Extreme gradient boosting-inspired process optimization algorithm for manufacturing engineering applications
出版年份 2023 全文链接
标题
Extreme gradient boosting-inspired process optimization algorithm for manufacturing engineering applications
作者
关键词
-
出版物
MATERIALS & DESIGN
Volume 226, Issue -, Pages 111625
出版商
Elsevier BV
发表日期
2023-01-14
DOI
10.1016/j.matdes.2023.111625
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- Explainable machine learning models for predicting the axial compression capacity of concrete filled steel tubular columns
- (2022) Celal Cakiroglu et al. CONSTRUCTION AND BUILDING MATERIALS
- Geometry evolution prediction and process settings influence in profiled ring rolling
- (2022) Irene Mirandola et al. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
- Incorporation of machine learning in additive manufacturing: a review
- (2022) Ali Raza et al. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
- Deep Learning in Sheet Metal Bending With a Novel Theory-Guided Deep Neural Network
- (2021) Shiming Liu et al. IEEE-CAA Journal of Automatica Sinica
- Machine Learning-Based Models for the Estimation of the Energy Consumption in Metal Forming Processes
- (2021) Irene Mirandola et al. Metals
- Mechanistic artificial intelligence (mechanistic-AI) for modeling, design, and control of advanced manufacturing processes: Current state and perspectives
- (2021) Mojtaba Mozaffar et al. JOURNAL OF MATERIALS PROCESSING TECHNOLOGY
- OPPORTUNITIES AND CHALLENGES IN METAL FORMING FOR LIGHTWEIGHTING: REVIEW AND FUTURE WORK
- (2020) Jian Cao et al. JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME
- Online prediction of mechanical properties of hot rolled steel plate using machine learning
- (2020) Qian Xie et al. MATERIALS & DESIGN
- Manufacturing of advanced smart tooling for metal forming
- (2019) Jian Cao et al. CIRP ANNALS-MANUFACTURING TECHNOLOGY
- Modeling the uncertainty in response surface methodology through optimization and Monte Carlo simulation: An application in stamping process
- (2019) Aneirson Francisco da Silva et al. MATERIALS & DESIGN
- A comparison of several machine learning techniques for the centerline segregation prediction in continuous cast steel slabs and evaluation of its performance
- (2018) P.J. García Nieto et al. JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS
- CAE-based process design for improving formability in hot stamping with partial cooling
- (2018) Eiichi Ota et al. JOURNAL OF MATERIALS PROCESSING TECHNOLOGY
- Deep learning for determining a near-optimal topological design without any iteration
- (2018) Yonggyun Yu et al. STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
- Closed-loop control of product properties in metal forming
- (2016) J.M. Allwood et al. CIRP ANNALS-MANUFACTURING TECHNOLOGY
- Mathematical definition of the 3D strain field of the ring in the radial-axial ring rolling process
- (2016) Luca Quagliato et al. INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES
- Displacement prediction of landslide based on generalized regression neural networks with K -fold cross-validation
- (2016) Ping Jiang et al. NEUROCOMPUTING
- Metal forming beyond shaping: Predicting and setting product properties
- (2015) A.E. Tekkaya et al. CIRP ANNALS-MANUFACTURING TECHNOLOGY
- Set-up of radial–axial ring-rolling process: Process worksheet and ring geometry expansion prediction
- (2015) G.A. Berti et al. INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES
- Forming process optimization for non-axisymmetrical complex component based on FEM simulation and experiment
- (2014) Xu-bin Li et al. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
- Bulk forming of sheet metal
- (2012) M. Merklein et al. CIRP ANNALS-MANUFACTURING TECHNOLOGY
- Complete modeling and parameter optimization for virtual ring rolling
- (2010) Z.W. Wang et al. INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES
- Optimization of roll forming process parameters—a semi-empirical approach
- (2009) John Paralikas et al. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
- Application of a feasible formability diagram for the effective design in stamping processes of automotive panels
- (2009) Dae-Cheol Ko et al. MATERIALS & DESIGN
- Multi-objective optimization of sheet metal forming process using Pareto-based genetic algorithm
- (2008) Liu Wei et al. JOURNAL OF MATERIALS PROCESSING TECHNOLOGY
- An optimisation strategy for industrial metal forming processes
- (2008) M. H. A. Bonte et al. STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
- Probabilistic design of sheet-metal die by finite element method
- (2007) Ilker Demir et al. MATERIALS & DESIGN
Discover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversationBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started