Scopus
YÖKSİS Eşleşti
Parametric picture fuzzy cross-entropy measures based on d-Choquet integral for building material recognition
Applied Soft Computing · Kasım 2024
YÖKSİS Kayıtları
Parametric picture fuzzy cross-entropy measures based on d-Choquet integral for building material recognition Applied Soft Computing
Applied Soft Computing · 2024 SCI-Expanded
DOÇENT DİLEK SÖYLEMEZ ÖZDEN →
Makale Bilgileri
DergiApplied Soft Computing
Yayın TarihiKasım 2024
Cilt / Sayfa166
Scopus ID2-s2.0-85202813856
Özet
This research paper introduces a novel picture fuzzy cross-entropy measure that utilizes Lin's divergence as a basis for comparing two picture fuzzy sets. To improve the flexibility and applicability of this new cross-entropy measure, a family of parametric cross-entropy measures is defined. By adjusting the parameters in applications, the influence of the degree of positive membership, negative membership, and neutral membership on the picture fuzzy cross-entropy can be observed, allowing for a more tailored analysis. Additionally, we investigate the relationship between power weighted means and the d-Choquet integral, which serves as an extension of the ordinary Choquet integral. Using this knowledge, picture fuzzy cross-entropy measures based on the d-Choquet integral are introduced to yield more sensitive results, particularly when interactions between criteria exist in specific problem domains. This consideration of criterion interactions is often absent in existing cross-entropy measures. Moreover, an algorithm is presented for solving pattern recognition problems and applied to a building material recognition problem sourced from existing literature. Then, we proposed another algorithm and use it to investigate a novel material classification problem. Through these applications, the effectiveness of the proposed cross-entropy measures in pattern recognition is demonstrated. The paper conducts a comparative analysis between existing methods and the proposed approaches, followed by a sensitivity analysis. This analysis involves manipulating the parameters derived from both the parametric cross-entropy measures and the d-Choquet integrals to assess their respective impacts and sensitivities. Finally, the results regarding the classification problem are examined with performance metrics such as accuracy, precision, recall, and F1 score.
Yazarlar (4)
1
Mahmut Can Bozyı̇ğı̇t
2
Murat Olgun
3
Mehmet Ünver
ORCID: 0000-0002-0857-1006
4
Di̇lek Söylemez
Anahtar Kelimeler
Classification
Entropy
Pattern recognition
Picture fuzzy set
Kurumlar
Ankara Üniversitesi
Ankara Turkey
Ankara Yildirim Beyazit University
Ankara Turkey
Selçuk Üniversitesi
Selçuklu Turkey
Metrikler
10
Atıf
4
Yazar
4
Anahtar Kelime