Comparison of Different Regularized and Shrinkage Regression Methods to Predict Daily Tropospheric Ozone Concentration in the Grand Casablanca Area

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ISSN Print: 2160-0368
ISSN Online: 2160-0384
www.scirp.org/journal/apm
E-mail: apm@scirp.org

"Comparison of Different Regularized and Shrinkage Regression Methods to Predict Daily Tropospheric Ozone Concentration in the Grand Casablanca Area"
written by Halima Oufdou, Lise Bellanger, Amal Bergam, Angélina El Ghaziri, Kenza Khomsi, El Mostafa Qannari,
published by Advances in Pure Mathematics, Vol.8 No.10, 2018

has been cited by the following article(s):

[1]	Comparative Study of Regression and Regularization Methods: Application to Weather and Climate Data
	2022

[2]	Forecasting Daily of Surface Ozone Concentration in the Grand Casablanca Region Using Parametric and Nonparametric Statistical Models
	2021

[1]	A hybrid model for predicting air quality combining Holt–Winters and Deep Learning Approaches: A novel method to identify ozone concentration peaks Mathematical Modeling and Computing, 2023 DOI:10.23939/mmc2023.04.1154

[2]	WITS 2020 Lecture Notes in Electrical Engineering, 2022 DOI:10.1007/978-981-33-6893-4_22

[3]	Forecasting Daily of Surface Ozone Concentration in the Grand Casablanca Region Using Parametric and Nonparametric Statistical Models Atmosphere, 2021 DOI:10.3390/atmos12060666

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