Results 101 to 110 of about 6,285,273 (279)

Mean Squared Error (MSE) of the four interpolation methods.

, 2016
Mean Squared Error (MSE) of the four interpolation methods.
Colin M. Beale (647716), Penny Relf (3164823), Mark S. Parsons (3164844), Dave Wainwright (3164841), Julian Small (3164832), Tallulah Gullett (3164847), Peter J. Mayhew (638353), David Baker (11642), Terry J. Crawford (3164835), Paul Robertson (3164826), Sinead Barrett (3164829), Sam Ellis (3164838)   +11 more
core   +1 more source

LLMs as Representation Generators for Gradient‐Free Scientific Optimization: A Case Study in Battery Fast Charging

Advanced Science, EarlyView.
Large language models serve as representation generators for gradient‐free scientific optimization. Two complementary approaches produce executable battery‐charging policies either directly or through LLM‐designed neural representations coupled to Bayesian optimization.
Ge Lei, Ferran Brosa Planella, Sterling G. Baird, Samuel J. Cooper   +3 more
wiley   +1 more source

Nanoscale Buried Interface Control in Silicone Hydrogels Enables a Biointerface Engineering Platform

Advanced Science, EarlyView.
A hydrophilic coating with controllable nanoscale thickness is applied to commercial silicone hydrogel contact lenses. By combining comprehensive multi‐modal three‐dimensional characterization with an advanced algorithm, the thickness and chemical information of these multilayered structures are resolved.
Po‐Hsiang Chen, Jia‐Hua Wang, Ching Chen, Shih‐Hsuan Fu, Rajan Deepan Chakravarthy, Hsin‐Chieh Lin   +5 more
wiley   +1 more source

Transforming oil market analysis: A novel GAN + LSTM predictive framework

Next Energy
A novel method of predicting the crude oil WTI futures prices based on a data set covering April 12, 2009 through January 7, 2024. To capture complex market dynamics more precisely, it incorporates key market factors such as open, high, and low price ...
Prity Kumari, G.Y. Chandan, Satish Kumar M   +2 more
doaj   +1 more source

Improved Skills for Predicting Sub‐Seasonal to Seasonal Global Sea Surface Temperature

Advanced Science, EarlyView.
Addressing the critical Sub‐seasonal to Seasonal predictability gap, this study presents CAS‐Canglong, a novel deep learning framework. By leveraging 3D Swin‐Transformers to capture long‐range ocean interactions, the model demonstrates superior skill over traditional GCMs.
Longhao Wang, Xuanze Zhang, Ruby L. Leung, Francis H. S. Chiew, Amir AghaKouchak, Kairan Ying, Yongqiang Zhang   +6 more
wiley   +1 more source

Data‐Driven and Physics‐Informed Modeling Perspectives for Soft Manipulators: From SINDy to Hybrid Intelligence

Advanced Science, EarlyView.
This Perspective charts the modeling landscape for soft manipulators, spanning sparse system identification, neural dynamics, physics‐informed models and hybrid intelligence. We examine how physics, data, sensing, adaptation and control can assume complementary roles within this landscape, and provide a framework for selecting modeling approaches ...
Wenbo Hui, Yunyi Wang, Teng Zhang, Yang Chen, Min Pan   +4 more
wiley   +1 more source

Snapshot Spatiotemporal‐Spectral Imaging Enabled by Joint Photonic Encoding

Advanced Science, EarlyView.
Spectra4D enables snapshot spatiotemporal‐spectral imaging by combining high‐speed DMD temporal modulation with CMOS‐integrated Fabry‐Pérot spectral encoding. From a single 2D measurement, a dual‐mask‐guided reconstruction network recovers multiple time‐resolved hyperspectral frames, enabling high‐fidelity observation of rapidly evolving spatial ...
Chunyu Chen, Junren Wen, Hao Sha, Chenying Yang, Ziyang Chen, Xiaochen Feng, Taiqin Chen, Wenzhen Zou, Xiangyu Chen, Xiangyang Ji, Guojun Liu, Yongbing Zhang   +11 more
wiley   +1 more source

Comparison of AI Models for Predicting Shelf Life of Roasted Coffee Drink

Transactions on Informatics and Data Science
This paper explores the application of artificial intelligence (AI), specifically artificial neural networks (ANN), to predict the shelf life of roasted coffee beverages. The research focuses on two advanced AI models: a competitive neural network based
Sumit Goyal
doaj   +1 more source

On the mean square error associated with adaptive generalized ridge regression

, 1980
Some numerical results are presented for generalized ridge regression where the additive constants are based on the data. The adaptive estimator so obtained is compared with the least‐squares estimator on the basis of mean square error (MSE). It is shown
McLachlan G.J.
core   +1 more source

Enriched Soil Organic Carbon Underpins Long‐Term Stable Crop Productivity Across China's Croplands

Advanced Science, EarlyView.
Quantifying the nonlinear relationships and causal effects of soil organic carbon (SOC) on crop stability reveals specific critical thresholds and saturation points. This partitions the national SOC spectrum into three functional phases. Integrating these spatial delineations with high‐resolution maps of marginal gains pinpoints regions with the ...
Yuyang Huang, Yulin Shangguan, Zhongkui Luo, Peng Zhu, David Makowski, Zhenzhong Zeng, Qingxu Ma, Min Wei, Yuanyuan Du, Su Ye, Zhou Shi, Songchao Chen   +11 more
wiley   +1 more source