首页|Reports Summarize Machine Learning Findings from North China Electric Power University (Machine Learning Insights In Predicting Heavy Metals Interaction With Biochar)
Reports Summarize Machine Learning Findings from North China Electric Power University (Machine Learning Insights In Predicting Heavy Metals Interaction With Biochar)
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NETL
NSTL
Springer Nature
Current study results on Machine Learning have been published. According to news originating from Beijing, People’s Republic of China, by NewsRx correspondents, research stated, “The use of machine learning (ML) in the field of predicting heavy metals interaction with biochar is a promising field of research, mainly because of the growing understanding of how removal efficiency is affected by characteristic variables, reaction conditions and biochar properties. The practical application in biochar still faces large challenges, such as difficulties in data collection, inadequate algorithm development, and insufficient information.” Financial support for this research came from National Natural Science Foundation of China (NSFC). Our news journalists obtained a quote from the research from North China Electric Power University, “However, the quantity, quality, and representation of data have a large impact on the accuracy, efficiency, and generalizability of machine learning tasks. From this perspective, the present data descriptors, the efficiency of machine learning-aided property and performance prediction, the interpretation of underlying mechanisms and complicated relationships, and some potential ways to augment the data are discussed regarding the interactions of heavy metals with biochar. Finally, future perspectives and challenges are discussed, and an enhanced model performance is proposed to reinforce the feasibility of a particular perspective.”
BeijingPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningNorth China Electric Power University
NETL
NSTL
Springer Nature
