Iyan E. Mulia - Concepedia

Concepedia

Author

Iyan E. Mulia

The University of Tokyo ORCID

Also Known As

I Mulia, I. E. Mulia, Iyan E Mulia, Iyan E. Mulia, Iyan Eka Mulia, Iyan Ekka MULIA, Iyan Mulia, Mulia, Iyan E.

94

Publications

1.2K

Citations

23

H-Index

70

Concepts

All Affiliations

The University of Tokyo Association for the Development of Earthquake Prediction GNS Science RIKEN Center for Advanced Intelligence Project University of Bath

IE

About

Iyan E. Mulia is an author at The University of Tokyo specializing in engineering, tsunami science, and earth science.

Top Concepts

#	Concept	H-Index	Publications	Citations
1	Engineering	19	25	794
2	Civil Engineering	13	13	371
3	Management	1	1	15
4	Social Sciences	1	1	31
5	Computer Science	1	1	36

Iyan E. Mulia

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35

Publications

1.2K

Citations

23

H-Index

	Year	Citations
Regional probabilistic tsunami hazard assessment associated with active faults along the eastern margin of the Sea of Japan Iyan E. Mulia, Takeo Ishibe, Kenji Satake, Earth Planets and Space	2020	97
Tsunami data assimilation of Cascadia seafloor pressure gauge records from the 2012 Haida Gwaii earthquake Aditya Riadi Gusman, A. F. Sheehan, Kenji Satake, Geophysical Research Letters EngineeringSeismic WaveCoastal ModelingTsunami Data AssimilationEarthquake Hazards	2016	79
Effects of uncertainty in fault parameters on deterministic tsunami hazard assessment: examples for active faults along the eastern margin of the Sea of Japan Kenji Satake, Takeo Ishibe, Satoko Murotani, Earth Planets and Space Fault ParametersCoastal EngineeringEngineeringCoastal ModelingEarthquake Hazards	2022	78
Machine learning-based tsunami inundation prediction derived from offshore observations Iyan E. Mulia, Naonori Ueda, Takemasa Miyoshi, Nature Communications	2022	76
A Tsunami Warning System Based on Offshore Bottom Pressure Gauges and Data Assimilation for Crete Island in the Eastern Mediterranean Basin Yuchen Wang, Mohammad Heidarzadeh, Kenji Satake, Journal of Geophysical Research Solid Earth EngineeringEarthquake HazardsCrete IslandEarthquake ScenarioOceanography	2020	56
Hybrid ANN–GA model for predicting turbidity and chlorophyll-a concentrations Iyan E. Mulia, Harold Tay, K. Roopsekhar, Journal of Hydro-environment Research Hybrid Ann–ga ModelPhotosynthesisWater QualityCrop Growth Modeling	2013	51
Real-time forecasting of near-field tsunami waveforms at coastal areas using a regularized extreme learning machine Iyan E. Mulia, Toshiyuki Asano, Akio NAGAYAMA Coastal Engineering Forecasting MethodologyTsunami ScienceEngineeringMachine LearningData Science	2015	44
Developments of Tsunami Observing Systems in Japan Iyan E. Mulia, Kenji Satake Frontiers in Earth Science GeophysicsUnconventional PlatformsTsunami ScienceCoastal VolcanoesEngineering	2020	38
Simulation of the 2018 Tsunami Due to the Flank Failure of Anak Krakatau Volcano and Implication for Future Observing Systems Iyan E. Mulia, Shingo Watada, Tung‐Cheng Ho, Geophysical Research Letters EngineeringSeismic WaveFlank FailureEarthquake HazardsOceanography	2020	36
Applying a Deep Learning Algorithm to Tsunami Inundation Database of Megathrust Earthquakes Iyan E. Mulia, Aditya Riadi Gusman, Kenji Satake Journal of Geophysical Research Solid Earth EngineeringMachine LearningEarthquake HazardsEarthquake ScenarioSeismic Hazard	2020	36

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