YUJIRO WADA

Last Updated :2020/09/01

Affiliations, Positions
Graduate School of Advanced Science and Engineering, Lecturer, Collaborative Research Laboratory
Web Site
E-mail
wadayhiroshima-u.ac.jp
Other Contact Details
1-4-1, Kagamiyama, Higashi-Hiroshima,Hiroshima,739-8527,JAPAN, Japan
TEL : (+81)82-424-7779 FAX : (+81)
Self-introduction
Please see above URL.

Basic Information

Major Professional Backgrounds

  • 2017/04, 2019/03, National Maritime Research Institute, Researcher
  • 2011/04, 2014/06, JFE Engineering Corporation, Pipeline system design

Educational Backgrounds

  • Hiroshima University, School of Engineering, 2006/04, 2009/03
  • Hiroshima University, Graduate School of Engineering, 2009/04, 2011/03
  • Hiroshima University, Graduate School of Engineering, 2014, 2017/03

Research Fields

  • Engineering;Integrated engineering;Naval and maritime engineering
  • Complex systems;Social / Safety system science;Social systems engineering / Safety system

Research Keywords

  • Maritime logistics,Maritime economics,Systems engineering,Simulation,System Dynamics

Affiliated Academic Societies

  • International Association of Maritime Economists
  • JAPAN SOCIETY OF LOGISTICS AND SHIPPING ECONOMICS
  • JAPAN INSTITUTE OF NAVIGATION
  • THE JAPAN SOCIETY OF NAVAL ARCHITECTS AND OCEAN ENGINEERS

Educational Activity

Course in Charge

  1. 2020, Undergraduate Education, 1Term, Technical English

Research Activities

Academic Papers

  1. Evaluation of GHG emission measures based on shipping and shipbuilding market forecasting, 8th International Conference on Transportation and Logistics (T-LOG 2020)
  2. A system dynamics model for shipbuilding demand forecasting, JOURNAL OF MARINE SCIENCE AND TECHNOLOGY, 23(2), 236-252
  3. Evaluation of AIS data and port calling data using ship operation data of a shipping company, 28th Annual Conference of the International Association of Maritime Economists
  4. A Study on Reliability of Ship Movement Data, The 33rd Asian-Pacific Technical Exchange and Advisory Meeting on Marine Structures (TEAM2019)
  5. Shipping Market Forecasting Using Deep Learning and Big Data of Maritime Logistics, The 33rd Asian-Pacific Technical Exchange and Advisory Meeting on Marine Structures (TEAM2019)
  6. Predicting a dry bulk freight index by deep learning with global vessel movement data, 26th ISTE International Conference on Transdisciplinary Engineering (TE2019)
  7. Dry Bulk Freight Index Forecasting based on Satellite AIS Data using Deep Learning, 27th Annual Conference of the International Association of Maritime Economists(IAME2019)
  8. A Study on the Improvement and Application of System Dynamics Model for Demand Forecasting of Ships, International Conference on Computer Applications in Shipbuilding 2017 (ICCAS2017)
  9. A Study on System Dynamics Model for the Demand Forecasting of Shipbuilding, International Marine Design Conference 2015
  10. A Study on the System Dynamics Model and its Application for Demand Forecasting of Ships

Invited Lecture, Oral Presentation, Poster Presentation

  1. Dry Bulk Freight Index Forecasting based on Satellite AIS Data using Deep Learning, Joint Seminar of JSPS (Japan Society for the Promotion of Science) and the Suez Canal Authority, 2019/07/01, Without Invitation
  2. Shipbuilding demand and Freight rate forecasting using Maritime Logistics Big data, International Seminar on the Usage of AIS and Vessel Movement Data for Logistics Research and Industry, 2019/12/18, Without Invitation

External Funds

Acceptance Results of Competitive Funds

  1. 2020/04/01, 2024/03/31
  2. 2019, 2020

Social Activities

Organizing Academic Conferences, etc.

  1. International Seminar on the Usage of AIS and Vessel Movement Data for Logistics Research and Industry, 2019/12, 2019/12
  2. 2020/06, 2020/06

Other Social Contributions

  1. IMO MEPC 73, International Maritime Organization, 2018/10/22, 2018/10/26

History as Peer Reviews of Academic Papers

  1. 2020, Journal of Navigation