Results 61 to 70 of about 776,810 (287)

Intelligent Maintenance Review for Robots: Multimodal Information, Deep Diagnosis and Embodied Artificial Intelligence

Advanced Robotics Research, EarlyView.
This review maps the methods to monitor robots’ health by fusing vibration, sound, control signals, vision, force, and oil information with artificial intelligence. It identifies deep learning, transfer learning, digital twins, and physics‐informed models as key methodological pathways enabling earlier diagnosis, safer human–robot collaboration, and ...
Yuting Qiao, Hongbo Wang, Naipeng Li, Shuo Wang, Yaguo Lei, Tonghai Wu, Junyi Cao   +6 more
wiley   +1 more source

Time History Gaussian Process Regression for Modeling the Dynamics of Ankle Exoskeleton User Comfort

Advanced Robotics Research, EarlyView.
Exoskeletons need to be comfortable, but the perception of comfort may change over time. This study investigated if short‐term time history directly influences comfort. No previous trials’ input features were predictive of comfort. Including the previous trial's comfort score marginally improved model accuracy compared to a model using only the current
Axl Maberry, Bo Cheng, Anne E. Martin
wiley   +1 more source

Hybrid bagging and boosting with SHAP based feature selection for enhanced predictive modeling in intrusion detection systems

Scientific Reports
The novelty and growing sophistication of cyber threats mean that high accuracy and interpretable machine learning models are needed more than ever before for Intrusion Detection and Prevention Systems. This study aims to solve this challenge by applying
Usman Ahmed, Zheng Jiangbin, Ahmad Almogren, Muhammad Sadiq, Ateeq Ur Rehman, M. T. Sadiq, Jaeyoung Choi   +6 more
doaj   +1 more source

Electricity Consumption Forecasting: An Approach Using Cooperative Ensemble Learning with SHapley Additive exPlanations

Forecasting
Electricity expense management presents significant challenges, as this resource is susceptible to various influencing factors. In universities, the demand for this resource is rapidly growing with institutional expansion and has a significant ...
Eduardo Luiz Alba, Gilson Adamczuk Oliveira, Matheus Henrique Dal Molin Ribeiro, Érick Oliveira Rodrigues   +3 more
doaj   +1 more source

Random forest Shapley additive explanations (SHAP) values.

Random forest Shapley additive explanations (SHAP) values.
In-Seok Song (17720212), Eun Sun Kim (843999), Sohee Jung (6553586), Kwang-Sig Lee (7587932), Jisu Kim (841223), Sunwoo Nam (8475585), Ki Hoon Ahn (10221265)   +6 more
core   +1 more source

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

Advanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray, Andrew R. Castillo, Manoj Kolel‐Veetil, Surya R. Kalidindi   +3 more
wiley   +1 more source

Income Inequality Games [PDF]

The paper explores different applications of the Shapley value for either inequality or poverty measures. We first investigate the problem of source decomposition of inequality measures, the so-called additive income sources inequality games, baed on the
Arthur Charpentier, Stéphane Mussard
core   +2 more sources

Calculation of exact Shapley values for explaining support vector machine models using the radial basis function kernel

Scientific Reports, 2023
Machine learning (ML) algorithms are extensively used in pharmaceutical research. Most ML models have black-box character, thus preventing the interpretation of predictions.
Andrea Mastropietro, Christian Feldmann, Jürgen Bajorath   +2 more
doaj   +1 more source

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

Advanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu, Tianshuo Wei, Yan Ge, Bo Peng, Yue Li, Maolin Wang, Peng Wen, Chao Yang, Ye Wei   +8 more
wiley   +1 more source

Integrating Machine Learning With Constant‐Potential Simulation to Unravel Charge‐Transfer Mechanisms in Electrochemical Nitrogen Fixation

Advanced Science, EarlyView.
Integrating interpretable machine learning with the fixed‐potential method reveals a novel mechanism: the catalytic activity of the electrochemical nitrogen reduction reaction is governed by partial charge transfer, induced by variations in the intermediate potential of zero charge under constant potential.
Yufei Xue, Dushuo Feng, Yuefei Zhang, Yang Zhang, Yalong Jiao, Aijun Du, Guoping Gao   +6 more
wiley   +1 more source