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1,119 results on '"Zhu, Yihua"'

153. A New Neural Network for Nonlinear Constrained Optimization Problems

Author

Meng, Zhiqing, Dang, Chuangyin, Zhou, Gengui, Zhu, Yihua, Jiang, Min, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Yin, Fu-Liang, editor, Wang, Jun, editor, and Guo, Chengan, editor

Published
2004
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161. PM 2.5 Concentration Prediction in Six Major Chinese Urban Agglomerations: A Comparative Study of Various Machine Learning Methods Based on Meteorological Data.

Author

Duan, Min, Sun, Yufan, Zhang, Binzhe, Chen, Chi, Tan, Tao, and Zhu, Yihua

Subjects
MACHINE learning, ARTIFICIAL intelligence, AIR pollution control, DEW point, MULTILAYER perceptrons, AIR pressure
Abstract

The escalating issue of air pollution in China's rapidly developing urban areas has prompted increased attention to the role of meteorological conditions in PM2.5 pollution. This study examines the spatiotemporal distribution of PM2.5 concentrations and their relationship with meteorological factors in six major Chinese urban agglomerations from 2017 to 2020, using daily average data. Statistical and spatial analysis techniques are employed, alongside the construction of eight machine learning models for prediction purposes. The study also compares the feature importance of various meteorological factors impacting PM2.5 concentrations. Results reveal significant regional differences in both average PM2.5 levels and meteorological influences. The Multilayer Perceptron (MLP) model demonstrates the highest prediction accuracy for PM2.5 concentrations. According to the MLP model's feature importance identification, temperature is the most significant factor affecting PM2.5 concentrations across all urban agglomerations, while wind speed and precipitation have the least impact. Contributions from air pressure and dew point temperature, however, vary among different urban agglomerations. This research considers the impact of urban agglomerations and meteorological conditions on PM2.5 and also offers valuable artificial intelligence-based insights into the key meteorological factors influencing PM2.5 concentrations in diverse regions, thereby informing the development of effective air pollution control policies. [ABSTRACT FROM AUTHOR]

Published
2023
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197. Clinical characteristics, rates of blindness, and geographic features of PACD in China

Author

Zhang, Hui, primary, Cao, Kai, additional, Jia, Hongyan, additional, Li, Liang, additional, Hu, Jianping, additional, Liang, Jing, additional, Song, Jing, additional, Wang, Hui, additional, Zhao, Aiping, additional, Duan, Xiaoming, additional, Fan, Sujie, additional, Wang, Feng, additional, Su, Ying, additional, Ha, Shaoping, additional, Duan, Xuanchu, additional, Yu, Jingni, additional, Zhao, Chunmei, additional, Tang, Guangxian, additional, Su, Yufang, additional, Cai, Hongying, additional, Gao, Jianlu, additional, Qu, Yanbing, additional, Lu, Peng, additional, Xie, Xiaobin, additional, Zhao, Junhong, additional, Tang, Li, additional, Liu, Danyan, additional, Liu, Wei, additional, Zhang, Min, additional, Fang, Aiwu, additional, Qu, Bo, additional, Dai, Weijia, additional, Zhong, Hua, additional, Zhang, Xueling, additional, Wu, Zuohong, additional, Zhai, Gang, additional, Lyu, Hongbin, additional, Xie, Lin, additional, Li, Haijun, additional, Zheng, Yajuan, additional, Li, Ning, additional, Li, Kaijun, additional, Xie, Guijun, additional, Qu, Hongbo, additional, Yu, Jinqiang, additional, Liang, Liang, additional, Zhu, Min, additional, Wang, Xuemei, additional, Ma, Xiang, additional, Zeng, Liuzhi, additional, Liu, Xuyang, additional, Zhang, Yong, additional, Zhang, Yuyan, additional, Yu, Fanglei, additional, Zhu, Yihua, additional, Cheng, Sumian, additional, Yu, Min, additional, Li, Jingmin, additional, Zhang, Yinong, additional, Liu, Ping, additional, Wu, Zhihong, additional, Zhang, Xiuzhi, additional, Kuo, Debbie, additional, Wang, Ningli, additional, and Qiao, Chunyan, additional

Published
2021
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200. Effect of Charge on Carbon Support on the Catalytic Activity of Cu2O toward CO2Reduction to C2Products

Author

Wang, Yating, Cheng, Ling, Ge, Wangxin, Zhu, Yihua, Zhang, Jie, Chen, Rongzhen, Zhang, Ling, Li, Yuhang, and Li, Chunzhong

Abstract

Electrochemical carbon dioxide (CO2) reduction for C2products has been studied on a series of supported Cu-based catalysts; however, the charge-promotion effects from the substrates for the selectivity of CO2reduction are still unclear. Here we localize nanosized Cu2O on three carbon-based substrates that provide different charge-promotion effects: positively charged boron-doped graphene (BG), negatively charged nitrogen-doped graphene (NG), and weak negatively charged reduced graphene oxide (rGO). We demonstrate that the charge-promotion effects lead to an increase in faradaic efficiency (FE) for C2products with an order of rGO/Cu < BG/Cu < pure Cu < NG/Cu and an FEC2/FEC1ratio from 0.2 to 7.1. By performing in situcharacterization, electrokinetic investigations, and density functional theory (DFT) calculations, we reveal that the negatively charged NG is favorable for stabilizing Cu+species under CO2reduction, which strengthens CO* adsorption to further boost C–C coupling for C2products. As a result, we achieve a high C2+FE of ∼68% at high current densities of 100–250 mA cm–2.

Published
2023
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