… Impressed by the study of EULUC [20], this research took Hangzhou as … machine-learning
methods: RF, SVM, and artificial neural network (ANN) to classify urban land use in Hangzhou …

… UECI IMP was applied to the Hefei-Nanjing-Hangzhou Region to explore its spatiotemporal
changes and response characteristics. Results show that the weights of UECI IMP fluctuate …

… In this study, we choose four machine learning models, which are Extreme Learning Machine
… Hangzhou, the capital of Zhejiang province with population over nine million, is the second …

… Machine learning is to achieve the purpose of classification and prediction through feature …
, the machine learning method is used to complete the air quality prediction of Hangzhou, and …

… Focusing on Hangzhou, a prototypical high-temperature city in China, this research …
temperature analysis, and employs machine learning algorithms to investigate the interrelation …

… Hangzhou Bay (HZB), where … machine learning is more efficient and accurate, especially
the Light Gradient Boosting model (LightGBM, R 2 = 0.84) outperforms other machine learning …

… A total of 84977 patients, living in the air-monitored area of Hangzhou city, were included
in this study. Table 1 describes the baseline characteristics of patient and environmental …

… and emission sources on O 3 formation in Hangzhou. … study employed ensemble machine
learning combined with SHAP … typical persistent pollution events in Hangzhou. The purpose is …

… in Hangzhou. Compared with the traditional atmospheric models, machine learning models
… in this paper is they outperform other machine learning models, such as Extreme Learning …

… Random forest was first introduced by Leo Breiman and Adele Cutler [38,39], and it belongs
to the range of supervised machine learning. According to the idea of ensemble learning, …