使用机器学习进行计算评估,分析由太阳能供电的膜淡化工艺
Muteb Alanazi1, Tareq Nafea Alharby2
1Department of Clinical Pharmacy, College of Pharmacy, University of Ha'il, Ha'il, 81442, Saudi Arabia.
Scientific reports
|October 17, 2025
概括
这项研究优化了用于净化水的膜淡化模型. 一个堆叠组合方法,与水母优化器调整,准确地预测了透体积,优于单个模型.
科学领域:
- 化学工程是化学工程的重要组成部分.
- 环境科学 环境科学
- 计算建模 计算建模
背景情况:
- 膜接触器对于水净化和海水淡化至关重要.
- 准确估计透体积对于优化膜性能至关重要.
研究的目的:
- 开发和比较膜淡化中透体积的预测模型.
- 为了评估组合方法和先进的超参数调的有效性.
主要方法:
- 在膜接触器中的质量转移的数值模拟.
- 开发和比较多层感知器 (MLP),极端梯度增强 (XGBoost) 和堆叠组合模型.
- 果优化器 (JO) 的应用,用于超参数调整和数据预处理技术.
主要成果:
- 堆叠组合模型展示了卓越的预测准确性.
- 取得了高的R2值 (0.99060培训,0.97627交叉验证,0.99043测试) 和低的测试误差 (RMSE = 6.17921).
- 水母优化器增强了模型的稳定性和超参数调整.
结论:
- 堆叠组合方法显著提高了透体积的预测准确性.
- JO调节的堆叠模型为膜海水淡化性能预测提供了强大而高效的解决方案.
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