Krystyna Kiersztyn

Orcid: 0000-0003-1957-1797

According to our database1, Krystyna Kiersztyn authored at least 15 papers between 2020 and 2024.

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Bibliography

2024
Random clustering-based outlier detector.
Inf. Sci., 2024

2023
Choquet Integral-Based Aggregation for the Analysis of Anomalies Occurrence in Sustainable Transportation Systems.
IEEE Trans. Fuzzy Syst., February, 2023

An Application of Fuzzy Techniques to Predict the Polymorphism of Selected Microsatellite Sequences.
Proceedings of the Artificial Intelligence and Soft Computing, 2023

The Concept of a City Bike Network Management System Using Fuzzy Sets.
Proceedings of the IEEE International Conference on Fuzzy Systems, 2023

2022
Detection and Classification of Anomalies in Large Datasets on the Basis of Information Granules.
IEEE Trans. Fuzzy Syst., 2022

Intuitively adaptable outlier detector.
Stat. Anal. Data Min., 2022

An Application of Information Granules to Detect Anomalies in COVID-19 Reports.
Proceedings of the Artificial Intelligence and Soft Computing, 2022

The Impact of Data Preprocessing on Prediction Effectiveness.
Proceedings of the Artificial Intelligence and Soft Computing, 2022

Analysis of the Homozygosity of Microsatellite Markers by Using Fuzzy Sets.
Proceedings of the IEEE International Conference on Fuzzy Systems, 2022

Fuzzy Modification of Analytic Hierarchy Process Using GUI Tools.
Proceedings of the IEEE International Conference on Fuzzy Systems, 2022

Fuzzy Rule-based Outlier Detector.
Proceedings of the IEEE International Conference on Fuzzy Systems, 2022

2021
A Comprehensive Analysis of the Impact of Selecting the Training Set Elements on the Correctness of Classification for Highly Variable Ecological Data.
Proceedings of the 30th IEEE International Conference on Fuzzy Systems, 2021

The Concept of Granular Representation of the Information Potential of Variables.
Proceedings of the 30th IEEE International Conference on Fuzzy Systems, 2021

Classification of Complex Ecological Objects with the Use of Information Granules.
Proceedings of the 30th IEEE International Conference on Fuzzy Systems, 2021

2020
The Concept of Detecting and Classifying Anomalies in Large Data Sets on a Basis of Information Granules.
Proceedings of the 29th IEEE International Conference on Fuzzy Systems, 2020


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