Predicting the unconfined compressive strength of stabilized soil using random forest coupled with meta-heuristic algorithms

3区 计算机科学 Q1 Computer Science Journal of Ambient Intelligence and Humanized Computing Pub Date : 2024-09-16 DOI:10.1007/s12652-024-04857-0
Yan Li
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Abstract

Unconfined Compressive Strength (UCS) is a crucial mechanical parameter of rocks, which is pivotal in developing accurate geomechanical models. Traditionally, UCS estimation involves expensive and time-consuming methods, such as lab testing of retrieved core samples or well-log data analysis. This research presents a novel approach for real-time estimation of UCS, crucial in various geomechanical applications. It employs Random Forest (RF) prediction models enhanced by Runge Kutta Optimization (RKO) and Beluga Whale Optimization (BWO) algorithms for improved accuracy and efficiency. Validation using UCS samples from diverse soil types yields three distinct models: RFRK (RF + RKO), RFBW (RF + BWO), and an individual RF model, each contributing valuable insights. The RFBW model particularly stands out with high R2 values (0.994) and a favorable RMSE (73.93), indicating superior predictive and generalization capabilities. This method represents a significant advancement in UCS prediction, offering efficiency and time-saving benefits across geomechanical fields.

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利用随机森林和元启发式算法预测稳定土的无压抗压强度
非收缩抗压强度(UCS)是岩石的一个重要力学参数,对于开发精确的地质力学模型至关重要。传统上,UCS 的估算需要采用昂贵而耗时的方法,如在实验室测试取回的岩心样本或分析井记录数据。本研究提出了一种实时估算 UCS 的新方法,这在各种地质力学应用中至关重要。它采用随机森林(RF)预测模型,并通过 Runge Kutta 优化(RKO)和白鲸优化(BWO)算法进行增强,以提高准确性和效率。使用来自不同土壤类型的 UCS 样本进行验证,得出了三种不同的模型:RFRK 模型(RF + RKO)、RFBW 模型(RF + BWO)和单独的 RF 模型,每个模型都能提供有价值的见解。RFBW 模型尤为突出,具有较高的 R2 值(0.994)和较好的 RMSE 值(73.93),显示出卓越的预测和概括能力。该方法代表了 UCS 预测领域的重大进步,为整个地质力学领域提供了高效、省时的优势。
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来源期刊
Journal of Ambient Intelligence and Humanized Computing
Journal of Ambient Intelligence and Humanized Computing COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCEC-COMPUTER SCIENCE, INFORMATION SYSTEMS
CiteScore
9.60
自引率
0.00%
发文量
854
期刊介绍: The purpose of JAIHC is to provide a high profile, leading edge forum for academics, industrial professionals, educators and policy makers involved in the field to contribute, to disseminate the most innovative researches and developments of all aspects of ambient intelligence and humanized computing, such as intelligent/smart objects, environments/spaces, and systems. The journal discusses various technical, safety, personal, social, physical, political, artistic and economic issues. The research topics covered by the journal are (but not limited to): Pervasive/Ubiquitous Computing and Applications Cognitive wireless sensor network Embedded Systems and Software Mobile Computing and Wireless Communications Next Generation Multimedia Systems Security, Privacy and Trust Service and Semantic Computing Advanced Networking Architectures Dependable, Reliable and Autonomic Computing Embedded Smart Agents Context awareness, social sensing and inference Multi modal interaction design Ergonomics and product prototyping Intelligent and self-organizing transportation networks & services Healthcare Systems Virtual Humans & Virtual Worlds Wearables sensors and actuators
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