一种基于变量自动编码器的轨迹异常值检测方法
Longmei Zhang1, Wei Lu2, Feng Xue2
1School of Communication and Information Engineering, Xi'an University of Science and Technology, Xi'an 710054, China.
Mathematical biosciences and engineering : MBE
|September 7, 2023
概括
本研究引入了用于轨道异常检测的变异自动编码模型,在识别异常交通模式时达到95%以上的准确性. 该模型有效地实时检测不寻常的轨迹,超过现有方法.
科学领域:
- 数据科学数据科学数据科学
- 机器学习 机器学习
- 交通工程是交通工程.
背景情况:
- 轨迹数据分析对于识别异常现象和预测交通风险至关重要.
- 现有的异常值检测方法在计算效率和手动值设置方面经常面临挑战.
研究的目的:
- 提出一种新的轨迹异常点检测模型,使用变量自动编码器.
- 提高在城市交通中检测异常轨迹的准确性和效率.
主要方法:
- 将轨迹数据编码为基于城市交通统计数据的分布参数.
- 训练自动编码器网络以最大限度地提高原始轨迹的生成概率.
- 通过测量原始和生成轨迹之间的差异来检测异常值.
主要成果:
- 实现了超过95%的准确性,超越了基于密度,基于分类和最近的机器学习方法.
- 证明了高计算效率,适合实时检测场景.
- 在培训期间展示了稳定的趋同,在培训时间中具有可扩展性.
结论:
- 拟议的变量自动编码器模型为轨迹异常值检测提供了有效和高效的解决方案.
- 该模型简化了门设置,并且非常适用于现实世界的交通监控.
- 这种方法在异常轨迹识别领域取得了重大进展.
相关概念视频
Outliers and Influential Points
4.1K
An outlier is an observation of data that does not fit the rest of the data. It is sometimes called an extreme value. When you graph an outlier, it will appear not to fit the pattern of the graph. Some outliers are due to mistakes (for example, writing down 50 instead of 500), while others may indicate that something unusual is happening. Outliers are present far from the least squares line in the vertical direction. They have large "errors," where the "error" or residual is the...
4.1K
What Are Outliers?
3.9K
Outliers are observed data points that are far from the least squares line. They have unusual values and need to be examined carefully. Though an outlier may result from erroneous data, at other times, it may hold valuable information about the population under study and should be included in the data. Hence, it is crucial to examine what causes a data point to be an outlier.
The z score is used to find outliers or unusual values. It should be noted that any values beyond -2 and +2 are...
The z score is used to find outliers or unusual values. It should be noted that any values beyond -2 and +2 are...
3.9K
Detection of Gross Error: The Q Test
6.2K
When one or more data points appear far from the rest of the data, there is a need to determine whether they are outliers and whether they should be eliminated from the data set to ensure an accurate representation of the measured value. In many cases, outliers arise from gross errors (or human errors) and do not accurately reflect the underlying phenomenon. In some cases, however, these apparent outliers reflect true phenomenological differences. In these cases, we can use statistical methods...
6.2K
Mean Absolute Deviation
2.7K
The mean absolute deviation is also a measure of the variability of data in a sample. It is the absolute value of the average difference between the data values and the mean.
Let us consider a dataset containing the number of unsold cupcakes in five shops: 10, 15, 8, 7, and 10. Initially, calculate the sample mean. Then calculate the deviation, or the difference, between each data value and the mean. Next, the absolute values of these deviations are added and divided by the sample size to...
Let us consider a dataset containing the number of unsold cupcakes in five shops: 10, 15, 8, 7, and 10. Initially, calculate the sample mean. Then calculate the deviation, or the difference, between each data value and the mean. Next, the absolute values of these deviations are added and divided by the sample size to...
2.7K
Quantifying and Rejecting Outliers: The Grubbs Test
1.6K
Sometimes, a data set can have a recorded numerical observation that greatly deviates from the rest of the data. Assuming that the data is normally distributed, a statistical method called the Grubbs test can be used to determine whether the observation is truly an outlier. To perform a two-tailed Grubbs test, first, calculate the absolute difference between the outlier and the mean. Then, calculate the ratio between this difference and the standard deviation of the sample. This...
1.6K
Variability: Analysis
158
Measures of variability are statistical metrics that reveal the dispersion pattern within a dataset. They are pivotal in biostatistics, providing insights into the heterogeneity within health and biological data. Variability signifies the degree to which data points diverge from one another, helping researchers understand the potential range of values and associated uncertainty within the data.
The range is a simple measure of variability, indicating the difference between the highest and...
The range is a simple measure of variability, indicating the difference between the highest and...
158


