OPTIMIZATION AND ANALYSIS OF THE INDEX OF AIR
QUALITY IN DAKAR BY THE PROCESS AUTO
REGRESSIVE MOVING AVERAGE ARMA(2,1)
Lebede Ngartera$^1$, Salimata Diagne$^2$, Youssou Gningue$^3$
$^1$Department of Mathematics
Faculty of Exact and Applied Sciences N'Djamena University, Chad
B.P: 1739, Ndjamena, CHAD
$^2$Department of Mathematics
Faculty of Science and Technology
Cheikh Anta Diop University, Dakar, SENEGAL
$^3$Department of Mathematics and Computer Sciences
Laurentian University
Sudbury, ON, CANADA
Abstract. Numerous time-dependent phenomena govern our world. The time series are part of one of the methods often used to understand mathematically. Time series can be used to predict future events. In this article, we use the concept of time series to analyze and model the Index of air quality in Dakar to make his short-term forecast. To top this approach, the auto-regressive moving average(2,1) selected by the optimal Akaike information criterion and Bayesian information criterion was used to perform some simulations.
AMS Subject Classification: 78M50, 65C20, 62P12, 37M10
Key Words and Phrases: AIC and BIC, air quality, optimization, auto-regressive moving average, simulation and estimation


Download full article from here (pdf format).

DOI: 10.12732/ijam.v28i5.13

Volume: 28
Issue: 5
Year: 2015