Detecting abnormal ozone levels using PCA-based GLR hypothesis testing

Harrou, Fouzi; Nounou, Mohamed; Nounou, Hazem

doi:10.1109/cidm.2013.6597223

Cited by 14 publications

(11 citation statements)

References 20 publications

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“…It chooses between two composite hypotheses (Harrou et al, 2013c(Harrou et al, , 2009Lehmann, 1996;Harrou et al, 2013a). In binary hypothesis testing, when hypotheses are composite or the corresponding data probability density functions contain unknown parameters, the GLR test is a popular means for deciding between two possibilities.…”

Section: Glr Hypothesis Testingmentioning

confidence: 99%

Improved data-based fault detection strategy and application to distillation columns

Madakyaru

Harrou

Sun

2017

Process Safety and Environmental Protection

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Section: Glr Hypothesis Testingmentioning

confidence: 99%

Improved data-based fault detection strategy and application to distillation columns

Madakyaru

Harrou

Sun

2017

Process Safety and Environmental Protection

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“…The small scale of wireless sensor station to communicate with the backend server and provide their measurement in a real time however the collected data are process and analyse in order to provide these data in different format to the end user [10].…”

Section: B Wireless Sensor Network For Real Time Monitoringmentioning

confidence: 99%

Review Paper on Air Pollution Monitoring system

Sirsikar¹,

Karemore²

2015

International Journal of Advanced Research in Computer and Comm

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Air pollution monitoring is though old but very useful concept in day to day life. Air pollution monitoring start from traditional way to the most sophisticated computer has been used to monitor the air quality, however the fresh air is necessary for all human being, for that various technology has been used and some of this technology is really useful in order to provide a real time air quality data. Aim of this paper is to highlight some technology which is used for air pollution monitoring and how effective of these technologies are and identify the important research in this important area.

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“…Statistics-based methods have been widely applied in detecting outliers in environmental data (Harkat et al, 2006;Harrou et al, 2013) and process monitoring (Li et al, 2000). The most popular statistics are:…”

Section: Statistics-based Methodsmentioning

confidence: 99%

“…PCA is one of the most popular techniques for detecting outliers in various applications such as industrial processes (Li et al, 2000), environmental sensors (Harkatet al, 2006;Harrou et al,2013), distributed sensor networks (Chatzigiannakis and Papavassiliou, 2007), and high dimensional data (Ding and Kolaczyk, 2013). Most PCA-based models for outlier detection operate in batch mode (Chatzigiannakis and Papavassiliou, 2007;Harrou et al, 2013;Harkat et al, 2006), where the model is first trained using training data and is then used to test the remaining data for outliers.…”

Section: Introductionmentioning

confidence: 99%

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Incremental Principal Component Analysis Based Outlier Detection Methods for Spatiotemporal Data Streams

Bhushan

Sharker

Karimi

2015

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:In this paper, we address outliers in spatiotemporal data streams obtained from sensors placed across geographically distributed locations. Outliers may appear in such sensor data due to various reasons such as instrumental error and environmental change. Realtime detection of these outliers is essential to prevent propagation of errors in subsequent analyses and results. Incremental Principal Component Analysis (IPCA) is one possible approach for detecting outliers in such type of spatiotemporal data streams. IPCA has been widely used in many real-time applications such as credit card fraud detection, pattern recognition, and image analysis. However, the suitability of applying IPCA for outlier detection in spatiotemporal data streams is unknown and needs to be investigated. To fill this research gap, this paper contributes by presenting two new IPCA-based outlier detection methods and performing a comparative analysis with the existing IPCA-based outlier detection methods to assess their suitability for spatiotemporal sensor data streams.

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Detecting abnormal ozone levels using PCA-based GLR hypothesis testing

Cited by 14 publications

References 20 publications

Improved data-based fault detection strategy and application to distillation columns

Improved data-based fault detection strategy and application to distillation columns

Review Paper on Air Pollution Monitoring system

Incremental Principal Component Analysis Based Outlier Detection Methods for Spatiotemporal Data Streams

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