Ensemble modelling technique for a micro-drilling process based on a two-stage bootstrap-Reference-Cited by-同舟云学术

Ensemble modelling technique for a micro-drilling process based on a two-stage bootstrap

Published:2018-06-01 Issue:3 Volume:51 Page:503-519
ISSN:0305-215X
Container-title:Engineering Optimization
language:en
Short-container-title:Engineering Optimization

Author:

Ouyang Linhan¹,Zhou Dequn¹,Park Chanseok²^ORCID,Chen Jianxiong³,Tu Yiliu⁴

Affiliation:

1. College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, People’s Republic of China

2. Department of Industrial Engineering, Pusan National University, Busan, Republic of Korea

3. School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, People’s Republic of China

4. Department of Mechanical and Manufacturing Engineering, University of Calgary, Calgary, Canada

Funder

National Natural Science Foundation of China

the Postdoctoral Science Foundation of Jiangsu Province

the China Postdoctoral Science Foundation

the Fundamental Research Fund for the Central Universities

Natural Science Foundation for Jiangsu Institutions

Publisher

Informa UK Limited

Subject

Applied Mathematics,Industrial and Manufacturing Engineering,Management Science and Operations Research,Control and Optimization,Computer Science Applications

Link

https://www.tandfonline.com/doi/pdf/10.1080/0305215X.2018.1472251

Reference39 articles.

1. Modeling of EDM responses by support vector machine regression with parameters selected by particle swarm optimization

2. Robust parameter design in embedded high-variability production processes: an alternative approach to mitigating sources of variability

3. Closed-loop control in ultrafast laser milling process using laser triggered plasma

4. Combining neural networks and genetic algorithms for optimising the parameter design of the inter-metal dielectric process

5. Gaussian Process Model - An Exploratory Study in the Response Surface Methodology

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