Results 51 to 60 of about 61,068 (254)
Price Prediction for Fresh Agricultural Products Based on a Boosting Ensemble Algorithm
MathematicsThe time series of agricultural prices exhibit brevity and considerable volatility. Considering that traditional time series models and machine learning models are facing challenges in making predictions with high accuracy and robustness, this paper ...
Nana Zhang +3 more
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Digital Health, 2022 Background To develop a highly discriminative machine learning model for the prediction of intensive care unit admission (>24h) using the easily available preoperative information from electronic health records.
Lan Lan +8 more
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Case Studies in Construction Materials, 2022 In this paper, the SHapley Additive exPlanation (SHAP) is utilized in conjunction with the ensemble machine learning (EML) model to study the creep behaviors of recycled aggregate concrete (RAC) for the first time. Five typical EML models, such as Random
Jinpeng Feng +5 more
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Advanced Engineering Materials, EarlyView.Thermomechanical fatigue tests of laser beam powder bed fusion (PBF‐LB) Inconel 718 show that the additively manufactured material reaches almost the lifetimes of conventionally‐rolled material under no‐dwell conditions. Introducing dwell times at the maximum temperature markedly reduces the lifetimes due to pronounced grain boundary sliding associated
Stefan Guth +6 more
wiley +1 more source
Features selection and prediction for IoT attacks
High-Confidence Computing, 2022 Cyber-attacks and anomaly detection are growing concerns in the Internet of Things (IoT). With fast-growing deployment and opportunities, an increasing number of attacks put IoT devices under the threat of continuous exploitation and danger.
Jingyi Su, Shan He, Yan Wu
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Current Status and Challenges in Data Collection for Aerospace Coatings Deposited by Plasma Spraying
Advanced Engineering Materials, EarlyView.An innovative approach has been integrated into the GRENAT project to optimize plasma spraying and coating performance. Raw materials are accelerated and melted in the plasma generated by torches, creating coatings. Monitoring sensors collect process data which are combined with ex situ characterization data.
Lila Randriamananjara +8 more
wiley +1 more source
Next MaterialsThis work deals with the machine learning techniques used to build predictive models to determine the phases in complex concentrated alloys (CCAs). Two different approaches were employed to determine the presence of phases.
Kaven A.S. +2 more
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Advanced Engineering Materials, EarlyView.This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer +4 more
wiley +1 more source
New AI‐Assisted Approach for Expanding the Solution Space: Application to Lattice Structure Design
Advanced Engineering Materials, EarlyView.This work introduces an innovative framework for designing structured materials by ex panding the design space through reparameterization of qualitative variables into continuous structural descriptors. Combined with machine‐learning‐based prediction and multi‐objective optimization, the approach enables the discovery of novel lattice architectures ...
G. H. Gahimbare +5 more
wiley +1 more source
PSPSO: A package for parameters selection using particle swarm optimization
SoftwareX, 2021 This paper reports a high-level python package for selecting machine learning algorithms and ensembles of machine learning algorithms parameters by using the particle swarm optimization (PSO) algorithm named PSPSO.
Ali Haidar +4 more
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