结合支向量的回归与火虫算法用于预测废水处理厂的能源消耗
Mohammed Achite1, Saeed Samadianfard2, Nehal Elshaboury3
1Faculty of Nature and Life Sciences, Water and Environment Laboratory, Hassiba Benbouali University of Chlef, Chlef 02180, Algeria.
概括
本研究引入了一种支持向量回归与火虫算法 (SVR-FFA) 模型,以准确预测废水处理厂的能源消耗. 先进的SVR-FFA-15模型增强了能源管理,并确定了节约机会.
科学领域:
- 环境工程 环境工程
- 水资源管理 水资源管理
- 计算智能是一种计算智能.
背景情况:
- 污水处理厂 (WWTP) 是重要的能源消费者,影响运营成本.
- 精确预测能源消耗对于高效的WWTP管理和降低成本至关重要.
- 现有的方法可能无法完全捕捉影响WWTP能源使用的因素的复杂相互作用.
研究的目的:
- 开发和验证一种新的混合模型来预测WWTP的能源消耗.
- 评估将支持向量回归 (SVR) 与火算法 (FFA) 集成的有效性.
- 确定关键的输入参数,以优化WWTP中的能源消耗预测.
主要方法:
- 一个包含1653个样本的综合数据集是从阿尔及利亚Chlef市的一个WWTP收集的.
- 这项研究使用了由火算法 (FFA) 优化的支持向量回归 (SVR).
- 通过各种化学,物理,液压,能源和气象参数的组合,评估了15种不同的模型.
主要成果:
- 该SVR-FFA-15模型在预测WWTP能源消耗方面表现出更高的准确性.
- 集成SVR和FFA为分析复杂数据集提供了一个强大的框架.
- 该研究确定了增强预测性能的特定输入参数组合.
结论:
- SVR-FFA方法为优化废水处理中的能源管理提供了一个有价值的工具.
- 准确的能源消耗预测可以带来显著的成本节约和提高运营效率.
- 这项研究为开发更智能,更节能的WWTP提供了基础.
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