An Improved Stochastic Configuration Networks With Compact Structure and Parameter Adaptation
Stochastic Configuration Networks (SCNs) perform well in machine learning and data mining tasks in complex data environments. However, traditional SCNs have limitations in network size and computation time. To address these issues, this paper proposes an improved version of SCNs. There are two key i...
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| Main Authors: | Sanyi Li, Hongyu Guan, Peng Liu, Weichao Yue, Qian Wang |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10852165/ |
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