Results 61 to 70 of about 4,489 (189)

Harnessing Machine Learning to Understand and Design Disordered Solids

Advanced Intelligent Discovery, EarlyView.
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley   +1 more source

Gaussian Process Regression (GPR)-based missing data imputation and its uses for bridge structural health monitoring

Advances in Bridge Engineering
Abstract Structural health monitoring (SHM) apparatuses rely on continuous measurement and analysis to assess the safety condition of a target system. However, in field applications, the SHM framework is often hampered by practical issues.
Dalmasso, Matteo, Civera, Marco, De Biagi, Valerio, Chiaia, Bernardino   +3 more
openaire   +3 more sources

Optimizing aerodynamic shape of benchmark problems using an improved Gaussian process regression algorithm

Engineering Applications of Computational Fluid Mechanics
The current challenges encountered in Surrogate-Based Optimization (SBO) primarily stem from the substantial number of function calls essential for accurate evaluations.
Youtao Xue, Yuxin Yang, Shaobo Yao, Wenwen Zhao, Lihua Chen   +4 more
doaj   +1 more source

Application of machine learning techniques to simulate the evaporative fraction and its relationship with environmental variables in corn crops

Ecological Processes, 2022
Background The evaporative fraction (EF) represents an important biophysical parameter reflecting the distribution of surface available energy. In this study, we investigated the daily and seasonal patterns of EF in a multi-year corn cultivation located ...
Terenzio Zenone, Luca Vitale, Daniela Famulari, Vincenzo Magliulo   +3 more
doaj   +1 more source

Accelerating Discovery of Organic Molecular Crystals via Materials Informatics and Autonomous Experiments

Advanced Intelligent Discovery, EarlyView.
Materials informatics and autonomous experimentation are transforming the discovery of organic molecular crystals. This review presents an integrated molecule–crystal–function–optimization workflow combining machine learning, crystal structure prediction, and Bayesian optimization with robotic platforms.
Takuya Taniguchi, Kazuki Ishizaki, Ryo Fukasawa   +2 more
wiley   +1 more source

A Comprehensive Comparative Study of Active Learning Schemes for Nanophotonics Design

Advanced Intelligent Discovery, EarlyView.
Active learning (AL) strategies are benchmarked for the binary design of planar multilayer nanophotonic structures. Factorization machines combined with quantum annealing (QA) become effective as dimensionality increases. Hybrid QA provides the strongest results for 100‐layer problems, highlighting the importance of optimization method selection in ...
Serang Jung, Seongmin Kim, Jaehyun Park, Chaeyoung Park, Zhihao Xu, Sanghyo Hwang, Baiqing Ye, Youn sang Kim, Sun‐Kyung Kim, Tengfei Luo, Eungkyu Lee   +10 more
wiley   +1 more source

Gaussian Process Regression (GPR) Method for the Prediction of Rate Coefficients of Gas-phase Reactions in Chemical Ionization Mass Spectrometry

, 2022
Reaction kinetics of chemical ionization mass spectrometry (CI-MS) based ion-molecule reactions is an important component in the quantification of trace-level volatile organic compounds (VOCs). The rate coefficients of such CI-MS reactions are predicted using the Gaussian process regression (GPR) machine learning method from the dipole moment ...
openaire   +1 more source

A Review on Recent Trends of Bioinspired Soft Robotics: Actuators, Control Methods, Materials Selection, Sensors, Challenges, and Future Prospects

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This article reviews the current state of bioinspired soft robotics. The article discusses soft actuators, soft sensors, materials selection, and control methods used in bioinspired soft robotics. It also highlights the challenges and future prospects of this field.
Abhirup Sarker, Tamzid Ul Islam, Md. Robiul Islam   +2 more
wiley   +1 more source

Machine Learning Paradigm for Advanced Battery Electrolyte Development

Carbon Energy, EarlyView.
Electrolyte materials determine ion transport kinetics within the bulk and interphases, ultimately influencing the performance of battery systems. As data‐driven paradigms increasingly reshape materials discovery, this review provides an application‐oriented exploration of the intersection between machine learning and electrolyte science. By evaluating
Chang Su, Mengfan Pei, Keyu Chen, Xigao Jian, Fangyuan Hu   +4 more
wiley   +1 more source

Radiation Mapping: A Gaussian Multi-Kernel Weighting Method for Source Investigation in Disaster Scenarios

Sensors
Structural collapses caused by accidents or disasters could create unexpected radiation shielding, resulting in sharp gradients within the radiation field.
Songbai Zhang, Qi Liu, Jie Chen, Yujin Cao, Guoqing Wang   +4 more
doaj   +1 more source