A Novel Feature-Engineered–NGBoost Machine-Learning Framework for Fraud Detection in Electric Power Consumption Data [PDF]
Sensors, 2021 This study presents a novel feature-engineered–natural gradient descent ensemble-boosting (NGBoost) machine-learning framework for detecting fraud in power consumption data.
Saddam Hussain +4 more
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Buildings, 2023 Multi-objective optimization problems (MOPs) in structural engineering arise as a significant challenge in achieving a balance between prediction accuracy and efficiency of the surrogate models, which are conventionally adopted as mechanics-driven models
Shixue Liang +3 more
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Uncertainty and explainable analysis of machine learning model for reconstruction of sonic slowness logs [PDF]
Artificial Intelligence in Geosciences, 2023 Logs are valuable information for oil and gas fields as they help to determine the lithology of the formations surrounding the borehole and the location and reserves of subsurface oil and gas reservoirs.
Hua Wang +6 more
doaj +4 more sources
Buildings, 2023 To ensure the safety of buildings, accurate and robust prediction of a reinforced concrete deep beam’s shear capacity is necessary to avoid unpredictable accidents caused by brittle failure.
Mao-Yi Liu, Zheng Li, Hang Zhang
doaj +2 more sources
Development and validation of predictive models for the hemodialysis adequacy index (Kt/V) using multiple linear regression and machine learning algorithms [PDF]
Frontiers in Digital HealthBackground and objectiveKt/V is a widely used indicator for assessing hemodialysis (HD) adequacy, but conventional measurement methods require blood sampling and are impractical for large-scale or real-time use.
Le-le Li +13 more
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A stacking ensemble with Pareto optimization for scalable electricity theft detection via hybrid data repair and lightweight deployment [PDF]
Scientific ReportsElectricity theft poses a significant challenge to grid reliability and utility revenues, while its detection using smart meter data is constrained by data quality issues, severe class imbalance, and practical deployment limitations.
Mohammed Ateequr Rahaman +1 more
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Salmon Consumption Behavior Prediction Based on Bayesian Optimization and Explainable Artificial Intelligence [PDF]
FoodsPredicting seafood consumption behavior is essential for fishing companies to adjust their production plans and marketing strategies. To achieve accurate predictions, this paper introduces a model for forecasting seafood consumption behavior based on an ...
Zhan Wu +4 more
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Identifying propionate metabolism-related genes as biomarkers of sepsis development and therapeutic targets [PDF]
Scientific ReportsThe treatment of sepsis is challenging due to unclear mechanisms. Propionate is increasingly seen as critical to sepsis pathophysiology by bridging gut microbiota and immunity, but the mechanisms remain unclear.
Lechen Yang +8 more
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EngineeringPressure has been introduced into power systems owing to the intermittent and uncertain nature of renewable energy. As a result, energy resource aggregators are emerging in the electricity market to realize sustainable and economic advantages through ...
Hong Tang +3 more
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Interpretable wind power probabilistic prediction based on NGBoost
Zhejiang dianli, 2023 To realize the probabilistic prediction of wind power and analyze the influencing factors of the prediction results， this paper proposes a probabilistic prediction method of wind power based on natural gradient boosting （NGBoost） and takes account of ...
LI Bingsheng +2 more
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