BBA: A Binary Bat Algorithm for Feature Selection

By Rodrigo Nakamura, Luís A. M. Pereira, Kelton Augusto Pontara Da Costa, Douglas Rodrigues, João Paulo Papa, Xin-She Yang. SIBGRAPI Conference on Graphics, Patterns and Images, 2012

409 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Cancer Research, Civil and Structural Engineering

View Paper: https://www.semanticscholar.org/paper/724817eb42342c54d56bf46503e54961dc69b196

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biomedical Engineering

1. Xingshi He
2. Ali Wagdy Mohamed
3. Xin-She Yang
4. Aboul Ella Otifey Hassanien
5. Hossam M. Zawbaa
6. Eid Emary
7. Talari Ganesh
8. Hattan F. Abutarboush

In Cancer Research

1. Xin-She Yang

In Civil and Structural Engineering

1. Xingshi He
2. Xin-She Yang
3. Aboul Ella Otifey Hassanien
4. Mehmet Karamanoglu
5. Yujun Zheng

Citations in the corpus

• Binary ant lion approaches for feature selection (2016, background): “It is important to assign for every bat a set of binary coordinates that indicate if this feature will belong to the final feature set [21].”
• Bat algorithm: literature review and applications (2013, methodology): “Nakamura et al. (2012) extended the standard bat algorithm to the so-called binary bat algorithm (BBA) for feature selection.”
• Metaheuristic Algorithms on Feature Selection: A Survey of One Decade of Research (2009-2019) (2021, background): “In solving feature selection problems, firstly Nakamura et al. [138] developed a binary version of BA (BBA) with sigmoid function to restrict the position of bat’s to binary variables.”
• Binary grey wolf optimization approaches for feature selection (2016, background): “So, the optimal (near to optimal) solution corresponds to one hypercube's corner [18].”