Machine learning applications for biochar studies: A mini-review
Biochar is a promising carbon sink whose application can assist in reducing carbon
emissions. Development of this technology currently relies on experimental trials, which are …
emissions. Development of this technology currently relies on experimental trials, which are …
[HTML][HTML] Machine learning assisted prediction of solar to liquid fuel production: a case study
In this era of heightened environmental awareness, the global community faces the critical
challenge of climate change. Renewable energy (RE) emerges as a vital contender to …
challenge of climate change. Renewable energy (RE) emerges as a vital contender to …
[HTML][HTML] Data Information integrated Neural Network (DINN) algorithm for modelling and interpretation performance analysis for energy systems
WM Ashraf, V Dua - Energy and AI, 2024 - Elsevier
Developing a well-predictive machine learning model that also offers improved
interpretability is a key challenge to widen the application of artificial intelligence in various …
interpretability is a key challenge to widen the application of artificial intelligence in various …
Evaluation of prediction and modeling performance using machine learning methods for thermal parameters of heat sinks under forced convection: The case of …
The capability of ML models in thermal systems is generally determined by internal
validation, while this study investigates the prediction performance of ML models with …
validation, while this study investigates the prediction performance of ML models with …
Active Learning-Based Guided Synthesis of Engineered Biochar for CO2 Capture
Biomass waste-derived engineered biochar for CO2 capture presents a viable route for
climate change mitigation and sustainable waste management. However, optimally …
climate change mitigation and sustainable waste management. However, optimally …
Modeling rapidly discriminative strategies of Cr contaminated soils through machine learning
J Wang, H Zhang, X Wang, X Liu, H Deng - Journal of Environmental …, 2024 - Elsevier
Soil washing is employed to prevent the issue of Cr re-oxidation following the remediation of
Cr-contaminated soil by transferring contaminants from the soil to the wash solution through …
Cr-contaminated soil by transferring contaminants from the soil to the wash solution through …
Removal of N-Nitrosodiphenylamine from contaminated water: A novel modeling framework using metaheuristic-based ensemble models
Investigating the complex interactions among physicochemical variables that influence the
adsorptive removal of pollutants is a challenge for conventional one-variable-at-a-time …
adsorptive removal of pollutants is a challenge for conventional one-variable-at-a-time …
Machine Learning to Characterize Biogenic Isoprene Emissions and Atmospheric Formaldehyde with Their Environmental Drivers in the Marine Boundary Layer
T Wang, S Wang, R Xue, Y Tan, S Zhang, C Gu, B Zhou - Atmosphere, 2024 - mdpi.com
Oceanic biogenic emissions exert a significant impact on the atmospheric environment
within the marine boundary layer (MBL). This study employs the extreme gradient boosting …
within the marine boundary layer (MBL). This study employs the extreme gradient boosting …
Data Information Integrated Neural Network (Diinn): Modelling Paradigm Enhancing the Model's Predictive Performance and Interpretation for Energy Systems
WM Ashraf, V Dua - Available at SSRN 4617564 - papers.ssrn.com
Developing a well-predictive machine learning based model that also offers improved
interpretability is a key challenge to widen the application of artificial intelligence in various …
interpretability is a key challenge to widen the application of artificial intelligence in various …