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Class-overlap undersampling based on Schur decomposition for Class-imbalance problems
The class-imbalance problem is an important area that plagues machine learning and data
mining researchers. It is ubiquitous in all areas of the real world. At present, many methods …
mining researchers. It is ubiquitous in all areas of the real world. At present, many methods …
ML-based pre-deployment SDN performance prediction with neural network boosting regression
Software defined networking (SDN) has been proposed as an effective approach to improve
network management efficiency and increase network intelligence in various networks …
network management efficiency and increase network intelligence in various networks …
Ensemble machine learning-based approach with genetic algorithm optimization for predicting bond strength and failure mode in concrete-GFRP mat anchorage …
Glass fiber-reinforced polymer (GFRP) bar reinforced concrete structures are susceptible to
bonding failure because of the low bond strength between GFRP bars and concrete. In this …
bonding failure because of the low bond strength between GFRP bars and concrete. In this …
Intelligent prediction model of mechanical properties of ultrathin niobium strips based on XGBoost ensemble learning algorithm
ZH Wang, YF Liu, T Wang, JG Wang, YM Liu… - Computational Materials …, 2024 - Elsevier
Ultrathin niobium strips with different thicknesses are prepared by an accumulative rolling
process. The tensile test of the ultrathin niobium strips is carried out, and the microstructure …
process. The tensile test of the ultrathin niobium strips is carried out, and the microstructure …
Estimation of syngas yield in hydrothermal gasification process by application of artificial intelligence models
Quality syngas production with higher moles of hydrogen and methane are the primary
objective of gasification process which is dependent upon the process parameters and …
objective of gasification process which is dependent upon the process parameters and …
Modelling biochemical oxygen demand in a large inland aquaculture zone of India: Implications and insights
Water quality surveillance is tough, and a specific timely management is necessary for the
inland aquaculture ponds and ecology as well. Real time quality monitoring involves the …
inland aquaculture ponds and ecology as well. Real time quality monitoring involves the …
An emission predictive system for CO and NOx from gas turbine based on ensemble machine learning approach
N Pachauri - Fuel, 2024 - Elsevier
The gas turbine in a combined cyclic power plant (CCPP) produces harmful gases like
carbon monoxide (CO) and nitrogen oxide (NOx) into the atmosphere. It is evident to monitor …
carbon monoxide (CO) and nitrogen oxide (NOx) into the atmosphere. It is evident to monitor …
Spatial risk assessment of maritime transportation in offshore waters of China using machine learning and geospatial big data
X Zhou - Ocean & Coastal Management, 2024 - Elsevier
Maritime transportation plays a crucial role in global trade and economic development.
However, this industry is exposed to various risks (eg, natural disasters), which can cause …
However, this industry is exposed to various risks (eg, natural disasters), which can cause …
Robust drought forecasting in Eastern Canada: Leveraging EMD-TVF and ensemble deep RVFL for SPEI index forecasting
Drought stands as a highly perilous natural catastrophe that impacts numerous facets of
human existence. Drought data is nonstationary and noisy, posing challenges for accurate …
human existence. Drought data is nonstationary and noisy, posing challenges for accurate …
Prediction of cotton FPAR and construction of defoliation spraying prescription map based on multi-source UAV images
Efficient and accurate spraying of cotton defoliant is a vital part of cotton production; the
traditional way of spraying cotton defoliant will cause waste of pesticides and environmental …
traditional way of spraying cotton defoliant will cause waste of pesticides and environmental …