Implementation of Speculate Modules and Performance Evaluation of Data Mining Clustering Techniques on Air Quality Index and Health Index to Predict High-Risk Air Polluted Stations of a Metropolitan City Using R Programming

Author(s):  
N. Asha ◽  
M. P. Indira Gandhi
2019 ◽  
Vol 35 ◽  
pp. 623-628 ◽  
Author(s):  
Thembinkosi Nkonyana ◽  
Yanxia Sun ◽  
Bhekisipho Twala ◽  
Eustace Dogo

Atmosphere ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1078
Author(s):  
Georgi Gadzhev ◽  
Kostadin Ganev

Air pollution is responsible for many adverse effects on human beings. Thermal discomfort, on the other hand, is able to overload the human body and eventually provoke health implications due to the heat imbalance. Methods: The aim of the presented work is to study the behavior of two bio-climatic indices and statistical characteristics of the air quality index for Sofia city—the capital of Bulgaria for the period 2008–2014. The study is based on the WRF-CMAQ model system simulations with a spatial resolution of 1 km. The air quality is estimated by the air quality index, taking into account the influence of different pollutants and the thermal conditions by two indices, respectively, for hot and cold weather. It was found that the recurrence of both the heat and cold index categories and of the air quality categories have heterogeneous space distribution and well manifested diurnal and seasonal variability. For all of the situations, only O3 and PM10 are the dominant pollutants—these which determine the AQI category. It was found that AQI1, AQI2, and AQI3, which fall in the “Low” band, have the highest recurrence during the different seasons, up to more than 70% in some places and situations. The recurrence of AQI10 (very high) is rather small—no more than 5% and concentrated in small areas, mostly in the city center. The Heat index of category “Danger” never appears, and the Heat index of category “Extreme caution” appears only in the spring and summer with the highest recurrence of less than 5% in the city center. For the Wind-chill index category, “Very High Risk” never appears, and the category “High Risk” appears with a frequency of about 1–2%. The above leads to the conclusion that both from a point of view of bioclimatic and air quality indices, the human health risks in the city of Sofia are not as high.


2021 ◽  
Vol 67 ◽  
pp. 102720
Author(s):  
R. Janarthanan ◽  
P. Partheeban ◽  
K. Somasundaram ◽  
P. Navin Elamparithi

Webology ◽  
2020 ◽  
Vol 17 (2) ◽  
pp. 01-14
Author(s):  
Yaser Issam Hamodi ◽  
Ruaa Riyadh Hussein ◽  
Naeem Th. Yousir

A performance evaluation of four different clustering techniques was carried out based on segmenting consumer by product type and by product usage in the research. Cobweb, DBSCAN, EM and k-means algorithms were evaluated based on the computational time, accuracy of the result produced and the purity of the result produced. The experiment was performed using WEKA as a data mining tool. The performance evaluation of the four techniques showed that K-means outperformed others in all considered evaluation measure while the EM technique was the second best in terms of accuracy and purity, outperforming the other two. DBSCAN technique was the 3rd best of the selected algorithms even as its computational time is shorter than that of EM while the fourth best performing calculation has been believed to be the Spider web calculation as respects to immaculateness, exactness and computational time.


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