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Machine learning methods for small data challenges in molecular science
Small data are often used in scientific and engineering research due to the presence of
various constraints, such as time, cost, ethics, privacy, security, and technical limitations in …
various constraints, such as time, cost, ethics, privacy, security, and technical limitations in …
Machine learning accelerates the materials discovery
J Fang, M ** machine learning-based predictive regression models for …
In this study, we introduce the count-based Morgan fingerprint (C-MF) to represent chemical
structures of contaminants and develop machine learning (ML)-based predictive models for …
structures of contaminants and develop machine learning (ML)-based predictive models for …
Predicting heavy metal adsorption on soil with machine learning and map** global distribution of soil adsorption capacities
Studying heavy metal adsorption on soil is important for understanding the fate of heavy
metals and properly assessing the related environmental risks. Existing experimental …
metals and properly assessing the related environmental risks. Existing experimental …
Deep learning based data-driven model for detecting time-delay water quality indicators of wastewater treatment plant influent
Y Zhang, C Li, H Duan, K Yan, J Wang… - Chemical Engineering …, 2023 - Elsevier
Rapid and accurate detection of time-delayed water quality indicators (WQIs) is the key to
achieving fast feedback regulation of wastewater treatment plants (WWTPs) that enables its …
achieving fast feedback regulation of wastewater treatment plants (WWTPs) that enables its …
Revealing drivers of haze pollution by explainable machine learning
Many places on earth still suffer from a high level of atmospheric fine particulate matter
(PM2. 5) pollution. Formation of a particulate pollution event or haze episode (HE) involves …
(PM2. 5) pollution. Formation of a particulate pollution event or haze episode (HE) involves …
Spatial heterogeneity modeling of water quality based on random forest regression and model interpretation
F Wang, Y Wang, K Zhang, M Hu, Q Weng… - Environmental …, 2021 - Elsevier
A systematic understanding of the spatial distribution of water quality is critical for successful
watershed management; however, the limited number of physical monitoring stations has …
watershed management; however, the limited number of physical monitoring stations has …
Taking the leap between analytical chemistry and artificial intelligence: A tutorial review
The last 10 years have witnessed the growth of artificial intelligence into different research
areas, emerging as a vibrant discipline with the capacity to process large amounts of …
areas, emerging as a vibrant discipline with the capacity to process large amounts of …
Optimization of a novel engineered ecosystem integrating carbon, nitrogen, phosphorus, and sulfur biotransformation for saline wastewater treatment using an …
The denitrifying sulfur (S) conversion-associated enhanced biological phosphorus removal
(DS-EBPR) process for treating saline wastewater is characterized by its unique microbial …
(DS-EBPR) process for treating saline wastewater is characterized by its unique microbial …