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Wan-Xin Yin

Showing results (1-10 of 12) with videos related to

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Bioresource Technology|June 17, 2025
Ferrous activated sodium percarbonate for controlling sulfide and methane production in sewer sedimentHong-Xu Bao, Wan-Xin Yin, Shuai Liu, et al.
Water Research|July 3, 2026
From fixed to condition-dependent emission factors: probabilistic tabular learning for wastewater N<sub>2</sub>O inventoriesJia-Ji Chen, Hong-Cheng Wang, Wan-Xin Yin, et al.
The Science of the Total Environment|July 7, 2024
Machine learning for high-precision simulation of dissolved organic matter in sewer: Overcoming data restrictions with generative adversarial networksFeng Hou, Shuai Liu, Wan-Xin Yin, et al.
Environmental Science and Ecotechnology|December 11, 2024
Augmented machine learning for sewage quality assessment with limited dataJia-Qiang Lv, Wan-Xin Yin, Jia-Min Xu, et al.
Bioresource Technology|October 16, 2024
Microbial-Guided prediction of methane and sulfide production in Sewers: Integrating mechanistic models with Machine learningWan-Xin Yin, Jia-Qiang Lv, Shuai Liu, et al.
Environmental Science & Technology|May 16, 2025
Federated Machine Learning Enables Risk Management and Privacy Protection in Water QualityYu-Qi Wang, Hong-Cheng Wang, Wen-Zhe Wang, et al.
Water Research|May 7, 2025
Data-driven differentiable model for dynamic prediction and control in wastewater treatmentYun-Peng Song, Wen-Zhe Wang, Yu-Qi Wang, et al.
Environmental Science & Technology|July 24, 2025
Machine Learning-Driven Dynamic Measurement of Environmental Indicators in Multiple Scenes and Multiple DisturbancesYu-Qi Wang, Han-Bo Zhou, Xiao-Qin Luo, et al.
Environmental Science & Technology|February 12, 2025
Deciphering and Mitigating of Dynamic Greenhouse Gas Emission in Urban Drainage Systems with Knowledge-Infused Graph Neural NetworkWan-Xin Yin, Ke-Hua Chen, Jia-Qiang Lv, et al.
Environmental Science and Ecotechnology|August 5, 2025
Leveraging scenario differences for cross-task generalization in water plant transfer machine learning modelsYu-Qi Wang, Xiao-Qin Luo, Han-Bo Zhou, et al.
Pageof 2

Showing results (1-10 of 12) with videos related to

Sort By:
Pageof 2
Bioresource Technology|June 17, 2025
Ferrous activated sodium percarbonate for controlling sulfide and methane production in sewer sedimentHong-Xu Bao, Wan-Xin Yin, Shuai Liu, et al.
Water Research|July 3, 2026
From fixed to condition-dependent emission factors: probabilistic tabular learning for wastewater N<sub>2</sub>O inventoriesJia-Ji Chen, Hong-Cheng Wang, Wan-Xin Yin, et al.
The Science of the Total Environment|July 7, 2024
Machine learning for high-precision simulation of dissolved organic matter in sewer: Overcoming data restrictions with generative adversarial networksFeng Hou, Shuai Liu, Wan-Xin Yin, et al.
Environmental Science and Ecotechnology|December 11, 2024
Augmented machine learning for sewage quality assessment with limited dataJia-Qiang Lv, Wan-Xin Yin, Jia-Min Xu, et al.
Bioresource Technology|October 16, 2024
Microbial-Guided prediction of methane and sulfide production in Sewers: Integrating mechanistic models with Machine learningWan-Xin Yin, Jia-Qiang Lv, Shuai Liu, et al.
Environmental Science & Technology|May 16, 2025
Federated Machine Learning Enables Risk Management and Privacy Protection in Water QualityYu-Qi Wang, Hong-Cheng Wang, Wen-Zhe Wang, et al.
Water Research|May 7, 2025
Data-driven differentiable model for dynamic prediction and control in wastewater treatmentYun-Peng Song, Wen-Zhe Wang, Yu-Qi Wang, et al.
Environmental Science & Technology|July 24, 2025
Machine Learning-Driven Dynamic Measurement of Environmental Indicators in Multiple Scenes and Multiple DisturbancesYu-Qi Wang, Han-Bo Zhou, Xiao-Qin Luo, et al.
Environmental Science & Technology|February 12, 2025
Deciphering and Mitigating of Dynamic Greenhouse Gas Emission in Urban Drainage Systems with Knowledge-Infused Graph Neural NetworkWan-Xin Yin, Ke-Hua Chen, Jia-Qiang Lv, et al.
Environmental Science and Ecotechnology|August 5, 2025
Leveraging scenario differences for cross-task generalization in water plant transfer machine learning modelsYu-Qi Wang, Xiao-Qin Luo, Han-Bo Zhou, et al.
Pageof 2