Particle Swarm Optimization–Long Short-Term Memory-Based Dynamic Prediction Model of Single-Crystal Furnace Temperature and Heating Power Article Swipe
Hou‐Wen Lin
,
Dedong Gao
,
Shan Wang
,
Wenyong Zhang
,
Haixin Lin
,
An Yan
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/cryst15020110
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/cryst15020110
Precise temperature and heating power control are crucial for crystal quality and production efficiency in the Czochralski single-crystal growth process. Existing sensor technologies can only monitor these parameters in real time, lacking the ability to predict future trends, which limits the ability to implement preventive control before issues arise. To address this, a temperature and heating power prediction model based on Long Short-Term Memory (LSTM) is proposed and developed using extensive production data. Spearman’s rank correlation coefficient is applied to identify the key parameters related to temperature and heating power. Hyperparameter optimization uses Particle Swarm Optimization (PSO) to improve prediction accuracy. The performance of the PSO-LSTM model is compared with two other widely used prediction models, demonstrating its superior predictive capability. The results show that the PSO-LSTM model achieves highly accurate temperature and heating power predictions in the crystal growth process, with a Mean Absolute Error (MAE) of 0.0295 for temperature and 0.0392 for heating power, further validating its effectiveness for real-time predictive control.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/cryst15020110
- https://www.mdpi.com/2073-4352/15/2/110/pdf?version=1737535002
- OA Status
- gold
- Cited By
- 2
- References
- 34
- Related Works
- 10
- OpenAlex ID
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Raw OpenAlex JSON
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https://doi.org/10.3390/cryst15020110Digital Object Identifier
- Title
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Particle Swarm Optimization–Long Short-Term Memory-Based Dynamic Prediction Model of Single-Crystal Furnace Temperature and Heating PowerWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-01-22Full publication date if available
- Authors
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Hou‐Wen Lin, Dedong Gao, Shan Wang, Wenyong Zhang, Haixin Lin, An YanList of authors in order
- Landing page
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https://doi.org/10.3390/cryst15020110Publisher landing page
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https://www.mdpi.com/2073-4352/15/2/110/pdf?version=1737535002Direct link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://www.mdpi.com/2073-4352/15/2/110/pdf?version=1737535002Direct OA link when available
- Concepts
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Term (time), Particle swarm optimization, Particle (ecology), Power (physics), Materials science, Nuclear engineering, Computer science, Engineering, Thermodynamics, Algorithm, Physics, Geology, Quantum mechanics, OceanographyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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2Total citation count in OpenAlex
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2025: 2Per-year citation counts (last 5 years)
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34Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| referenced_works | https://openalex.org/W4220738785, https://openalex.org/W2130715736, https://openalex.org/W2073072421, https://openalex.org/W1988884874, https://openalex.org/W4388486062, https://openalex.org/W4403068356, https://openalex.org/W4281617932, https://openalex.org/W2028488358, https://openalex.org/W4210565675, https://openalex.org/W3175066877, https://openalex.org/W3198769006, https://openalex.org/W3165960344, https://openalex.org/W4312202337, https://openalex.org/W4307855910, https://openalex.org/W3207681706, https://openalex.org/W3104174523, https://openalex.org/W2998268303, https://openalex.org/W3021048621, https://openalex.org/W3133735015, https://openalex.org/W2920463045, https://openalex.org/W6791569714, https://openalex.org/W4285006073, https://openalex.org/W2984376566, https://openalex.org/W3008235510, https://openalex.org/W3044087904, https://openalex.org/W2125213524, https://openalex.org/W2573137292, https://openalex.org/W6682642761, https://openalex.org/W4401545617, https://openalex.org/W3117614508, https://openalex.org/W4403475700, https://openalex.org/W3172280330, https://openalex.org/W4390465781, https://openalex.org/W3134574975 |
| referenced_works_count | 34 |
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