Model-based imputation of sound level data at thoroughfare using computational intelligence
The aim of the paper was to present the methodology of imputation of the missing sound level data, for a period of several months, in many noise monitoring stations located at thoroughfares by applying one model which describes variability of sound level within the tested period. To build the model,...
Main Author: | Kekez Michał |
---|---|
Format: | Article |
Language: | English |
Published: |
De Gruyter
2021-03-01
|
Series: | Open Engineering |
Subjects: | |
Online Access: | https://doi.org/10.1515/eng-2021-0051 |
Similar Items
-
Application of selected computational intelligence methods to sound level modelling based on traffic intensity in thoroughfare
by: Kekez Michał
Published: (2019-01-01) -
Missing values reconstruction in sound level monitoring station by means of intelligent computing
by: Radziszewski Leszek, et al.
Published: (2018-01-01) -
Accuracy of random-forest-based imputation of missing data in the presence of non-normality, non-linearity, and interaction
by: Shangzhi Hong, et al.
Published: (2020-07-01) -
Sequential Imputation of Missing Spatio-Temporal Precipitation Data Using Random Forests
by: Utkarsh Mital, et al.
Published: (2020-08-01) -
The importance of disease incidence rate on performance of GBLUP, threshold BayesA and machine learning methods in original and imputed data set
by: Yousef Naderi, et al.
Published: (2020-12-01)