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相关概念视频

Design Example: Maintaining Level of an Embankment01:19

Design Example: Maintaining Level of an Embankment

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Constructing a roadway embankment over uneven terrain requires precise leveling to ensure stability and proper drainage. Surveyors use a leveling instrument and staff to calculate ground elevations and determine the required fill material at each point along the embankment alignment.The process begins by positioning a leveling instrument near a benchmark with a known elevation. A backsight reading establishes the instrument height, which serves as a reference for subsequent measurements. A...
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Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

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Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
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Survival Tree01:19

Survival Tree

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Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
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Shrinkage in Concrete01:27

Shrinkage in Concrete

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Shrinkage in concrete is primarily due to water loss from evaporation, hydration of cement, or carbonation, leading to a reduction in volume. The volumetric contraction results in volumetric strain in concrete. However, in practice, shrinkage is measured as linear strain, which is one-third of the volumetric strain.
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Building separation joints divide large or complex building structures into smaller, discrete units that can move independently. These joints are categorized into three types: volume-change joints, settlement joints, and seismic separation joints.
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The concrete is placed as close as possible to its final position to avoid segregation. The placed concrete is then fully compacted to expel the entrapped air, and the next layer of concrete is laid while the underlying layer is still in the plastic state. The rate at which concrete is placed and compacted is kept equal.
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相关实验视频

Updated: Jun 12, 2025

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines
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开发有效的优化机器学习方法,用于对浅基础的定居预测.

Mohammad Khajehzadeh1,2, Suraparb Keawsawasvong1, Viroon Kamchoom3

  • 1Research Unit in Sciences and Innovative Technologies for Civil Engineering Infrastructures, Department of Civil Engineering, Faculty of Engineering, Thammasat School of Engineering, Thammasat University, Pathumthani, 12120, Thailand.

Heliyon
|September 19, 2024
PubMed
概括

这项研究引入了一种混合机器学习方法,AEFSCO,以准确预测沙地土壤中浅层基础沉积的情况. 优化的LSTM模型显著提高了预测准确性,超过了其他模型.

关键词:
基金会结算 基金会结算这是一种混合的元启发式传闻.长期短期记忆 长期短期记忆参数优化 参数优化

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科学领域:

  • 地质技术工程 地质技术工程
  • 机器学习 机器学习
  • 计算科学 计算科学

背景情况:

  • 在无凝聚性土壤上准确预测浅基础定居点至关重要,但由于复杂的影响因素,这是具有挑战性的.
  • 现有的方法经常与地质技术参数固有的不确定性作斗争.
  • 开发先进的预测模型对于可靠的基础设计至关重要.

研究的目的:

  • 开发和验证一种新的混合机器学习方法,用于估计浅基础结算 (Sm).
  • 为了优化机器学习模型,使用新的混合优化算法来提高预测准确度.
  • 评估优化模型在根据土壤和几何性质预测基础沉积的性能.

主要方法:

  • 开发和验证人工电场和单一候选优化器 (AEFSCO) 的混合优化算法.
  • 使用AEFSCO的长短期记忆 (LSTM),支持向量回归 (SVR) 和多层感知神经网络 (MLPNN) 模型的优化.
  • 在189个病例历史数据库上的培训和测试模型中,有五个输入参数 (基础几何,土壤特性) 和一个输出 (结算).

主要成果:

  • 经过AEFSCO优化,所有测试的机器学习模型的确定系数 (R2) 显著提高.
  • 在AEFSCO优化后,MLPNN,SVR和LSTM模型显示R2的增加分别为9.3%,8%和22%.
  • LSTM-AEFSCO模型表现出优异的性能,R2为0.9903,表现优于SVR-AEFSCO (0.9494) 和MLPNN-AEFSCO (0.9290).

结论:

  • 使用AEFSCO的混合优化大大提高了机器学习模型的准确性,用于预测浅基础结算.
  • 优化的LSTM模型 (LSTM-AEFSCO) 在评估的方法中提供了最准确的预测.
  • 这种先进的混合方法为基础结算的可靠地质工程评估提供了一个有希望的工具.