Detection of outliers in water quality monitoring samples using functional data analysis in San Esteban estuary (Northern Spain)

2012 ◽  
Vol 439 ◽  
pp. 54-61 ◽  
Author(s):  
C. Díaz Muñiz ◽  
P.J. García Nieto ◽  
J.R. Alonso Fernández ◽  
J. Martínez Torres ◽  
J. Taboada
Keyword(s):  
Water Quality ◽  
Data Analysis ◽  
Functional Data Analysis ◽  
Functional Data ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
Northern Spain ◽  
Detection Of Outliers

scholarly journals Detection of Outliers in Pollutant Emissions from the Soto de Ribera Coal-Fired Plant Using Functional Data Analysis: A Case Study in Northern Spain

Proceedings ◽  
2018 ◽  
Vol 2 (23) ◽  
pp. 1473 ◽  
Author(s):  
Fernando Sánchez Lasheras ◽  
Celestino Ordóñez Galán ◽  
Paulino José García Nieto ◽  
Esperanza García-Gonzalo
Keyword(s):  
Data Analysis ◽  
Functional Data Analysis ◽  
Functional Data ◽  
Functional Method ◽  
Pollutant Emissions ◽  
Northern Spain ◽  
Density Region ◽  
Discrete Information ◽  
High Density Region ◽  
Detection Of Outliers

The present research uses two different functional data analysis methods called functional high-density region (HDR) boxplot and functional bagplot. Both methodologies were applied for the outlier detection in the time pollutant emissions curves that were built using as inputs the discrete information available from an air quality monitoring data record station. Although the record of pollutant emissions is made in a discrete way, these methodologies consider pollutant emissions over time as curves, with outliers obtained by a comparison of curves instead of vectors. Then the concept of outlier passes from been a point to a curve that employed the functional depth as the indicator of curve distances. In this study, the referred methodologies are applied to the detection of outliers in pollutant emissions from the Soto de Ribera coal-fired plant which is in the nearby of the city of Oviedo, located in the Principality of Asturias, Spain. Finally, the advantages of the functional method are reported.

Study of Water Quality in a Spanish River Based on Statistical Process Control and Functional Data Analysis

2015 ◽  
Vol 48 (2) ◽  
pp. 163-186 ◽  
Author(s):  
J. Sancho ◽  
C. Iglesias ◽  
J. Piñeiro ◽  
J. Martínez ◽  
J. J. Pastor ◽  
...  
Keyword(s):  
Water Quality ◽  
Data Analysis ◽  
Process Control ◽  
Statistical Process Control ◽  
Functional Data Analysis ◽  
Functional Data ◽  
Statistical Process

Air quality parameters outliers detection using functional data analysis in the Langreo urban area (Northern Spain)

2014 ◽  
Vol 241 ◽  
pp. 1-10 ◽  
Author(s):  
J. Martínez ◽  
Á. Saavedra ◽  
P.J. García-Nieto ◽  
J.I. Piñeiro ◽  
C. Iglesias ◽  
...  
Keyword(s):  
Data Analysis ◽  
Air Quality ◽  
Urban Area ◽  
Functional Data Analysis ◽  
Functional Data ◽  
Quality Parameters ◽  
Northern Spain ◽  
Outliers Detection

Detection of outliers in gas emissions from urban areas using functional data analysis

2011 ◽  
Vol 186 (1) ◽  
pp. 144-149 ◽  
Author(s):  
J. Martínez Torres ◽  
P.J. Garcia Nieto ◽  
L. Alejano ◽  
A.N. Reyes
Keyword(s):  
Data Analysis ◽  
Functional Data Analysis ◽  
Functional Data ◽  
Urban Areas ◽  
Gas Emissions ◽  
Detection Of Outliers

A dynamic water quality index model based on functional data analysis

2015 ◽  
Vol 57 ◽  
pp. 249-258 ◽  
Author(s):  
Feng Yan ◽  
Ling Liu ◽  
Yanfeng Li ◽  
You Zhang ◽  
Musong Chen ◽  
...  
Keyword(s):  
Water Quality ◽  
Data Analysis ◽  
Functional Data Analysis ◽  
Functional Data ◽  
Water Quality Index ◽  
Quality Index ◽  
Index Model ◽  
Model Based

Detection of Outliers in GPS Measurements by Using Functional-Data Analysis

2011 ◽  
Vol 137 (4) ◽  
pp. 150-155 ◽  
Author(s):  
C. Ordoñez ◽  
J. Martínez ◽  
J. R. Rodríguez-Pérez ◽  
A. Reyes
Keyword(s):  
Data Analysis ◽  
Functional Data Analysis ◽  
Functional Data ◽  
Gps Measurements ◽  
Detection Of Outliers
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