Special Issues

Data Analytics for Critical Infrastructures

Submission Deadline: 01 December 2022 (closed) View: 148

Guest Editors

Dr. Süleyman Eken, Kocaeli University, Turkey. Dr. Alaa Ali Hameed, Istinye University, Turkey. Dr. Akhtar Jamil, University of Computer and Emerging Sciences, Pakistan.

Summary

Critical infrastructures (CI) are organizational and physical structures and facilities of such vital importance to a nation's society and economy. CI includes the vast network of highways, connecting bridges and tunnels, railways, utilities and buildings necessary to maintain normalcy in daily life. Transportation, commerce, clean water and electricity all rely on these vital systems. Data Analytics is considered to be a relatively new field which turns the high-volume data into useful information that will be used for better decision making.

 

International Conference on Computing, Intelligence and Data Analytics (ICCIDA) is organized by the Department of Information Systems Engineering at Kocaeli University, Turkey. The conference will serve as an interdisciplinary forum that may help the research community to take a step forward and share the research findings. In addition, it will provide an arena where researchers, scholars, professionals, students, and academicians may be able to foster working relationships and gain access to the latest research results. ICCIDA 2022 (http://iccida.net/) will be held on September 16-17, 2022. Due to the COVID-19 restrictions, it will be held online in this year. Selected high quality papers presented at ICCIDA 2022 will be invited to submit extended versions for this special issue. Original technical papers with novel contributions are also welcome. Potential topics under the special issue include but are not limited to the following:

 

-Different types of analytics such as descriptive, diagnostic, predictive, and prescriptive for CI

-System and network security

-Soft computing techniques for critical infrastructures

-Convergence of blockchain and edge computing for scalable critical infrastructures

-New architectures for CI data analysis

-Fog-enabled IoT applications for critical infrastructures

-Case-studies on different CI systems


Keywords

Data Analytics, Computing, Intelligence, Critical Infrastructure

Published Papers


  • Open Access

    ARTICLE

    SCADA Data-Based Support Vector Machine for False Alarm Identification for Wind Turbine Management

    Ana María Peco Chacón, Isaac Segovia Ramírez, Fausto Pedro García Márquez
    Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2595-2608, 2023, DOI:10.32604/iasc.2023.037277
    (This article belongs to the Special Issue: Data Analytics for Critical Infrastructures)
    Abstract Maintenance operations have a critical influence on power generation by wind turbines (WT). Advanced algorithms must analyze large volume of data from condition monitoring systems (CMS) to determine the actual working conditions and avoid false alarms. This paper proposes different support vector machine (SVM) algorithms for the prediction and detection of false alarms. K-Fold cross-validation (CV) is applied to evaluate the classification reliability of these algorithms. Supervisory Control and Data Acquisition (SCADA) data from an operating WT are applied to test the proposed approach. The results from the quadratic SVM showed an accuracy rate of More >

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