| 基于随机森林与分位数阈值分析的生物污损与环境因子相关性研究 |
| Correlation Between Marine Biofouling and Environmental Factors Based on Random Forest and Quantile Threshold Analysis |
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| DOI：10.3969/j.issn.1003-2029.2026.03.008 |
| 中文关键词: 生物污损 环境因子 随机森林 样条插值 阈值分析 |
| 英文关键词:biofouling environmental factors random forest spline interpolation threshold analysis |
| 基金项目:国家自然科学基金资助项目（51809233） |
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| 中文摘要: |
| 生物污损是海洋工程结构在服役过程中普遍存在的附着现象，对工程材料和船舶运行造成显著影响。为定量揭示生物污损与环境因子的耦合关系，本文基于舟山中远码头的浅海浸泡实验数据，构建了融合改进样条插值、随机森林建模与分位数阈值分析的预测框架。结果表明：所提出的物理约束型三次样条插值方法可实现污损数据的平滑重构，随机森林模型能有效刻画环境因子与污损强度的非线性关系，测试集R2达到0.905。阈值分析识别出水温（23.26 ℃）、盐度（32.44 PSU）、流速（0.10 m/s）、日照时长（14 384 s）和短波辐射总值（12.64 MJ/m2）等关键转折点，污损值在阈值以上显著增加，表明污损过程受多环境因子耦合控制。本文提出的框架可为生物污损预测和防治提供科学依据。 |
| 英文摘要: |
| Biofouling is a common attachment phenomenon on marine engineering structures during service and can significantly affect engineering materials and ship operations. To quantitatively reveal the coupling relationship between biofouling and environmental factors, this paper constructed a prediction framework integrating improved spline interpolation, random forest modeling, and quantile threshold analysis based on shallow-sea immersion experimental data from a COSCO wharf berth in Zhoushan. The results show that the proposed physically constrained cubic spline interpolation method can achieve smooth reconstruction of biofouling data. The random forest model effectively characterizes the nonlinear relationship between environmental factors and biofouling intensity, with a test-set R² of 0.905. Threshold analysis identified key turning points for water temperature (23.26 ℃), salinity (32.44 PSU), flow velocity (0.10 m·s⁻¹), sunshine duration (14 384 s), and total shortwave radiation (12.64 MJ·m⁻²). The fouling rating increased significantly above these thresholds, indicating that the biofouling process is jointly controlled by multiple environmental factors. The proposed framework can provide a scientific basis for biofouling prediction and prevention. |
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