming Luo",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 17th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2018 ; Conference date: 16-07-2018 Through 18-07-2018",
year = "2018",
month = oct,
day = "4",
doi = "10.1109/ICCI-CC.2018.8482033",
language = "英语",
series = "Proceedings of 2018 IEEE 17th International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "478--484",
editor = "Yingxu Wang and Sam Kwong and Jerome Feldman and Newton Howard and Phillip Sheu and Bernard Widrow",
booktitle = "Proceedings of 2018 IEEE 17th International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2018",
address = "美国",
}