A review on missing values for main challenges and methods
Several recent reviews summarize common missing value analysis methods. However,
none of them provide a systematic and in-depth summary of the analytical challenges and …
none of them provide a systematic and in-depth summary of the analytical challenges and …
Modern data science for analytical chemical data–A comprehensive review
E Szymańska - Analytica chimica acta, 2018 - Elsevier
Efficient and reliable analysis of chemical analytical data is a great challenge due to the
increase in data size, variety and velocity. New methodologies, approaches and methods …
increase in data size, variety and velocity. New methodologies, approaches and methods …
Data mining and analytics in the process industry: The role of machine learning
Data mining and analytics have played an important role in knowledge discovery and
decision making/supports in the process industry over the past several decades. As a …
decision making/supports in the process industry over the past several decades. As a …
Technology opportunity analysis using hierarchical semantic networks and dual link prediction
Z Liu, J Feng, L Uden - Technovation, 2023 - Elsevier
Technology opportunity analysis using network analysis and link prediction has attracted the
interest of both academia and industry. However, there are several unresolved issues with …
interest of both academia and industry. However, there are several unresolved issues with …
Delineating the controlling mechanisms of arsenic release into groundwater and its associated health risks in the Southern Loess Plateau, China
The mechanisms controlling arsenic (As) enrichment and mobilization associated with
human health risk assessment of groundwater in the Longdong Basin, located in the …
human health risk assessment of groundwater in the Longdong Basin, located in the …
A systematic review of machine learning-based missing value imputation techniques
T Thomas, E Rajabi - Data Technologies and Applications, 2021 - emerald.com
Purpose The primary aim of this study is to review the studies from different dimensions
including type of methods, experimentation setup and evaluation metrics used in the novel …
including type of methods, experimentation setup and evaluation metrics used in the novel …
Predictive modeling and analysis of key drivers of groundwater nitrate pollution based on machine learning
Y Deng, X Ye, X Du - Journal of Hydrology, 2023 - Elsevier
Nitrate comtamination of shallow groundwater in agricultural intensification regions is a
prevalent and global environment issue affecting food security, human health, and the water …
prevalent and global environment issue affecting food security, human health, and the water …
Data cleaning in the process industries
In the past decades, process engineers are facing increasingly more data analytics
challenges and having difficulties obtaining valuable information from a wealth of process …
challenges and having difficulties obtaining valuable information from a wealth of process …
Identification of SARS-CoV-2–induced pathways reveals drug repurposing strategies
The global outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)
necessitates the rapid development of new therapies against coronavirus disease 2019 …
necessitates the rapid development of new therapies against coronavirus disease 2019 …
Targeted metabolite profiling of Salvia rosmarinus Italian local ecotypes and cultivars and inhibitory activity against Pectobacterium carotovorum subsp. carotovorum
Introduction The development of agriculture in terms of sustainability and low environmental
impact is, at present, a great challenge, mainly in underdeveloped and marginal …
impact is, at present, a great challenge, mainly in underdeveloped and marginal …