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Application of the InterCriteria Analysis Over Air Quality Data

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Part of the book series:Lecture Notes in Computer Science ((LNAI,volume 10333))

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Abstract

In the paper application of the InterCriteria analysis approach to real dataset with instances of hourly averaged responses from an array of 5 metal oxide chemical sensors embedded in an air quality chemical multisensor device [29,30] is represented. The InterCriteria analysis is a new method that can be used for multicriteria decision making. The aim is to analyze the correlations between 12 indicators representing the recordings of on field deployed air quality chemical sensor devices responses.

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Acknowledgments

The authors are thankful for the support provided by the Bulgarian National Science Fund under Grant Ref. No. DFNI-I-02-5 “InterCriteria Analysis: A New Approach to Decision Making”.

Author information

Authors and Affiliations

  1. Intelligent Systems Laboratory, University “Prof. Dr. Assen Zlatarov”, Burgas, Bulgaria

    Evdokia Sotirova, Veselina Bureva & Sotir Sotirov

  2. Department of Silicate Technology, University “Prof. Dr. Assen Zlatarov”, Burgas, Bulgaria

    Irena Markovska

  3. Medical University-Varna “Prof. Dr. P. Stoyanov”, Varna, Bulgaria

    Desislava Vankova

Authors
  1. Evdokia Sotirova

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  2. Veselina Bureva

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  3. Irena Markovska

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  4. Sotir Sotirov

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  5. Desislava Vankova

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Corresponding authors

Correspondence toEvdokia Sotirova orDesislava Vankova.

Editor information

Editors and Affiliations

  1. Roskilde University, Roskilde, Denmark

    Henning Christiansen

  2. ENSSAT-IRISA, Lannion Cedex, France

    Hélène Jaudoin

  3. University of Westminster, London, United Kingdom

    Panagiotis Chountas

  4. Roskilde University, Roskilde, Denmark

    Troels Andreasen

  5. Aalborg University, Esbjerg, Denmark

    Henrik Legind Larsen

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Sotirova, E., Bureva, V., Markovska, I., Sotirov, S., Vankova, D. (2017). Application of the InterCriteria Analysis Over Air Quality Data. In: Christiansen, H., Jaudoin, H., Chountas, P., Andreasen, T., Legind Larsen, H. (eds) Flexible Query Answering Systems. FQAS 2017. Lecture Notes in Computer Science(), vol 10333. Springer, Cham. https://doi.org/10.1007/978-3-319-59692-1_20

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JPY 3498
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