[HTML][HTML] Comparison of machine-learning methods for urban land-use mapping in Hangzhou city, China
W Mao, D Lu, L Hou, X Liu, W Yue - Remote Sensing, 2020 - mdpi.com
… 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 …
methods: RF, SVM, and artificial neural network (ANN) to classify urban land use in Hangzhou …
Combing remote sensing information entropy and machine learning for ecological environment assessment of Hefei-Nanjing-Hangzhou region, China
… 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 …
changes and response characteristics. Results show that the weights of UECI IMP fluctuate …
Unveiling tropospheric ozone by the traditional atmospheric model and machine learning, and their comparison: A case study in hangzhou, China
R Feng, H Zheng, A Zhang, C Huang, H Gao… - Environmental pollution, 2019 - Elsevier
… 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 …
… Hangzhou, the capital of Zhejiang province with population over nine million, is the second …
Research on air quality prediction method in Hangzhou based on machine learning
Z Fu, H Lin, B Huang, J Yao - Journal of Physics: Conference …, 2021 - iopscience.iop.org
… 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 …
, the machine learning method is used to complete the air quality prediction of Hangzhou, and …
Association of neighborhood-level socioeconomic status and urban heat in China: Evidence from Hangzhou
J Li, G Li, Y Jiao, C Li, Q Yan - Environmental Research, 2024 - Elsevier
… Focusing on Hangzhou, a prototypical high-temperature city in China, this research …
temperature analysis, and employs machine learning algorithms to investigate the interrelation …
temperature analysis, and employs machine learning algorithms to investigate the interrelation …
Revealing the drivers of surface ozone pollution by explainable machine learning and satellite observations in Hangzhou Bay, China
… 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 …
the Light Gradient Boosting model (LightGBM, R 2 = 0.84) outperforms other machine learning …
Machine learning prediction on number of patient due to conjunctivitis based on air pollutants: A preliminary study
Y Cheng, Z Feng, MY Zhou, N Wang, MW Wang, L Ye… - 2020 - researchsquare.com
… 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 …
in this study. Table 1 describes the baseline characteristics of patient and environmental …
Explainable ensemble machine learning revealing the effect of meteorology and sources on ozone formation in megacity Hangzhou, China
L Zhang, L Wang, D Ji, Z Xia, P Nan, J Zhang… - Science of The Total …, 2024 - Elsevier
… 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 …
learning combined with SHAP … typical persistent pollution events in Hangzhou. The purpose is …
Recurrent Neural Network and random forest for analysis and accurate forecast of atmospheric pollutants: a case study in Hangzhou, China
R Feng, H Zheng, H Gao, A Zhang, C Huang… - Journal of cleaner …, 2019 - Elsevier
… 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 …
… in this paper is they outperform other machine learning models, such as Extreme Learning …
[HTML][HTML] Extraction of old towns in Hangzhou (2000–2018) from Landsat time series image stacks
… 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, …
to the range of supervised machine learning. According to the idea of ensemble learning, …
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