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Fingerprint Dive into the research topics where Tomohiro Murata is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

  • 22 Similar Profiles
Scheduling Engineering & Materials Science
Petri nets Engineering & Materials Science
Planning Engineering & Materials Science
Recommender systems Engineering & Materials Science
Genetic algorithms Engineering & Materials Science
Cellular manufacturing Engineering & Materials Science
Supply chains Engineering & Materials Science
Collaborative filtering Engineering & Materials Science

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Research Output 1985 2019

  • 302 Citations
  • 6 h-Index
  • 65 Conference contribution
  • 27 Article
  • 3 Conference article

Intermittent snapshot method for remote data synchronization from cloud on-ramp to cloud storage

Yagawa, Y., Hayasaka, M., Maki, N., Tezuka, S. & Murata, T., 2019 Jan 1, In : IEEJ Transactions on Electronics, Information and Systems. 139, 6, p. 745-756 12 p.

Research output: Contribution to journalArticle

Synchronization
Petri nets
Wide area networks
Local area networks
Degradation

Optimal electric vehicle routing for minimizing electrical energy consumption based on hybrid genetic algorithm

Chen, H. & Murata, T., 2019 Jan 1, In : Lecture Notes in Engineering and Computer Science. 2239, p. 526-531 6 p.

Research output: Contribution to journalConference article

Vehicle routing
Electric vehicles
Energy utilization
Genetic algorithms
Trucks

Production planning for closed loop supply chain with recycle parts and product life cycle

Kajiyama, R. & Murata, T., 2019 Jan 1, In : Lecture Notes in Engineering and Computer Science. 2239, p. 427-430 4 p.

Research output: Contribution to journalConference article

Supply chains
Life cycle
Profitability
Planning
Sales

Stock market trend prediction with sentiment analysis based on LSTM neural network

Jiawei, X. & Murata, T., 2019 Jan 1, In : Lecture Notes in Engineering and Computer Science. 2239, p. 475-479 5 p.

Research output: Contribution to journalConference article

Neural networks
Feature extraction
Financial markets
Long short-term memory
Deep learning

Adaptive ARIMA model based on lazy learning algorithm for short period electric load forecasting

Li, C. & Murata, T., 2018 Jan 1, Proceedings of the International MultiConference of Engineers and Computer Scientists 2018, IMECS 2018. Castillo, O., Feng, D. D., Korsunsky, A. M., Douglas, C. & Ao, S. I. (eds.). Newswood Limited, (Lecture Notes in Engineering and Computer Science; vol. 2).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Electric load forecasting
Learning algorithms
Time series