- 學位論文
在虛實整合系統中應用隨機森林和可拓類神經網路改善良率及預防性診斷之實證研究
Utilizing Random Forest and Extension Neural Network to Improve Yield and Fault Diagnosis in Cyber Physical System: Two Empirical Studies
並列摘要
abstract hide
延伸閱讀
- Chen, C. H. (2022). 藥物基因體導向之抗憂鬱藥物治療反應預測研究：以隨機森林方法應用於插補基因表現量資料 [master's thesis, National Taiwan University]. Airiti Library. https://doi.org/10.6342/NTU202203958
- 萬絢、馬弘霖（2020）。綠化生態模型系列研究：比較隨機森林演算法和支援向量機在都市多類別影像判釋的差異。嶺東學報，(46)，151-172。https://www.airitilibrary.com/Article/Detail?DocID=18111912-202006-202006290016-202006290016-151-172
- 黃建勳、謝尚賢（2021）。隨機森林及支持向量機應用於結構BIM建模及出圖人力成本預測能力之比較分析。中國土木水利工程學刊，33(5)，389-398。https://doi.org/10.6652/JoCICHE.202109_33(5).0006
- Wagh, N., & Deshpande, D. M. (2014). Investigations on Incipient Fault Diagnosis of Power Transformer Using Neural Networks and Adaptive Neurofuzzy Inference System. Applied Computational Intelligence and Soft Computing, (2014), 135-143. https://doi.org/10.1155/2014/845815
- Ma, H. Y., & Su, C. T. (2010). Applying Hierarchical Genetic Algorithm Based Neural Network and Multiple Objective Evolutionary Algorithm to Optimize Parameter Design with Dynamic Characteristics. 品質學報, 17(4), 311-325. https://www.airitilibrary.com/Article/Detail?DocID=10220690-201008-201009100028-201009100028-311-325