Machine learning in environmental research: common pitfalls and best practices
Machine learning (ML) is increasingly used in environmental research to process large data
sets and decipher complex relationships between system variables. However, due to the …
sets and decipher complex relationships between system variables. However, due to the …
Application of machine learning in groundwater quality modeling-A comprehensive review
Groundwater is a crucial resource across agricultural, civil, and industrial sectors. The
prediction of groundwater pollution due to various chemical components is vital for planning …
prediction of groundwater pollution due to various chemical components is vital for planning …
Machine learning assisted materials design and discovery for rechargeable batteries
Y Liu, B Guo, X Zou, Y Li, S Shi - Energy Storage Materials, 2020 - Elsevier
Abstract Machine learning plays an important role in accelerating the discovery and design
process for novel electrochemical energy storage materials. This review aims to provide the …
process for novel electrochemical energy storage materials. This review aims to provide the …
Data quantity governance for machine learning in materials science
Y Liu, Z Yang, X Zou, S Ma, D Liu… - National Science …, 2023 - academic.oup.com
Data-driven machine learning (ML) is widely employed in the analysis of materials structure–
activity relationships, performance optimization and materials design due to its superior …
activity relationships, performance optimization and materials design due to its superior …
Binary dragonfly optimization for feature selection using time-varying transfer functions
Abstract The Dragonfly Algorithm (DA) is a recently proposed heuristic search algorithm that
was shown to have excellent performance for numerous optimization problems. In this …
was shown to have excellent performance for numerous optimization problems. In this …
Application of novel data-mining technique based nitrate concentration susceptibility prediction approach for coastal aquifers in India
In water resource management and pollution control research, prediction of nitrate
concentration in groundwater gets utmost priority in the last few years. Thus, our current …
concentration in groundwater gets utmost priority in the last few years. Thus, our current …
Assessment of compressive strength of Ultra-high Performance Concrete using deep machine learning techniques
The compressive strength of Ultra-High Performance Concrete (UHPC) is a function of the
type, property and quantities of its material constituents. Empirically capturing this …
type, property and quantities of its material constituents. Empirically capturing this …
[HTML][HTML] Prediction modelling framework comparative analysis of dissolved oxygen concentration variations using support vector regression coupled with multiple …
X Nong, C Lai, L Chen, D Shao, C Zhang, J Liang - Ecological Indicators, 2023 - Elsevier
Dissolved oxygen (DO) is an essential indicator for assessing water quality and managing
aquatic environments, but it is still a challenging topic to accurately understand and predict …
aquatic environments, but it is still a challenging topic to accurately understand and predict …
Review of resampling techniques for the treatment of imbalanced industrial data classification in equipment condition monitoring
Y Yuan, J Wei, H Huang, W Jiao, J Wang… - … Applications of Artificial …, 2023 - Elsevier
In an actual industrial scenario, machines typically operate normally for the majority of the
time, with malfunctions occurring only occasionally. As a result, there is very little recorded …
time, with malfunctions occurring only occasionally. As a result, there is very little recorded …
Machine learning modelling for predicting non-domestic buildings energy performance: A model to support deep energy retrofit decision-making
Non-domestic buildings contribute 20% of the UK's annual carbon emissions. A contribution
exacerbated by its ageing stock of which only 7% is considered new-build. Consequently …
exacerbated by its ageing stock of which only 7% is considered new-build. Consequently …