Refining satellite Altimetry-Derived gravity anomaly model with shipborne gravity using multilayer perceptron neural networks

Abstract This study refines the gravity anomaly model derived from altimetry data by employing a multilayer perceptron (MLP) neural network to integrate multi-source geophysical data (longitude, latitude, gravity anomaly, geoid height, bathymetry, and sediment thickness) based on shipborne gravity....

Täydet tiedot

Bibliografiset tiedot

Päätekijät:	Chengjun Xiao, Jinyun Guo, Chengcheng Zhu, Hui Li, Shangguo Liu, Xin Liu
Aineistotyyppi:	Artigo
Kieli:	Inglês
Julkaistu:	Nature Portfolio 2025-06-01
Sarja:	Scientific Reports
Aiheet:	Multilayer perceptron Marine gravity anomalies Shipborne gravity Multi-source geophysical data Gulf of Mexico
Linkit:	https://doi.org/10.1038/s41598-025-04619-8
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