TITLE:
Outlier Detection of Air Quality for Two Indian Urban Cities Using Functional Data Analysis
AUTHORS:
Mohammad Ahmad, Weihu Cheng, Zhao Xu, Abdul Kalam
KEYWORDS:
Functional Data Analysis, Outliers, Air Quality, Gas Emission, Classical Statistics
JOURNAL NAME:
Open Journal of Air Pollution,
Vol.12 No.3,
August
29,
2023
ABSTRACT: Human living would be impossible without air quality.
Consistent advancements in practically every aspect of contemporary human life
have harmed air quality. Everyday industrial, transportation, and home
activities turn up dangerous contaminants in our surroundings. This study
investigated two years’ worth of air quality and outlier detection data from
two Indian cities. Studies on air pollution have used numerous types of
methodologies, with various gases being seen as a vector whose components
include gas concentration values for each observation per-formed. We use curves
to represent the monthly average of daily gas emissions in our technique. The
approach, which is based on functional depth, was used to find outliers in the
city of Delhi and Kolkata’s gas emissions, and the outcomes were compared to
those from the traditional method. In the evaluation and comparison of these
models’ performances, the functional approach model studied well.