Probabilistic Forecasts of Storm Sudden Commencements From Interplanetary Shocks Using Machine Learning by A. W. Smith, I. J. Rae, C. Forsyth, D. M. Oliveira, M. P. Freeman, D. R. Jackson

“…Abstract In this study we investigate the ability of several different machine learning models to provide probabilistic predictions as to whether interplanetary shocks observed upstream of the Earth at L1 will lead to immediate (Sudden Commencements, SCs) or longer lasting magnetospheric activity (Storm Sudden Commencements, SSCs). …”
Get full text

The Optimal Machine Learning Model for the Precise Prediction of HighPerformance Concrete Strength Property by Yufeng Qian

“…The present study employs a machine learning-based support vector regression (SVR) method to implement compressive strength prediction. …”
Get full text

Decision tree-based learning and laboratory data mining: an efficient approach to amebiasis testing by Enas Al-khlifeh, Ahmad S. Tarawneh, Khalid Almohammadi, Malek Alrashidi, Ramadan Hassanat, Ahmad B. Hassanat

Subjects: Get full text

A comparative assessment of machine learning models and algorithms for osteosarcoma cancer detection and classification by Amoakoh Gyasi-Agyei

Subjects: Get full text

Finding Neural Biomarkers for Motor Learning and Rehabilitation Using an Explainable Graph Neural Network by J. Han, A. Embs, F. Nardi, S. Haar, A. A. Faisal

Subjects: Get full text

Forecasting geothermal temperature in western Yemen with Bayesian-optimized machine learning regression models by Abdulrahman Al-Fakih, Abbas Al-khudafi, Ardiansyah Koeshidayatullah, SanLinn Kaka, Abdelrigeeb Al-Gathe

Subjects: “…Machine learning…”
Get full text

Identifying Ocean Submesoscale Activity From Vertical Density Profiles Using Machine Learning by Leyu Yao, John R. Taylor, Dani C. Jones, Scott D. Bachman

Subjects: Get full text

CS-FL: Cross-Zone Secure Federated Learning with Blockchain and a Credibility Mechanism by Chongzhen Zhang, Hongye Sun, Zhaoyu Shen, Dongyu Wang

Subjects: “…federated learning…”
Get full text

A Novel Active Learning Technique for Fetal Health Classification Based on XGBoost Classifier by Kaushal Bhardwaj, Niyati Goyal, Bhavika Mittal, Vandna Sharma, Shiv Naresh Shivhare

Subjects: Get full text

RISKS REDUCING THROUGH INTELLIGENT HEADLIGHT MANAGEMENT: OPTIMIZING Q-LEARNING FOR ELECTRIC VEHICLES by Pitchaya Jamjuntr, Chanchai Techawatcharapaikul, Pannee Suanpang

Subjects: Get full text

RFMVDA: An Enhanced Deep Learning Approach for Customer Behavior Classification in E-Commerce Environments by Kwanhee Kim, Mingyu Jo, Ilkyeun Ra, Sangoh Park

Subjects: Get full text

The good, the better and the challenging: Insights into predicting high-growth firms using machine learning by Sermet Pekin, Aykut Şengül

“…This study aims to classify high-growth firms using several machine learning algorithms, including K-Nearest Neighbors, Logistic Regression with L1 (Lasso) and L2 (Ridge) Regularization, XGBoost, Gradient Descent, Naive Bayes and Random Forest. …”
Get full text

CausMatch: Causal Matching Learning With Counterfactual Preference Framework for Cross-Modal Retrieval by Chen Chen, Dan Wang

Subjects: “…Multimodal learning…”
Get full text

Conv‐ELSTM: An ensemble deep learning approach for predicting short‐term wind power by Guibin Wang, Xinlong Huang, Yiqun Li, Hong Wang, Xian Zhang, Jing Qiu

“…This article introduces a hybrid data‐driven framework that employs an ensemble deep learning model to provide highly precise short‐term wind power predictions. …”
Get full text

Predicting the delisted companies of Tehran Stock Exchange using machine learning based algorithms by Aminollah Zarghami, Meysam Doaei, Abtin Boostani

Get full text

Machine learning techniques for estimating high–temperature mechanical behavior of high strength steels by C. Yazici, F.J. Domínguez-Gutiérrez

Subjects: Get full text

Supervised machine learning reveals introgressed loci in the genomes of Drosophila simulans and D. sechellia. by Daniel R Schrider, Julien Ayroles, Daniel R Matute, Andrew D Kern

“…We developed a novel machine learning framework, called FILET (Finding Introgressed Loci via Extra-Trees) capable of revealing genomic introgression with far greater power than competing methods. …”
Get full text

Dynamic Interferometry for Freeform Surface Measurement Based on Machine Learning-Configured Deformable Mirror by Xu Chang, Yao Hu, Jintao Wang, Xiang Liu, Qun Hao

Subjects: Get full text

Multi-domain collaborative anti-jamming based on multi-agent deep reinforcement learning by Biao ZHANG, Ximing WANG, Yifan XU, Wen LI, Hao HAN, Songyi LIU, Xueqiang CHEN

Subjects: Get full text

Language-mixing in Content and Language Integrated Learning: benefit or burden? An auditory recall perspective by Thomas Caira, Mathieu Declerck, Esli Struys

Get full text