Results 161 to 170 of about 201,886 (307)

RMSE: Stata module to calculate raw or adjusted RMSE (Root MSE)

rmse provides a fast and easy way to calculate RMSE, useful for checking prediction accuracy.rmse, root mean squared error ...
Roy Wada
core  

A Versatile‐Designable Framework for Active and Programmable Shape‐Morphing Soft Matter Systems: From Inverse Design to Closed‐Loop Control

Advanced Science, EarlyView.
A versatile framework integrates addressable electrothermal actuation and strain‐constraint mechanisms to construct programmable shape‐morphing soft matter systems. By combining an analytical inverse design strategy for high‐fidelity 3D surface reconstruction with deep learning‐based closed‐loop control, this approach enables zero‐energy shape locking,
Kai Liu, Peiling Xie, Ruitong Song, Banghan Liu, Rui Guo, Jiu‐an Lv   +5 more
wiley   +1 more source

Physics‐Guided Descriptors Enable Data‐Efficient Prediction of Battery Coulombic Efficiency

Advanced Science, EarlyView.
This work integrates multiscale simulations with data‐driven approaches to predict Coulombic efficiency (CE). Multiscale simulations of battery systems are performed to extract Physics‐Guided descriptors and construct a dataset. Machine learning models trained on this dataset are then subjected to interpretable analysis to identify the most influential
Qintao Sun, Xuewei Gu, Yulin Jie, Hao Yang, Shuhong Jiao, Chao Tang, Yangping Sheng, Yuhao Lu, Ruiguo Cao, Tao Cheng   +9 more
wiley   +1 more source

Multiscale Coupling From Mastication to Retronasal Aroma Perception: The PG‐DTCFN Model and Multiphysics Simulation

Advanced Science, EarlyView.
Using grilled lamb skewers as a model system, this work builds a multiscale coupling framework from oral processing to retronasal aroma perception, reveals dual‐kinetic release patterns and Electroencephalogram‐characterized central encoding features, and proposes an interpretable physics‐guided deep learning model validated by multiphysics simulation,
Che Shen, Xiongfeng He, Zihao Li, Zidong Chen, Jiajin Sun, Xinyu Jiang, Yunhui Zhang, Lizhang Wu, Ran Wang, Jingnan Lu, Bo Wang, Kezhou Cai, Baocai Xu   +12 more
wiley   +1 more source

A Closed‐Loop Framework for Inverse Design: Dynamic Training and Intelligent Optimization for Heterostructured Materials

Advanced Science, EarlyView.
To accelerate the inverse design of heterostructured metal matrix composites, a closed‐loop scientific machine learning framework integrates continual learning prediction with NSGA‐II‐PMCP optimization. The framework maps microstructural descriptors to strength, toughness, and modulus, expands high‐quality Pareto solutions, and guides experimentally ...
Zhiyan Zhong, Xueru Zheng, Xiao Zhou, Zhengheng Tao, Wan Han, Jingyi Pan, Dian Wu, Ning Gao, Lei Liu, Zhongyang Wang, Fanchao Meng, Tongxiang Fan   +11 more
wiley   +1 more source

Evaluation du potentiel d’énergie éolienne au Liban

Revue des Énergies Renouvelables, 2014
Dans cette étude, les caractéristiques du vent sont analysées en utilisant les données de la vitesse du vent recueillies pour cinq stations météorologiques au Liban et disponibles pour au moins une année (2 ans pour Klaiaat, 10 ans pour les Cèdres, 7 ans
G. Al Zohbi, P. Hendrick, P. Bouillard   +2 more
doaj  

Enhanced Ionic Conductivity at the Solid Electrolyte Interphase of Oxygen‐Doped Li6PS5Cl

Advanced Science, EarlyView.
Machine‐learned molecular dynamics and machine‐learning‐based phase identification reveal the kinetically formed SEI at buried Li | Li6PS5Cl interfaces. The SEI is dominated by Li2S‐based anion‐substituted phases, while oxygen doping enhances SEI ionic conductivity.
Sojeong Yang, Sungwoo Kang, Atefeh Yadegarifard, Hyun‐Jae Lee, Nongnuch Artrith, Jung‐Hoon Lee, Byungju Lee   +6 more
wiley   +1 more source

On the Mathematical Relationship Between RMSE and NSE Across Evaluation Scenarios

Model evaluation metrics play a crucial role in hydrology, where accurate prediction of continuous variables such as streamflow and rainfall–runoff is essential for sustainable water resources management and climate resilience. Among these metrics, the Nash–Sutcliffe efficiency (NSE) is the most widely adopted, while the Root Mean Squared Error (RMSE ...
openaire   +1 more source

Enhancing Super‐Resolution Spatial Transcriptomics Data by Transfer Learning

Advanced Science, EarlyView.
SpotZoomer employs a transfer‐learning‐based strategy to enhance the resolution of Visium data by leveraging available high‐resolution priors. The resulting super‐resolved maps enable sharper delineation of cell boundaries and more precise inference of cell–cell communication patterns that would otherwise remain obscured at native resolution.
Xiaoyu Li, Lihua Zhang, Wenwen Min
wiley   +1 more source

Human‐Guided Bayesian Optimization Enables High‐Throughput Laser Annealing of Mesoporous SiOx Anodes for Lithium‐Ion Batteries

Advanced Science, EarlyView.
An empirical‐aided active learning framework is developed to optimize high‐throughput laser‐induced photothermal annealing of silicon suboxide anodes. By integrating probabilistic machine learning with empirical domain knowledge, this approach achieves optimal electrochemical performance using limited experiments.
Chaeyoung Park, Yeongje Lee, Sunho Jeong, Eungkyu Lee   +3 more
wiley   +1 more source