scholarly journals Retraction Note to: Mountain air pollution evaluation and urban public art based on data mining

2021 ◽  
Vol 14 (23) ◽  
Author(s):  
Jun Zhang ◽  
Kele Zhang
Keyword(s):  
Data Mining ◽  
Air Pollution ◽  
Public Art ◽  
Pollution Evaluation

scholarly journals Canonical PSO Based K-Means Clustering Approach for Real Datasets

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Lopamudra Dey ◽  
Sanjay Chakraborty
Keyword(s):  
Data Mining ◽  
Air Pollution ◽  
Clustering Algorithm ◽  
Clustering Algorithms ◽  
Real Life ◽  
Cluster Validity ◽  
Validity Assessment ◽  
Different Types ◽  
Clustering Approach ◽  
Validity Measure

“Clustering” the significance and application of this technique is spread over various fields. Clustering is an unsupervised process in data mining, that is why the proper evaluation of the results and measuring the compactness and separability of the clusters are important issues. The procedure of evaluating the results of a clustering algorithm is known as cluster validity measure. Different types of indexes are used to solve different types of problems and indices selection depends on the kind of available data. This paper first proposes Canonical PSO based K-means clustering algorithm and also analyses some important clustering indices (intercluster, intracluster) and then evaluates the effects of those indices on real-time air pollution database, wholesale customer, wine, and vehicle datasets using typical K-means, Canonical PSO based K-means, simple PSO based K-means, DBSCAN, and Hierarchical clustering algorithms. This paper also describes the nature of the clusters and finally compares the performances of these clustering algorithms according to the validity assessment. It also defines which algorithm will be more desirable among all these algorithms to make proper compact clusters on this particular real life datasets. It actually deals with the behaviour of these clustering algorithms with respect to validation indexes and represents their results of evaluation in terms of mathematical and graphical forms.

Urban background of air pollution: Evaluation through moss bag biomonitoring of trace elements in Botanical garden

2017 ◽  
Vol 25 ◽  
pp. 1-10 ◽  
Author(s):  
Mira Aničić Urošević ◽  
Gordana Vuković ◽  
Petar Jovanović ◽  
Milorad Vujičić ◽  
Aneta Sabovljević ◽  
...  
Keyword(s):  
Air Pollution ◽  
Trace Elements ◽  
Botanical Garden ◽  
Urban Background ◽  
Pollution Evaluation

Spatio-Temporal Data Mining for Air Pollution Problems

2011 ◽  
pp. 1815-1822 ◽  
Author(s):  
Seoung Bum Kim ◽  
Chivalai Temiyasathit ◽  
Sun-Kyoung Park ◽  
Victoria C.P. Chen
Keyword(s):  
Data Mining ◽  
Air Pollution ◽  
Real Data ◽  
Ambient Air ◽  
Ambient Air Pollution ◽  
Temporal Data Mining ◽  
Area Of Interest ◽  
Mining Methods ◽  
Spatio Temporal ◽  
Temporal And Spatial Characteristics

Vast amounts of data are being generated to extract implicit patterns of ambient air pollution. Because air pollution data are generally collected in a wide area of interest over a relatively long period, such analyses should take into account both temporal and spatial characteristics. Furthermore, combinations of observations from multiple monitoring stations, each with a large number of serially correlated values, lead to a situation that poses a great challenge to analytical and computational capabilities. Data mining methods are efficient for analyzing such large and complicated data. Despite the great potential of applying data mining methods to such complicated air pollution data, the appropriate methods remain premature and insufficient. The major aim of this chapter is to present some data mining methods, along with the real data, as a tool for analyzing the complex behavior of ambient air pollutants.

scholarly journals A systematic review of data mining and machine learning for air pollution epidemiology

2017 ◽  
Vol 17 (1) ◽  
Author(s):  
Colin Bellinger ◽  
Mohomed Shazan Mohomed Jabbar ◽  
Osmar Zaïane ◽  
Alvaro Osornio-Vargas
Keyword(s):  
Machine Learning ◽  
Systematic Review ◽  
Data Mining ◽  
Air Pollution ◽  
Air Pollution Epidemiology

Indoor air pollution evaluation with emphasize on HDI and biological assessment of HDA in the polyurethane factories

2009 ◽  
Vol 165 (1-4) ◽  
pp. 341-347 ◽  
Author(s):  
Mirtaghi Mirmohammadi ◽  
M. Hakimi Ibrahim ◽  
Anees Ahmad ◽  
Mohd Omar Abdul Kadir ◽  
M. Mohammadyan ◽  
...  
Keyword(s):  
Air Pollution ◽  
Indoor Air ◽  
Indoor Air Pollution ◽  
Biological Assessment ◽  
Pollution Evaluation

Air Pollution Evaluation of Titan II Test Firings

AIHAJ ◽  
1965 ◽  
Vol 26 (4) ◽  
pp. 419-422 ◽  
Author(s):  
Philip Diamond ◽  
Hamilton K. Johnson
Keyword(s):  
Air Pollution ◽  
Pollution Evaluation
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