Enhancement of multilayer perceptron model training accuracy through the optimization of hyperparameters: a case study of the quality prediction of injection-molded parts-Reference-Cited by-同舟云学术

Enhancement of multilayer perceptron model training accuracy through the optimization of hyperparameters: a case study of the quality prediction of injection-molded parts

Published:2021-09-26 Issue:7-8 Volume:118 Page:2247-2263
ISSN:0268-3768
Container-title:The International Journal of Advanced Manufacturing Technology
language:en
Short-container-title:Int J Adv Manuf Technol

Author:

Ke Kun-Cheng,Huang Ming-Shyan^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Industrial and Manufacturing Engineering,Computer Science Applications,Mechanical Engineering,Software,Control and Systems Engineering

Link

https://link.springer.com/content/pdf/10.1007/s00170-021-08109-9.pdf

Reference29 articles.

1. Huang MS, Ke KC, Liu CY (2021) Cavity pressure-based holding pressure adjustment for enhancing the consistency of injection molding quality. J Appl Polym Sci 138(50357):1–10

2. Zhang J, Zhao P, Zhao Y, Huang J, Xia N, Fu J (2019) On-line measurement of cavity pressure during injection molding via ultrasonic investigation of tie bar. Sens Actuators Phys 285:118–126

3. Lin CC, Wang WT, Kuo CC, Wu CL (2014) Experimental and theoretical study of melt viscosity in injection process. Int J Mech Mecha Eng 8:1–5

4. Wang J, Peng J, Yang W (2011) Filling-to-packing switchover mode based on cavity temperature for injection molding. Polym-Plast Technol Eng 50:1273–1280

5. Zhao P, Xia N, Zhang J, Xie J, Zhang C, Fu J (2020) Measurement of molecular orientation using longitudinal ultrasound and its first application in in-situ characterization. Polymer 187(122092):1–11

Cited by 6 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Multi-Objective Optimisation of Injection Moulding Process for Dashboard Using Genetic Algorithm and Type-2 Fuzzy Neural Network;Processes;2024-06-05

2. Quality evaluation modeling of a DED-processed metallic deposition based on ResNet-50 with few training data;Journal of Intelligent Manufacturing;2024-04-23

3. Blade sequencing optimization of aero-engine based on deep reinforcement learning;Aerospace Science and Technology;2023-11

4. A multitask encoder–decoder model for quality prediction in injection moulding;Journal of Manufacturing Processes;2023-10

5. Yield and Properties Prediction Based on the Multicondition LSTM Model for the Solvent Deasphalting Process;ACS Omega;2023-02-03