模拟和优化奶酪乳糖添加剂的增值堆肥生产:超参数调整方法和遗传算法
Cem Şahin1, Fulya Aydın Temel2, Ozge Cagcag Yolcu3
1Department of Environmental Engineering, Faculty of Engineering, Ondokuz Mayıs University, Samsun, 55200, Turkiye.
Journal of environmental management
|October 3, 2024
概括
将3%的奶酪糖添加到污水污泥和家禽废物堆肥中,可以显著提高堆肥质量和工艺效率. 机器学习模型,特别是高斯过程回归,准确地模拟和优化了这一过程,以实现有效的废物管理.
科学领域:
- 环境科学 环境科学
- 废物管理 废物管理
- 农业科学 农业科学
背景情况:
- 奶酪乳清由于有机和矿物质含量高,因此对废水处理具有重大挑战.
- 目前的乳清管理策略是昂贵的,其在堆肥中的应用仍然有限.
- 乳酪乳糖的有效利用对于可持续的废物管理至关重要.
研究的目的:
- 调查奶酪乳糖添加对污水污泥和家禽废物的堆肥的影响.
- 为了评估堆肥质量和工艺效率,使用不同的奶酪乳清比率.
- 开发和验证用于模拟和优化堆肥过程的机器学习模型.
主要方法:
- 用污水污泥和家禽废物进行了堆肥实验,在不同百分比中加入奶酪乳清.
- 分析了堆肥的物理化学参数,以评估质量和工艺效率.
- 机器学习算法,包括高斯过程回归 (GPR),支持向量回归 (SVR) 和神经网络回归 (NNR),用于模拟.
- 超参数调整和遗传算法用于模型优化.
主要成果:
- 添加3%的奶酪乳糖明显提高了两种原料的堆肥效率和最终堆肥质量.
- 高斯过程回归 (GPR) 证明是实现现实和可靠的过程模拟的最有效算法.
- 使用遗传算法进行的优化研究表明,最佳奶酪乳糖比率为污水污泥的3.27%,禽类废物的3.15%.
- 实验和模拟结果显示出强大的兼容性,验证了预测模型.
结论:
- 奶酪乳清可以有效地用作堆肥补充剂,以提高废物处理和生产更高质量的堆肥.
- 机器学习,特别是GPR,为建模,模拟和优化生物废物处理过程提供了强大的工具.
- 这项研究提出了一种新的奶酪乳糖回收战略,并提供了对其对堆肥动态和预测建模的影响的见解.
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