Identification of feature selection techniques for software defect prediction by using BCF-WASPAS methodology based on Einstein operators DOI
Ubaid ur Rehman,

Tahir Mahmood

International Journal of Intelligent Computing and Cybernetics, Journal Year: 2024, Volume and Issue: 18(1), P. 183 - 216

Published: Dec. 16, 2024

Purpose This research focuses on a very important question of determining the appropriate feature selection methods for software defect prediction. The study is centered creation new method that would enable identification both positive and negative criteria handling ambiguous information in decision-making process. Design/methodology/approach To do so, we develop an improved by extending WASPAS assessment context bipolar complex fuzzy sets, which leads to method. approach also uses Einstein operators increase accuracy aggregation manage complicated parameters. methodology designed processing multi-criteria problems where have polarities as well other information. Findings It shown proposed outperforms traditional weighted sum or product models when assessing methods. incorporation sets with improves taking into account aspects criteria, contributes more accurate We investigate case related techniques prediction using methodology. compare certain prevailing ones reveal supremacy requirements theory. Originality/value offers first integrated framework bipolarity uncertainty combination DM process, will be useful engineers help them select best techniques. work helps enhance overall performance systems.

Language: Английский

Complex q-rung orthopair fuzzy Yager aggregation operators and their application to evaluate the best medical manufacturer DOI

Shumaila Javeed,

Mubashar Javed,

Izza Shafique

et al.

Applied Soft Computing, Journal Year: 2024, Volume and Issue: 157, P. 111532 - 111532

Published: March 26, 2024

Language: Английский

Citations

6
Significance and classification of AI-driven techniques in telecommunication sectors based on interval-valued bipolar fuzzy soft aggregation operators DOI Creative Commons
Jabbar Ahmmad, Meraj Ali Khan,

Ibrahim Al-Dayel

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: April 23, 2025

In the context of telecommunications, AI enhances network efficiency by predicting and managing traffic. many decision-making scenarios, decision-makers choose more flexible structure that can handle all kinds information. Bipolarity is only case in which we discuss positive negative aspects certain scenarios. On one side, efficiency, proactive maintenance, personalized customer experience but on other hand, it has also some (1) implementing infrastructure be costly (2) Uses telecommunication may raise data security concerns user privacy (3) lead to potential issues if system fail or misused. To cover these issues, idea an interval-valued bipolar fuzzy soft set (IVBFSS) been developed deal with both AI. Some basic operational laws for IVBPFS numbers are developed. Several fundamental aggregation operators have introduced like arithmetic average geometric operators, indicating our main contribution. An algorithm application perspective initiated approaches. We utilized notions classify AI-driven techniques telecommunications sector applicability notions. A comparative analysis approaches shows advantages superiority work.

Language: Английский

Citations

0
Dynamic q-Rung Orthopair Hesitant Fuzzy Decision-making Model based on Banzhaf Value of Fuzzy Measure DOI
Yibo Wang, Xiuqin Ma, Hongwu Qin

et al.

Applied Soft Computing, Journal Year: 2025, Volume and Issue: unknown, P. 113036 - 113036

Published: March 1, 2025

Language: Английский

Citations

0
Identification of feature selection techniques for software defect prediction by using BCF-WASPAS methodology based on Einstein operators DOI
Ubaid ur Rehman,

Tahir Mahmood

International Journal of Intelligent Computing and Cybernetics, Journal Year: 2024, Volume and Issue: 18(1), P. 183 - 216

Published: Dec. 16, 2024

Purpose This research focuses on a very important question of determining the appropriate feature selection methods for software defect prediction. The study is centered creation new method that would enable identification both positive and negative criteria handling ambiguous information in decision-making process. Design/methodology/approach To do so, we develop an improved by extending WASPAS assessment context bipolar complex fuzzy sets, which leads to method. approach also uses Einstein operators increase accuracy aggregation manage complicated parameters. methodology designed processing multi-criteria problems where have polarities as well other information. Findings It shown proposed outperforms traditional weighted sum or product models when assessing methods. incorporation sets with improves taking into account aspects criteria, contributes more accurate We investigate case related techniques prediction using methodology. compare certain prevailing ones reveal supremacy requirements theory. Originality/value offers first integrated framework bipolarity uncertainty combination DM process, will be useful engineers help them select best techniques. work helps enhance overall performance systems.

Language: Английский

Citations

0