Explainable artificial intelligence and multi-stage transfer learning for injection molding quality prediction
Author:
Funder
Wisconsin Alumni Research Foundation
Ajou University
Mead Witter Foundation
University of Wisconsin-Madison
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s10845-024-02436-w.pdf
Reference45 articles.
1. Aljundi, R., Babiloni, F., Elhoseiny, M., Rohrbach, M., & Tuytelaars, T. (2018). Memory aware synapses: Learning what (not) to forget. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11207 LNCS, 144–161. https://doi.org/10.1007/978-3-030-01219-9_9.
2. Annicchiarico, D., & Alcock, J. R. (2014). Review of factors that affect shrinkage of molded part in injection molding. Materials and Manufacturing Processes, 29(6), 662–682. https://doi.org/10.1080/10426914.2014.880467.
3. Barredo Arrieta, A., Díaz-Rodríguez, N., Del Ser, J., Bennetot, A., Tabik, S., Barbado, A., Garcia, S., Gil-Lopez, S., Molina, D., Benjamins, R., Chatila, R., & Herrera, F. (2020). Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI. Information Fusion, 58, 82–115. https://doi.org/10.1016/J.INFFUS.2019.12.012.
4. Bensingh, R. J., Machavaram, R., Boopathy, S. R., & Jebaraj, C. (2019). Injection molding process optimization of a bi-aspheric lens using hybrid artificial neural networks (ANNs) and particle swarm optimization (PSO). Measurement, 134, 359–374. https://doi.org/10.1016/J.MEASUREMENT.2018.10.066.
5. Bottou, L. (2012). Stochastic Gradient Descent Tricks. In G. B. and M. K.-R. Montavon Grégoire and Orr (Ed.), Neural Networks: Tricks of the Trade: Second Edition (pp. 421–436). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-35289-8_25.
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