Identification of outliers in pollution concentration levels using anomaly detection

被引：0
|
作者：
Anandharajan, T. R. V. [1 ]
Vignajeth, K. K. [1 ]
Hariharan, G. Abhishek [1 ]
Jijendiran, R. [1 ]
机构：
[1] Velammal Inst Technol, Madras, Tamil Nadu, India
来源：
2016 INTERNATIONAL CONFERENCE ON COMPUTATIONAL TECHNIQUES IN INFORMATION AND COMMUNICATION TECHNOLOGIES (ICCTICT) | 2016年
关键词：
AirPollution; MachineLearning; Anomaly detection; Air quality Index;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Anomaly detection is generally an identification of any odd or anomalous data sometimes even called as an outlier from a give pattern of data. It involves machine learning technique to learn the data and determine the outliers based on a probability condition. Machine learning, a branch of artificial intelligence plays a vital role in analyzing the data and identifies the outliers with a good probability. The objective of this paper is to determine the outlier of pollutant's concentration based on anomaly detection techniques and describe the air quality standards of the particular area.
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页数：6
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