Identifying the Time of Step Change and the Source of Mean Shift in Multivariate Process Using Convolutional Neural Networks
碩士 === 國立成功大學 === 工業與資訊管理學系 === 107 === Detecting and identifying the mean shift in the manufacturing process has always been an important issue. An effective detection method can help engineers figure out the root causes of the shift so as to improve or restore the underlying manufacture process. I...
Main Authors: | Kai-ChunChien, 簡愷均 |
---|---|
Other Authors: | Tai-Yue Wang |
Format: | Others |
Language: | zh-TW |
Published: |
2019
|
Online Access: | http://ndltd.ncl.edu.tw/handle/drxa5g |
Similar Items
-
Identifying the Source of Multivariate Process Shifts by Artificial Neural Networks and Support Vector Machine
by: Ping-Ru Yuan, et al.
Published: (2006) -
Identifying the Source of Multivariate Process Shifts by Artificial Neural Networks and Support Vector Machine
by: Ping-Ru Yuan, et al.
Published: (2006) -
Identifying the Source of Mean Shifts for the Multivariate Normal Process Using a Novel Statistical Approach
by: CHOU,YU-CHING, et al.
Published: (2016) -
Multivariate Convolutional Neural network for time series classification
by: Tu, Yao-Chung, et al.
Published: (2017) -
Multivariate Time Series Data Transformation for Convolutional Neural Network
by: Chen-Yi YANG, et al.
Published: (2018)