Results 121 to 130 of about 1,537 (209)

A hybrid analytical-machine learning framework for data-driven modeling of soliton solutions in the complex Ginzburg-Landau equation. [PDF]

Sci Prog
Muhammad J, Tedjani AH, Yao F, Younas U.
europepmc   +1 more source

A Hybrid ML‐PDE Framework for Predicting Breaking Ocean Waves

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 4, August 2026.
Abstract Wave breaking plays a central role in ocean dynamics, dissipating wave energy and shaping the evolution of the sea surface. Yet, breaking remains difficult to model: envelope‐based models efficiently capture nonlinear wave evolution and are interpretable but exclude breaking, while high‐fidelity direct numerical simulations resolve breaking ...
Y. Liu, T. A. A. Adcock, T. S. van den Bremer, D. Eeltink   +3 more
wiley   +1 more source

On certain novel numerical and analytical solutions for the pure-cubic Schrödinger equation in optical fibers with Kerr nonlinearity. [PDF]

Sci Rep
Tariq KU, Khan R, Alsharidi AK, Almusallam N.   +3 more
europepmc   +1 more source

Physics‐Informed Machine Learning Framework to Retroactively Estimate Mantle Thermal Convection From Partial Geophysical Observations

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 4, August 2026.
Abstract Mantle convection drives the solid Earth, powering plate motions, volcanism, and earthquakes while regulating planetary heat loss. Reconstructing its history is hampered by sparse, noisy observations concentrated near the surface and the present day. Here I develop an inverse physics‐informed neural network framework to estimate mantle thermal
Atsushi Nakao
wiley   +1 more source

Soliton structures and dynamical characteristics of fractional nonlinear waves in the classical Boussinesq framework. [PDF]

Sci Rep
Rimu NN, Islam MA, Dey P.
europepmc   +1 more source

Attention and Geological Knowledge Guided Spectral‐Spatial Networks for Geochemical Anomalies Recognition

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 4, August 2026.
Abstract Achieving both accuracy and interpretability in deep learning models for geochemical anomaly recognition constitutes a significant challenge. To overcome this challenge, this study developed a novel interpretable dual‐branch network combining a spectral attention bidirectional RNN (BiRNN) branch and a spatial attention CNN branch guided with ...
Yihui Xiong, Zhixiang Liang, Zhiyi Chen, Yao Fan, Renguang Zuo   +4 more
wiley   +1 more source

Local Adaptation to Current but Not Future Climate in Seasonally Dry Tropical Forests: Population Genomic Evidence in a Neotropical Legume Tree

Evolutionary Applications, Volume 19, Issue 8, August 2026.
ABSTRACT Neotropical seasonally dry biomes are amongst the world's most threatened ecosystems and are predicted to lose more biodiversity with climate change. The capacity of natural populations to respond to these changes depends on their genetic variation, but is poorly understood in most Neotropical seasonally dry forest species.
Francisco J. Velásquez‐Puentes, Walter Durka, Colin Hughes, R. Toby Pennington, Jens J. Ringelberg, Renske E. Onstein, Christopher D. Barratt   +6 more
wiley   +1 more source

Dynamical study of optical soliton solutions to the Lakshmanan-Porsezian-Daniel equation by using [Formula: see text]-model expansion approach. [PDF]

Sci Rep
Alharthi MR, Inayat M, Abbas M, Birhanu A, Yousaf MZ, El-Zahar ER.   +5 more
europepmc   +1 more source

Kinetic parameter prediction using neural networks identifies limitations to C4 photosynthesis

New Phytologist, Volume 251, Issue 3, Page 1578-1594, August 2026.
Schematic overview of the generation of artificial training data and training of neural networks in C4TUNE. Summary Kinetic models of photosynthesis enable time‐resolved predictions of traits related to this key process and provide the means to identify factors limiting photosynthesis.
Philipp Wendering, John Ferguson, Rudan Xu, Johannes Kromdijk, Zoran Nikoloski   +4 more
wiley   +1 more source

Dynamical analysis of lump, breather, M-shaped and other wave profiles propagating in a nonlinear PDE describing the nonlinear low-pass electrical transmission lines. [PDF]

Sci Rep
Baber MZ, Shafee A, Ceesay B, Ahmed N.
europepmc   +1 more source