Results 91 to 100 of about 59,339 (255)

Wearable exoskeleton robot control using radial basis function‐based fixed‐time terminal sliding mode with prescribed performance

Asian Journal of Control, EarlyView.
Abstract This paper tackles the problem of robust and accurate fixed‐time tracking in human–robot interaction and deals with uncertainties. This work introduces a control approach for a wearable exoskeleton designed specifically for rehabilitation tasks.
Mahmoud Abdallah, Yassine Kali, Maarouf Saad, Raouf Fareh, Maamar Bettayeb   +4 more
wiley   +1 more source

Research of output characteristic fitting of eddy-current sensor based on radial-basis function neural network

Gong-kuang zidonghua, 2013
In view of problem that eddy-current sensor cannot reflect measured physical quantity accurately caused by higher nonlinear of output characteristic parameter, the paper proposed a scheme of using RBF neural network to fit output characteristic parameter
YOU Wen-jian, LIANG Bing, LI Yin-jun
doaj  

Machine Learning‐Driven Prediction and Optimization of Cu‐Based Catalysts for CO2 Hydrogenation to Methanol

Carbon and Hydrogen, EarlyView.
A machine‐learning framework integrating multimodel prediction, feature selection, and SHAP interpretability is developed to uncover structure–performance relationships of Cu‐based CO2‐to‐methanol catalysts. The optimized XGBoost model and an online prediction platform enable accurate selectivity prediction and data‐driven catalyst design.
Conglong Su, Zhangkai Jing, Qiuming Zhou, Yuan Zhu, Sishi Ye, Tianye Wang, Kuo Chen, Xuebin Luan, Zhigang Tang, Run Xu, Chaopeng Hou, Hongwei Li   +11 more
wiley   +1 more source

RBF neural net based classifier for the AIRIX accelerator fault diagnosis [PDF]

, 2000
The AIRIX facility is a high current linear accelerator (2-3.5kA) used for flash-radiography at the CEA of Moronvilliers France. The general background of this study is the diagnosis and the predictive maintenance of AIRIX.
Delaunay, G., Delvaux, J., Merle, E., Mouillet, M., Ribes, J. C.   +4 more
core   +2 more sources

Ensemble‐based soil liquefaction assessment: Leveraging CPT data for enhanced predictions

Civil Engineering Design, Volume 7, Issue 1, Page 23-35, March 2025.
Abstract This study focuses on predicting soil liquefaction, a critical phenomenon that can significantly impact the stability and safety of structures during seismic events. Accurate liquefaction assessment is vital for geotechnical engineering, as it informs the design and mitigation strategies needed to safeguard infrastructure and reduce the risk ...
Arsham Moayedi Far, Masoud Zare
wiley   +1 more source

A system for monitoring NO2 emissions from biomass burning by using GOME and ATSR-2 data [PDF]

, 2002
In this paper, we propose a system for monitoring abnormal NO2 emissions in troposphere by using remote-sensing sensors. In particular, the system aims at estimating the amount of NO2 resulting from biomass burning by exploiting the synergies between the
Bruzzone, Lorenzo, Casadio, S., Cossu, Roberto, Sini, Francesco, Zehner, Claus   +4 more
core  

An adiabatic neural network for RBF approximation

Neural Computing & Applications, 1994
Numerous studies have addressed nonlinear functional approximation by multilayer perceptrons (MLPs) and RBF networks as a special case of the more general mapping problem. The performance of both these supervised network models intimately depends on the efficiency of their learning process.
B. Truyen, N. Langloh, J. Cornelis
openaire   +2 more sources

Membrane Engineering for Battery Systems: Bridging Design Principles and Frontier Applications

ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
The review emphasizes membrane separators' role in battery performance and safety, covering redox flow, lithium‐ion, and solid‐state batteries. It reviews advances in membrane materials (e.g., polymer electrolytes, hybrid composites) and ion transport mechanisms, while addressing challenges like dendrite growth and crossover losses.
Xiaoqun Zhou, Justice Delali Akoto, Rui Tan, Jun Ma   +3 more
wiley   +1 more source

AI‐driven circular economy optimization in waste management: A review of current evidence

Environmental Progress &Sustainable Energy, EarlyView.
Abstract The integration of artificial intelligence (AI) and machine learning (ML) in waste management has the potential to significantly advance circular economy objectives by enhancing efficiency, reducing waste, and optimizing resource recovery. However, realising these benefits depends on addressing significant technical, economic, and systemic ...
David Bamidele Olawade, Ram Narayan Yadav, James O Ijiwade, Ojima Z. Wada   +3 more
wiley   +1 more source

Algorithms selection and adaptation in accord with architecture for RBF neural network based face authentication SoC

, 2007
International audienceThis paper describes the algorithms applied to a Radial Basis Function (RBF) neural network. This neural network is used as a classifier to design a human face authentication system.
Jay, Jacques, Pierrefeu, Lionel
core   +1 more source