Pureに変更を加えた場合、すぐここに表示されます。

Fingerprint Shigeru Fujimuraが取り組む研究トピックをご確認ください。これらのトピックラベルは、この人物の研究に基づいています。これらを共に使用することで、固有の認識が可能になります。

  • 3 同様のプロファイル
Scheduling Engineering & Materials Science
Genetic algorithms Engineering & Materials Science
Evolutionary algorithms Engineering & Materials Science
Just in time production Engineering & Materials Science
Flow Shop Mathematics
Process planning Engineering & Materials Science
Industry Engineering & Materials Science
Job Shop Scheduling Problem Mathematics

ネットワーク 最近の共同研究。丸をクリックして詳細を確認しましょう。

研究成果 2007 2019

  • 122 引用
  • 5 h指数
  • 48 Conference contribution
  • 17 Article
  • 1 Conference article

A Mix Integer Programming Model for Bi-objective Single Machine with Total Weighted Tardiness and Electricity Cost under Time-of-use Tariffs

Kurniawan, B., Gozali, A. A., Weng, W. & Fujimura, S., 2019 1 9, 2018 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2018. IEEE Computer Society, p. 137-141 5 p. 8607420. (IEEE International Conference on Industrial Engineering and Engineering Management; 巻数 2019-December).

研究成果: Conference contribution

Integer programming
Electricity
Costs
Genetic algorithms
Scheduling

Building Deep Neural Network Model for Short Term Electricity Consumption Forecasting

Chandramitasari, W., Kurniawan, B. & Fujimura, S., 2019 3 22, Proceeding - 2018 International Symposium on Advanced Intelligent Informatics: Revolutionize Intelligent Informatics Spectrum for Humanity, SAIN 2018. Institute of Electrical and Electronics Engineers Inc., p. 43-48 6 p. 8673340. (Proceeding - 2018 International Symposium on Advanced Intelligent Informatics: Revolutionize Intelligent Informatics Spectrum for Humanity, SAIN 2018).

研究成果: Conference contribution

Electricity
Feedforward neural networks
Time series
Industry
Deep neural networks
Preserver
Island Model
Genetic Models
Islands
Migration

Abnormal data analysis in process industries using deep-learning method

Song, W., Weng, W. & Fujimura, S., 2018 2 9, 2017 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2017. IEEE Computer Society, 巻 2017-December. p. 2356-2360 5 p.

研究成果: Conference contribution

Industrial plants
Industry
Sensors
Deep learning
Process industry

A control method to save machine energy in production

Weng, W., Yang, Y. & Fujimura, S., 2018 7 4, : : IOP Conference Series: Materials Science and Engineering. 383, 1, 012014.

研究成果: Conference article

Energy conservation
Scheduling
Just in time production
Energy utilization
Processing