相关实验视频
Updated: May 8, 2025

11:59
High-speed Particle Image Velocimetry Near Surfaces
Published on: June 24, 2013
32.9K
使用混合随机森林方法预测峰值粒子速度
Yu Yan1,2, Jiwei Guo3,4, Shijie Bao5
1School of Civil Engineering, Liaoning Technical University, Fuxin, 123000, China. hityanyu@163.com.
Scientific reports
|December 27, 2024
概括
这项研究调查了爆炸引起的地面振动,重点关注粒子峰值速度 (PPV). 它引入了一个新的经验方程,并评估机器学习模型,优化的随机森林 (AOA-RF) 在预测PPV方面显示了最高的准确性.
科学领域:
- 地质技术工程 地质技术工程
- 采矿工程 采矿工程 采矿工程
- 土木工程 土木工程是指土木工程.
背景情况:
- 爆炸挖掘会产生地面振动,对城市地区构成风险.
- 粒子峰值速度 (PPV) 是评估地面振动的一个关键指标.
- 诸如负载等参数对爆炸引起的振动的影响仍在争论中.
研究的目的:
- 评估负载对地面振动的影响.
- 开发和验证PPV的预测模型.
- 为了确定最准确的PPV预测方法在采矿.
主要方法:
- 在武家田煤矿收集地面振动的数据.
- 相关性分析以确定变量 (例如距离和PPV) 之间的关系.
- 使用维度分析开发新的经验方程.
- 应用和比较六个机器学习算法 (RF,KNN等). ) 的情况.
- 使用算术优化算法 (AOA) 优化ML模型.
主要成果:
- 距离 (R) 与PPV的相关性最强 (系数 -0.67).
- 新的经验方程在PPV预测中表现优于现有的方程.
- 随机森林 (RF) 和K-最近邻居 (KNN) 在最初的ML模型中表现出优异的性能.
- 优化的随机森林 (AOA-RF) 模型在PPV预测中取得了最高的准确性.
结论:
- 这项研究提供了一种更准确的方法来预测爆炸的PPV.
- 机器学习,特别是AOA-RF,为振动评估提供了一个强大的方法.
- 调查结果有助于执行爆炸操作的安全规定.
相关概念视频
Prediction Intervals
2.2K
The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
2.2K
End Point Prediction: Gran Plot
169
A Gran plot is used to predict the equivalence volume or endpoint of a potentiometric or acid-base titration without reaching the endpoint. Typically, titration data is collected as a function of the titrant's volume up to a point less than the equivalence volume and then transformed into a linear format. The straight line is extended to the x-axis, indicating the necessary titrant volume to achieve the equivalence point.
For potentiometric titration, the Gran plot is created by plotting...
For potentiometric titration, the Gran plot is created by plotting...
169
Determination of Expected Frequency
2.1K
Suppose one wants to test independence between the two variables of a contingency table. The values in the table constitute the observed frequencies of the dataset. But how does one determine the expected frequency of the dataset? One of the important assumptions is that the two variables are independent, which means the variables do not influence each other. For independent variables, the statistical probability of any event involving both variables is calculated by multiplying the individual...
2.1K
Random Sampling Method
10.9K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest. Among the various sampling methods used by...
10.9K
Residuals and Least-Squares Property
7.2K
The vertical distance between the actual value of y and the estimated value of y. In other words, it measures the vertical distance between the actual data point and the predicted point on the line
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...
7.2K
Survival Tree
37
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
Constructing a...
Building a Survival Tree
Constructing a...
37

