Research field (3)：
Marine and maritime engineering
, Soft computing
, Mechanics and mechatronics
Research theme for competitive and other funds (6)：
2023 - 2026 Assembly sequence and path planning based on machine learning for large-scale products
2022 - 2026 Bubble Diameter Distribution Estimation for Propeller Cavitation Using Photometric Stereo and Deep Learning
2020 - 2023 A Study on Fluid Characteristics of Wake Field Utilizing Hull Forms and Flow Field Database
2020 - 2023 Study on hull fouling evaluation model by topological data analysis of multiple time series data
2020 - 2023 Basic development of self-powering active dynamic absorber based on parametric resonance
2017 - 2019 Reduction of vibration on shipboard by passive type dynamic absorber and rational optimization
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Papers (3)：
Tomoyuki Taniguchi, Masahito Takezawa, Kohei Matsuo. Development of High Precision Process Simulation Based on Multi-Agent System for Shipbuilding. 2022. 36. 89-100
Yasuo Ichinose, Tomoyuki Taniguchi. A Curved Surface Representation Method for Convolutional Neural Network of Wake Field Prediction. Journal of Marine Science and Technology. 2022. 27. 1. 637-647
Tomoyuki Taniguchi, Yusuke Yoshitomi. Detecting similar piping design failures in shipbuilding based on sub-graph isomorphism identification. 2021
Taniguchi Tomoyuki, Ichinose Yasuo. Hull form design support tool based on machine learning. COMPIT 2020. 2020
TANIGUCHI Tomoyuki, ICHINOSE Yasuo. A stern wake prediction method based on machine learning. Proceedings of the Annual Conference of JSAI. 2020. 2020. 0. 3Rin457-3Rin457
