Generating IoT traffic: A Case Study on Anomaly Detection

2020 IEEE International Symposium on Local and Metropolitan Area Networks (LANMAN ◽

10.1109/lanman49260.2020.9153235 ◽

2020 ◽

Cited By ~ 1

Author(s):

Hung Nguyen-An ◽

Thomas Silverston ◽

Taku Yamazaki ◽

Takumi Miyoshi

Keyword(s):

Anomaly Detection

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Meteorological and human mobility data on predicting COVID-19 cases by a novel hybrid decomposition method with anomaly detection analysis: a case study in the capitals of Brazil

Expert Systems with Applications ◽

10.1016/j.eswa.2021.115190 ◽

2021 ◽

pp. 115190

Author(s):

Tiago Tiburcio da Silva ◽

Rodrigo Francisquini ◽

Maric C. V. Nascimento

Keyword(s):

Anomaly Detection ◽

Decomposition Method ◽

Human Mobility ◽

Mobility Data ◽

Detection Analysis ◽

Hybrid Decomposition

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Classification and Anomaly Detection in Traffic Patterns of New York City Taxis: A Case Study in Compound Analytics

2018 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW) ◽

10.1109/ipdpsw.2018.00181 ◽

2018 ◽

Author(s):

Ronald D. Hagan ◽

Charles A. Phillips ◽

Michael A. Langston ◽

Bradley J. Rhodes

Keyword(s):

New York ◽

New York City ◽

Anomaly Detection ◽

York City ◽

Traffic Patterns

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An Efficient Anomaly Detection in Quasi-Periodic Time Series Data—A Case Study with ECG

Time Series Analysis and Forecasting - Contributions to Statistics ◽

10.1007/978-3-319-96944-2_10 ◽

2018 ◽

pp. 147-157 ◽

Cited By ~ 1

Author(s):

Goutam Chakraborty ◽

Takuya Kamiyama ◽

Hideyuki Takahashi ◽

Tetsuo Kinoshita

Keyword(s):

Time Series ◽

Anomaly Detection ◽

Time Series Data ◽

Series Data ◽

Periodic Time Series

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Time Series Analysis for Anomaly Detection of Water Consumption: A Case Study

Innovations in Industrial Engineering - Lecture Notes in Mechanical Engineering ◽

10.1007/978-3-030-78170-5_21 ◽

2021 ◽

pp. 234-245

Author(s):

Marta Santos ◽

Ana Borges ◽

Davide Carneiro ◽

Flora Ferreira

Keyword(s):

Time Series ◽

Time Series Analysis ◽

Anomaly Detection ◽

Water Consumption ◽

Series Analysis

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Behavior Anomaly Detection in SDN Control Plane: A Case Study of Topology Discovery Attacks

2019 International Conference on Information and Communication Technology Convergence (ICTC) ◽

10.1109/ictc46691.2019.8939903 ◽

2019 ◽

Cited By ~ 1

Author(s):

Li-Der Chou ◽

Chien-Chang Liu ◽

Meng-Sheng Lai ◽

Kai-Cheng Chiu ◽

Hsuan-Hao Tu ◽

...

Keyword(s):

Anomaly Detection ◽

Topology Discovery ◽

Control Plane

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Feasibility study of thermal anomaly detection for earthquake: A case study from 2014 Mae Lao earthquake, Thailand

IOP Conference Series Earth and Environmental Science ◽

10.1088/1755-1315/538/1/012034 ◽

2020 ◽

Vol 538 ◽

pp. 012034

Author(s):

P Wongpornchai ◽

C Suwanprasit

Keyword(s):

Anomaly Detection ◽

Feasibility Study ◽

Thermal Anomaly

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LSTM Based Prediction and Time-Temperature Varying Rate Fusion for Hydropower Plant Anomaly Detection: A Case Study

Advanced Manufacturing and Automation VIII - Lecture Notes in Electrical Engineering ◽

10.1007/978-981-13-2375-1_13 ◽

2018 ◽

pp. 86-94 ◽

Cited By ~ 1

Author(s):

Jin Yuan ◽

Yi Wang ◽

Kesheng Wang

Keyword(s):

Anomaly Detection ◽

Hydropower Plant

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A deep learning approach for anomaly detection with industrial time series data: a refrigerators manufacturing case study

Procedia Manufacturing ◽

10.1016/j.promfg.2020.01.031 ◽

2019 ◽

Vol 38 ◽

pp. 233-240 ◽

Cited By ~ 2

Author(s):

Mattia Carletti ◽

Chiara Masiero ◽

Alessandro Beghi ◽

Gian Antonio Susto

Keyword(s):

Time Series ◽

Deep Learning ◽

Anomaly Detection ◽

Time Series Data ◽

Series Data ◽

Learning Approach

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Big-data-driven anomaly detection in industry (4.0): An approach and a case study

2016 IEEE International Conference on Big Data (Big Data) ◽

10.1109/bigdata.2016.7840777 ◽

2016 ◽

Cited By ~ 22

Author(s):

Ljiljana Stojanovic ◽

Marko Dinic ◽

Nenad Stojanovic ◽

Aleksandar Stojadinovic

Keyword(s):

Big Data ◽

Anomaly Detection ◽

Industry 4.0 ◽

Data Driven

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Long short‐term memory based anomaly detection: A case study of China railway passenger ticketing system

IET Intelligent Transport Systems ◽

10.1049/itr2.12007 ◽

2020 ◽

Author(s):

Ze Xie ◽

Jiansheng Zhu ◽

Fuzhang Wang ◽

Wen Li ◽

Tuo Wang

Keyword(s):

Anomaly Detection ◽

Short Term Memory ◽

Short Term ◽

Term Memory ◽

Long Short Term Memory ◽

China Railway ◽

Railway Passenger

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