APPLICATION OF GAUSSIAN PROCESS REGRESSION TO IMPROVE THE EFFICIENCY OF TSUNAMI PREDICTIONS IN PROBABILISTIC TSUNAMI HAZARD ANALYSIS

Authors

Naoto Kihara (ORCID: https://orcid.org/0000-0003-0128-8598)
Tetsushi KURITA
Kazuma SUZUKI

Publication Details

Journal: Japanese Journal of JSCE
Published: 2025-01-01
DOI: https://doi.org/10.2208/jscejj.25-17193
Primary Topic: Earthquake and Tsunami Effects
Type: article
Field-Weighted Citation Impact: 0.00

Controls

|||

ALL TIME

JAN

FEB

MAR

APR

MAY

JUN

JUL

AUG

SEP

OCT

article

APPLICATION OF GAUSSIAN PROCESS REGRESSION TO IMPROVE THE EFFICIENCY OF TSUNAMI PREDICTIONS IN PROBABILISTIC TSUNAMI HAZARD ANALYSIS

Naoto Kihara, Tetsushi KURITA, Kazuma SUZUKI

Jan 1, 2025

Japanese Journal of JSCE

Earthquake and Tsunami Effects

article

APPLICATION OF GAUSSIAN PROCESS REGRESSION TO IMPROVE THE EFFICIENCY OF TSUNAMI PREDICTIONS IN PROBABILISTIC TSUNAMI HAZARD ANALYSIS

Naoto Kihara, Tetsushi KURITA, Kazuma SUZUKI

January 1, 2025article en

Abstract

No abstract available for this paper.

Japanese Journal of JSCEVol. 81(17)

Openalex Percentile: Top 66%

Earthquake and Tsunami Effects

DOI Source OpenAlex

AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

APPLICATION OF GAUSSIAN PROCESS REGRESSION TO IMPROVE THE EFFICIENCY OF TSUNAMI PREDICTIONS IN PROBABILISTIC TSUNAMI HAZARD ANALYSIS — Naoto Kihara, Tetsushi KURITA, et al. · Japanese Journal of JSCE (2025) | TGRS Research Map | TGRS