Results 21 to 30 of about 25,341,143 (317)

Hardenability prediction model of 8620 steel based on machine learning

工程科学学报
8620 steel is a critical alloy widely used in the manufacturing of gears designed to transmit substantial power and endure heavy loads. Its applications span vital sectors, including transportation, lifting equipment, locomotive traction, and wind power ...
Binbin WANG, Dexin ZHU, Sen WU, Fuyong LI, Shengyong HUANG, Honghui WU   +5 more
doaj   +1 more source

Artificial Intelligence-Assisted Machine Learning Methods for Forecasting Green Bond Index: A Comparative Analysis

Ekonomi, Politika & Finans Araştırmaları Dergisi
The main objective of this study is to contribute to the literature by forecasting green bond index with different machine learning models supported by artificial intelligence.
Ahmed İhsan Şimşek, Yunus Emre Gür, Emre Bulut   +2 more
doaj   +1 more source

A Robust Interpretable Deep Learning Classifier for Heart Anomaly Detection Without Segmentation

, 2020
Traditionally, abnormal heart sound classification is framed as a three-stage process. The first stage involves segmenting the phonocardiogram to detect fundamental heart sounds; after which features are extracted and classification is performed.
Denman, Simon, Dissanayake, Theekshana, Fernando, Tharindu, Fookes, Clinton, Ghaemmaghami, Houman, Sridharan, Sridha   +5 more
core   +1 more source

Application of SHAP on CatBoost classification for identification of variabels characterizing food insecurity occurrences in Aceh Province households

Jurnal Natural, 2023
Classification is the process of building a model that can distinguish between different classes of data. The model aims to predict the class of testing data based on patterns or relationships learned from training data.
MUHAMMAD SUBIANTO, INA YATUL ULYA, EVI RAMADHANI, BAGUS SARTONO, ALFIAN FUTUHUL HADI   +4 more
doaj   +1 more source

A machine learning-based study of serological biomarkers for predicting intestinal necrosis in patients with adhesive small bowel obstruction

Xin yixue
ObjectiveTo explore the value of machine learning-based serological markers in predicting irreversible transmural intestinal necrosis (ITIN) in surgical patients with adhesive small bowel obstruction (ASBO).
Ruming LIU, Youlong ZHU, Jiawei FENG
doaj   +1 more source

Machine learning-guided synthesis of advanced inorganic materials

, 2019
Synthesis of advanced inorganic materials with minimum number of trials is of paramount importance towards the acceleration of inorganic materials development.
Chouhan, Tushar, Golani, Prafful, Guan, Cuntai, Liu, Zheng, Lu, Yuhao, Tang, Bijun, Wang, Han, Xu, Manzhang, Xu, Quan, Zhou, Jiadong   +9 more
core   +1 more source

Adjustment of the Grace Score and Shap Analysis in Stemi Patients

Computer Methods and Programs in Biomedicine
The GRACE (Global Registry of Acute Coronary Events) risk score is a well-established tool for predicting major cardiovascular events in patients with acute coronary syndrome. However, its application in acute ST-segment elevation myocardial infarction (STEMI) requires refinement to enhance its predictive accuracy in clinical settings.In this study, we
Jin, Cao, Jingyi, Liu, Xiaoqiang, Wang, Xiaoyun, Wang   +3 more
openaire   +2 more sources

Active Learning‐Accelerated Discovery of Fibrous Hydrogels with Tissue‐Mimetic Viscoelasticity

Advanced Functional Materials, EarlyView.
Active learning accelerates the design of fibrous hydrogels that mimic the viscoelasticity of native tissues. By integrating multi‐objective optimization and closed‐loop experimentation, this approach efficiently identifies optimal formulations from thousands of possibilities and decouples elasticity and viscosity. The resulting hydrogels offer tunable
Zhengkun Chen, Zheyuan Miao, Gary Tom, Austin H. Cheng, Elizaveta Gusarova, Benjamen Zondag, Tianyi Wu, Dianoosh Kalhori, Boris Hinz, Milad Abolhasani, Alán Aspuru‐Guzik, Eugenia Kumacheva   +11 more
wiley   +1 more source

OSL investigations at Hardisty, Alberta, Canada: Sections HD03, HD04 & HD05 [PDF]

, 2015
This report is concerned with optically stimulated luminescence (OSL) investigations of a number of sediment stratigraphies in the Battle River Valley area, near Hardisty, east-central Alberta.
Kinnaird, T.C., Munyikwa, K., Sanderson, D.C.W.   +2 more
core   +4 more sources

Interpretable landslide susceptibility evaluation using a BP neural network model optimized by multiple algorithms

Zhongguo dizhi zaihai yu fangzhi xuebao
Current landslide susceptibility evaluation methods predominantly rely on statistical techniques and machine learning models, both of which are prone to errors related to sample quality and parameter selection.
Hao LU, Shuqiang LU, Jiale LI, Zhen LIN, Yong LI   +4 more
doaj   +1 more source