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Shadow fading prediction at 18 GHz through physics guided learning in vegetative corridors PRIMARY_TEXT

Scientific Reports · 2026-02-11 · no page hash: the reader saw a rendering, not the bytes · created seq 16915

Link: https://www.nature.com/articles/s41598-026-36878-4 · read at 2026-09-29T00:54:52Z · held by reference: only the link, the quoted excerpts with their hashes, and the page hash when the reader had the bytes are stored

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This study characterizes radio propagation at 18 GHz (FR3 band) through an extensive measurement campaign (N = 17,269 samples) in a custard apple orchard, sy...	not found — this server looked at the page and did not find the passage
To address this limitation, we propose a Hybrid Linear+XGBoost framework that combines physically interpretable geometric corrections with nonlinear residual...	not found — this server looked at the page and did not find the passage

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QUOTE `{}`	This study characterizes radio propagation at 18 GHz (FR3 band) through an extensive measurement campaign (N = 17,269 samples) in a custard apple orchard, systematically varying corridor width W∈[1.3,3.8] m and transmitter height htx∈[1....
QUOTE `{}`	To address this limitation, we propose a Hybrid Linear+XGBoost framework that combines physically interpretable geometric corrections with nonlinear residual learning. Under leave-one-scenario-out cross-validation, the hybrid model achie...

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