Correlation between soil compression index (Cc) and state parameters is frequently referenced in studies investigating the fundamental mechanisms underlying changes in soil compressibility. However, developing an efficient formula for Cc that adequately captures the complexity of soil compressive behavior has been challenging for conventional approaches. This study utilized contemporary symbolic regression (SR) to propose a generalized formula for Cc that can represent the nonlinear relationships with state parameters across various soil types. A geological database from southern Vietnam was utilized to establish this data-driven formula. Data exploration revealed the apparent combined effects of moisture content (w), initial void ratio (e0), and moist density (ρ) on soil compressive behavior. Statistical indicators and graphical analysis were adopted to comprehensively assess the performance of the proposed formula against empirical equations found in the literature, aiming to gain a deeper understanding of the mechanism influencing changes in soil compressibility. The evaluation results demonstrated the efficiency of the proposed formula in predicting Cc, as evidenced by low error metrics and a good balance between precision and accuracy. Moreover, the applicability and limitations of the proposed formula were examined using different regional soils with specified geologic origins. Given its reliability and adequacy, the proposed formula explicitly quantified the nonlinear combined effects of e0, ρ and w on the compressibility of undisturbed soils. However, further research accounting for clay minerals, specimen preparation, and geologic origins is needed to enhance the universal applicability of our understanding of soil compressive behavior.

中文翻译：

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基于多进化算法预测土壤压缩指数的广义公式


土壤压缩指数 （Cc） 和状态参数之间的相关性在调查土壤压缩性变化的基本机制的研究中经常被引用。然而，开发一种有效的 Cc 公式来充分捕捉土壤压缩行为的复杂性对于传统方法来说一直是一个挑战。本研究利用当代符号回归 （SR） 提出了一个 Cc 的广义公式，该公式可以表示各种土壤类型中状态参数的非线性关系。利用来自越南南部的地质数据库来建立这个数据驱动的公式。数据探索揭示了含水率 （w）、初始空隙率 （e0） 和湿密度 （ρ） 对土壤压缩行为的明显综合影响。采用统计指标和图形分析方法，根据文献中的实证方程对所提出的公式的性能进行了综合评估，旨在更深入地了解影响土壤压缩率变化的机制。评估结果表明，所提出的公式在预测 Cc 方面的有效性，低误差指标和精度与准确度之间的良好平衡证明了这一点。此外，使用具有特定地质成因的不同区域土壤检查了所提出的公式的适用性和局限性。鉴于其可靠性和充分性，所提出的公式明确量化了 e0、ρ 和 w 对未受干扰土壤压缩性的非线性组合效应。然而，需要对粘土矿物、标本制备和地质起源进行进一步研究，以增强我们对土壤压缩行为理解的普遍适用性。