年単位の研究成果
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。
- 4 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
1
引用
(Scopus)
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
1
引用
(Scopus)
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
2
引用
(Scopus)
DM-LIMGA: Dual Migration Localized Island Model Genetic Algorithm—a better diversity preserver island model
Gozali, A. A. & Fujimura, S., 2019 1 1, ： : Evolutionary Intelligence.研究成果: Article
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