Oversampling Application of Identifying 3D Selective Laser Sintering Yield by Hybrid Mathematical Classification Models
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Yilin Guo & Wen Feng Lu & Jerry Ying Hsi Fuh, 2021. "Semi-supervised deep learning based framework for assessing manufacturability of cellular structures in direct metal laser sintering process," Journal of Intelligent Manufacturing, Springer, vol. 32(2), pages 347-359, February.
- Mengrui Zhu & Yun Yang & Xiaobing Feng & Zhengchun Du & Jianguo Yang, 2023. "Robust modeling method for thermal error of CNC machine tools based on random forest algorithm," Journal of Intelligent Manufacturing, Springer, vol. 34(4), pages 2013-2026, April.
- Akshit Kurani & Pavan Doshi & Aarya Vakharia & Manan Shah, 2023. "A Comprehensive Comparative Study of Artificial Neural Network (ANN) and Support Vector Machines (SVM) on Stock Forecasting," Annals of Data Science, Springer, vol. 10(1), pages 183-208, February.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Saima Akhtar & Sulman Shahzad & Asad Zaheer & Hafiz Sami Ullah & Heybet Kilic & Radomir Gono & Michał Jasiński & Zbigniew Leonowicz, 2023. "Short-Term Load Forecasting Models: A Review of Challenges, Progress, and the Road Ahead," Energies, MDPI, vol. 16(10), pages 1-29, May.
- Thinh Quy Duc Pham & Truong Vinh Hoang & Xuan Tran & Quoc Tuan Pham & Seifallah Fetni & Laurent Duchêne & Hoang Son Tran & Anne-Marie Habraken, 2023. "Fast and accurate prediction of temperature evolutions in additive manufacturing process using deep learning," Journal of Intelligent Manufacturing, Springer, vol. 34(4), pages 1701-1719, April.
- Chin Soon Ku & Jiale Xiong & Yen-Lin Chen & Shing Dhee Cheah & Hoong Cheng Soong & Lip Yee Por, 2023. "Improving Stock Market Predictions: An Equity Forecasting Scanner Using Long Short-Term Memory Method with Dynamic Indicators for Malaysia Stock Market," Mathematics, MDPI, vol. 11(11), pages 1-20, May.
- Qin, Fuli & Tong, Mingyu & Huang, Ying & Zhang, Yubo, 2024. "Modeling, prediction and analysis of natural gas consumption in China using a novel dynamic nonlinear multivariable grey delay model," Energy, Elsevier, vol. 305(C).
- Dongxiang Hou & Xiaodong Wang & Qing Song & Xuesong Mei & Haicheng Wang, 2024. "A quality improvement method for complex component fine manufacturing based on terminal laser beam deflection compensation," Journal of Intelligent Manufacturing, Springer, vol. 35(1), pages 331-341, January.
- Syed Hasan Jafar & Shakeb Akhtar & Hani El-Chaarani & Parvez Alam Khan & Ruaa Binsaddig, 2023. "Forecasting of NIFTY 50 Index Price by Using Backward Elimination with an LSTM Model," JRFM, MDPI, vol. 16(10), pages 1-23, September.
- Jin, Ting & Liang, Feiyan & Dong, Xiaoqi & Cao, Xiaojuan, 2023. "Research on land resource management integrated with support vector machine —Based on the perspective of green innovation," Resources Policy, Elsevier, vol. 86(PB).
- Thiago Conte & Roberto Oliveira, 2024. "Comparative Analysis between Intelligent Machine Committees and Hybrid Deep Learning with Genetic Algorithms in Energy Sector Forecasting: A Case Study on Electricity Price and Wind Speed in the Brazi," Energies, MDPI, vol. 17(4), pages 1-31, February.
- Mokhtar Jlidi & Oscar Barambones & Faiçal Hamidi & Mohamed Aoun, 2024. "ANN for Temperature and Irradiation Prediction and Maximum Power Point Tracking Using MRP-SMC," Energies, MDPI, vol. 17(12), pages 1-21, June.
- Ying Zhang & Mutahar Safdar & Jiarui Xie & Jinghao Li & Manuel Sage & Yaoyao Fiona Zhao, 2023. "A systematic review on data of additive manufacturing for machine learning applications: the data quality, type, preprocessing, and management," Journal of Intelligent Manufacturing, Springer, vol. 34(8), pages 3305-3340, December.
- Pulikandala Nithish Kumar & Nneka Umeorah & Alex Alochukwu, 2024. "Dynamic graph neural networks for enhanced volatility prediction in financial markets," Papers 2410.16858, arXiv.org.
- Agnieszka Wawrzyniak & Andrzej Przybylak & Piotr Boniecki & Agnieszka Sujak & Maciej Zaborowicz, 2023. "Neural Modelling in the Study of the Relationship between Herd Structure, Amount of Manure and Slurry Produced, and Location of Herds in Poland," Agriculture, MDPI, vol. 13(7), pages 1-13, July.
- Deyuan Ma & Ping Jiang & Leshi Shu & Zhaoliang Gong & Yilin Wang & Shaoning Geng, 2024. "Online porosity prediction in laser welding of aluminum alloys based on a multi-fidelity deep learning framework," Journal of Intelligent Manufacturing, Springer, vol. 35(1), pages 55-73, January.
- Mirza, Nawazish & Rizvi, Syed Kumail Abbas & Naqvi, Bushra & Umar, Muhammad, 2024. "Inflation prediction in emerging economies: Machine learning and FX reserves integration for enhanced forecasting," International Review of Financial Analysis, Elsevier, vol. 94(C).
- Saeed Alqadhi & Hoang Thi Hang & Javed Mallick & Abdullah Faiz Saeed Al Asmari, 2024. "Evaluating landslide susceptibility and landscape changes due to road expansion using optimized machine learning," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 120(13), pages 11713-11741, October.
- Clemens Tegetmeier & Arne Johannssen & Nataliya Chukhrova, 2024. "Artificial Intelligence Algorithms for Collaborative Book Recommender Systems," Annals of Data Science, Springer, vol. 11(5), pages 1705-1739, October.
More about this item
Keywords
selective laser sintering; random forest; support vector machine; artificial neural network; oversampling method;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:11:y:2023:i:14:p:3204-:d:1199408. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.