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The log-distance path loss model is a radio propagation model that predicts the path loss a signal encounters inside a building or densely populated areas over long distance. While the log-distance model is suitable for longer distances, the short-distance path loss model is often used for indoor environments or very short outdoor distances.
In telecommunications, the free-space path loss (FSPL) (also known as free-space loss, FSL) is the attenuation of radio energy between the feedpoints of two antennas that results from the combination of the receiving antenna's capture area plus the obstacle-free, line-of-sight (LoS) path through free space (usually air). [1]
Path loss is a major component in the analysis and design of the link budget of a telecommunication system. This term is commonly used in wireless communications and signal propagation. Path loss may be due to many effects, such as free-space loss, refraction, diffraction, reflection, aperture-medium coupling loss, and absorption. Path loss is ...
The 2-ray ground reflection model is a simplified propagation model used to estimate the path loss between a transmitter and a receiver in wireless communication systems, in order to estimate the actual communication paths used. It assumes that the signal propagates through two paths:
L = The median path loss. Unit: decibel (dB). L 0 = The reference path loss along 1 km. Unit: decibel (dB). = The slope of the path loss curve. Unit: decibels per decade. d = The distance on which the path loss is to be calculated. Unit: kilometer (km). F A = Adjustment factor
The partial least squares path modeling or partial least squares structural equation modeling (PLS-PM, PLS-SEM) [1] [2] [3] is a method for structural equation modeling that allows estimation of complex cause-effect relationships in path models with latent variables.
Weissberger’s modified exponential decay model, or simply, Weissberger’s model, is a radio wave propagation model that estimates the path loss due to the presence of one or more trees in a point-to-point telecommunication link. This model belongs to the category Foliage or Vegetation models.
In machine learning, a key challenge is enabling models to accurately predict outcomes on unseen data, not just on familiar training data. Regularization is crucial for addressing overfitting —where a model memorizes training data details but can't generalize to new data.