使用循环经济的多表达式编程预测城市垃圾的产生:一个数据驱动的方法
Ayodeji Sulaiman Olawore1,2, Kuan Yew Wong3, Kamoru Olufemi Oladosu2
1Faculty of Mechanical Engineering, Universiti Teknologi Malaysia, 81310, Skudai, Malaysia.
Environmental science and pollution research international
|October 26, 2024
概括
预测城市废物产生对于可持续发展至关重要. 多表达式编程 (MEP) 为MWG提供了卓越的预测模型,优于其他方法并帮助废物管理策略.
科学领域:
- 环境科学 环境科学
- 计算机科学 计算机科学
- 可持续发展 可持续发展 可持续发展
背景情况:
- 城市垃圾产量 (MWG) 的增加对可持续发展构成了重大障碍.
- 有效的废物管理策略需要准确的预测模型,特别是在循环经济框架内.
研究的目的:
- 开发和验证使用多表达式编程 (MEP) 的城市废物产生 (MWG) 的新型预测模型.
- 将MEP模型的性能与人工神经网络 (ANN),随机森林 (RF) 和多重线性回归 (MLR) 模型进行比较.
- 通过敏感性分析,确定影响MWG的关键社会经济和环境因素.
主要方法:
- 使用基于历史社会经济和环境数据的多表达式编程 (MEP) 开发预测模型.
- 通过对ANN,RF和MLR模型的比较分析验证MEP模型,使用各种评估指标.
- 进行参数和灵敏度分析,以评估MEP模型的性能和输入变量的影响.
主要成果:
- 与ANN (R2 = 0.974),MLR (R2 = 0.964) 和RF (R2 = 0.957) 相比,MEP模型实现了更高的确定系数 (R2 = 0.977) 来预测MWG.
- 灵敏度分析确定了MEP模型中输入变量的相对重要性.
- 该研究制定了一个新的数学模型,将社会经济和环境因素与MWG联系起来.
结论:
- 该MEP模型在预测城市废物产生 (MWG) 方面表现出卓越的准确性和性能.
- 开发的模型为废物管理当局提供了一个有价值的工具,以优化循环经济的基础设施和政策.
- 这项研究有助于创建一个新的MEP应用程序,并为明智的废物管理和可持续发展提供了一个数学模型.
相关概念视频
01:30Environmental Applications of Microorganisms
2
Microorganisms play a pivotal role in maintaining ecosystem balance by recycling essential elements such as carbon, nitrogen, and phosphorus, as well as supporting processes like bioremediation, wastewater treatment, and biofuel production.Microbes in Elemental CyclesIn the carbon cycle, microorganisms decompose organic matter, releasing carbon dioxide via aerobic respiration. This carbon dioxide is subsequently used by photosynthetic organisms to synthesize organic compounds, closing the...
2
01:23Mechanistic Models: Compartment Models in Individual and Population Analysis
29
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
29
01:29Levels of Use of a GIS
45
Geographic Information Systems (GIS) operate across three levels of application, each representing an increasing degree of complexity: data management, analysis, and prediction. These levels reflect the expanding functionality and versatility of GIS technology in handling spatial data for diverse purposes.Data ManagementAt its foundational level, GIS serves as a tool for data management, enabling the input, storage, retrieval, and organization of spatial data. This level is often employed in...
45