Using mega-trend-diffusion and artificial samples in small data set learning for early flexible manufacturing system scheduling knowledge
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Publication:856675
DOI10.1016/j.cor.2005.05.019zbMath1102.90324OpenAlexW2010354425MaRDI QIDQ856675
Tung-I Tsai, Chih-Sen Wu, Yao-San Lina, Der-Chiang Li
Publication date: 7 December 2006
Published in: Computers \& Operations Research (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.cor.2005.05.019
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Uses Software
Cites Work
- Principle of information diffusion
- A diffusion-neural-network for learning from small samples
- A review of machine learning in dynamic scheduling of flexible manufacturing systems
- Dynamic scheduling system utilizing machine learning as a knowledge acquisition tool
- Indentifying attributes for knowledge-based development in dynamic scheduling environments
- Using an unsupervized neural network and decision tree as knowledge acquisition tools for FMS scheduling
- Simulation metamodelling with neural networks: An experimental investigation
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