使用回归和分类模型的组合来预测路径损失的机器学习方法
Ilia Iliev1, Yuliyan Velchev1, Peter Z Petkov1
1Department of Radio Communications and Video Technology, Faculty of Telecommunications, Technical University of Sofia, 1000 Sofia, Bulgaria.
Sensors (Basel, Switzerland)
|September 14, 2024
概括
这项研究引入了一种新的机器学习模型,用于准确预测无线电波路径损失. 复合模型在各种无线通信场景中平衡了准确性和计算效率.
科学领域:
- 无线通信工程 无线通信工程
- 无线电传播建模 无线电传播建模
- 机器学习应用 机器学习应用
背景情况:
- 准确的无线电路损失预测对于有效的无线电链路规划至关重要.
- 现有的预测方法往往缺乏准确性,通用性和计算效率之间的平衡.
- 433 MHz频段对于各种无线系统如物联网和LPWAN至关重要.
研究的目的:
- 开发一个通用和计算效率高的机器学习模型,用于无线电路损失预测.
- 提高在各种地形和传播条件 (视线和非视线) 上的路径损失预测的准确性.
- 创建适用于不同天线高度和环境类型的灵活模型.
主要方法:
- 开发了一个新的复合机器学习模型,结合了两个回归模型和一个分类器.
- 该模型仅使用五个输入参数:距离,天线高度和地形/障碍物统计.
- 一个分类模型概率地结合了训练用于视线和非视线条件的回归模型的输出.
主要成果:
- 拟议的机器学习方法实现了7.3dB的低根平均平方误差.
- 记录了0.702的高确定系数 (R平方),表明了强大的预测性能.
- 该模型在不同地形 (平坦,丘陵,山地) 和区域 (农村,城市,郊区) 上表现出色.
结论:
- 开发的复合机器学习模型为路径丢失预测提供了精度,通用性和低计算复杂性的卓越平衡.
- 该模型的灵活性允许在各种无线电链路规划场景中应用,包括物联网和LPWAN系统.
- 虽然该模型在433MHz的频率上得到了验证,但它可以适应在十米波长范围内的其他频率.
相关概念视频
01:23Mechanistic Models: Compartment Models in Individual and Population Analysis
33
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
33
01:30Classification of Signals
420
In signal processing, signals are classified based on various characteristics: continuous-time versus discrete-time, periodic versus aperiodic, analog versus digital, and causal versus noncausal. Each category highlights distinct properties crucial for understanding and manipulating signals.
A continuous-time signal holds a value at every instant in time, representing information seamlessly. In contrast, a discrete-time signal holds values only at specific moments, often denoted as x(n), where...
A continuous-time signal holds a value at every instant in time, representing information seamlessly. In contrast, a discrete-time signal holds values only at specific moments, often denoted as x(n), where...
420
01:29Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
45
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...
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
45
01:11Regression Analysis
5.7K
Regression analysis is a statistical tool that describes a mathematical relationship between a dependent variable and one or more independent variables.
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
5.7K
01:25Multiple Regression
3.0K
Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
3.0K
01:11Residuals and Least-Squares Property
7.3K
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...
7.3K