Enhancing Water Level Prediction Using Ensemble Machine Learning Models: A Comparative Analysis DOI
Saleh Alsulamy, Vijendra Kumar, Özgür Kişi

et al.

Water Resources Management, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 11, 2025

Language: Английский

Innovative Approaches in Regulatory Affairs: Leveraging Artificial Intelligence and Machine Learning for Efficient Compliance and Decision-Making DOI

C. S. Ajmal,

Sravani Yerram,

V S Abishek

et al.

The AAPS Journal, Journal Year: 2025, Volume and Issue: 27(1)

Published: Jan. 7, 2025

Language: Английский

Citations

4
Explainable district heating load forecasting by means of a reservoir computing deep learning architecture DOI
Adrià Serra Oliver, Alberto Ortiz, Pau Joan Cortés Forteza

et al.

Energy, Journal Year: 2025, Volume and Issue: unknown, P. 134641 - 134641

Published: Jan. 1, 2025

Language: Английский

Citations

4
Explainable AI-Enhanced Human Activity Recognition for Human–Robot Collaboration in Agriculture DOI Creative Commons
Lefteris Benos, Dimitrios Tsaopoulos, Aristotelis C. Tagarakis

et al.

Applied Sciences, Journal Year: 2025, Volume and Issue: 15(2), P. 650 - 650

Published: Jan. 10, 2025

This study addresses a critical gap in human activity recognition (HAR) research by enhancing both the explainability and efficiency of classification collaborative human–robot systems, particularly agricultural environments. While traditional HAR models often prioritize improving overall accuracy, they typically lack transparency how sensor data contribute to decision-making. To fill this gap, integrates explainable artificial intelligence, specifically SHapley Additive exPlanations (SHAP), thus interpretability model. Data were collected from 20 participants who wore five inertial measurement units (IMUs) at various body positions while performing material handling tasks involving an unmanned ground vehicle field harvesting scenario. The results highlight central role torso-mounted sensors, lumbar region, cervix, chest, capturing core movements, wrist sensors provided useful complementary information, especially for load-related activities. XGBoost-based model, selected mainly allowing in-depth analysis feature contributions considerably reducing complexity calculations, demonstrated strong performance HAR. findings indicate that future should focus on enlarging dataset, investigating use additional placements, real-world trials enhance model’s generalizability adaptability practical applications.

Language: Английский

Citations

3
Revolutionizing Prostate Cancer Therapy: Artificial intelligence – based Nanocarriers for Precision Diagnosis and Treatment DOI
Moein Shirzad,

Afsaneh Salahvarzi,

Sobia Razzaq

et al.

Critical Reviews in Oncology/Hematology, Journal Year: 2025, Volume and Issue: unknown, P. 104653 - 104653

Published: Feb. 1, 2025

Language: Английский

Citations

3
Enhancing Water Level Prediction Using Ensemble Machine Learning Models: A Comparative Analysis DOI
Saleh Alsulamy, Vijendra Kumar, Özgür Kişi

et al.

Water Resources Management, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 11, 2025

Language: Английский

Citations

3