A new design method based on artificial bee colony algorithm for digital IIR filters
By N. Karaboga. Journal of the Franklin Institute, 2009
596 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computational Mechanics, Signal Processing
View Paper: https://www.semanticscholar.org/paper/91c792b9f8164b90aa70c8567f38ebed034b7958
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Pinar Çivicioglu
- Erkan Besdok
- Bahriye Akay
- Sam Kwong
- Guopu Zhu
- Dervis Karaboga
- Ebubekir Kaya
- Azlan Mohd Zain
In Computational Mechanics
- Sam Kwong
- Ahmet Cosar
- Dervis Karaboga
- Tansel Dökeroğlu
- Azlan Mohd Zain
- Tayfun Kucukyilmaz
- Pinar Çivicioglu
- Sin C. Ho
In Signal Processing
- Sam Kwong
- Ahmet Cosar
- Dervis Karaboga
- Tansel Dökeroğlu
- Azlan Mohd Zain
- Tayfun Kucukyilmaz
- Pinar Çivicioglu
- Sin C. Ho
Citations in the corpus
- A comparative study of Artificial Bee Colony algorithm (2009, methodology): “ABC algorithm was used for designing IIR filters in [33] and for the leaf-constrained minimum spanning tree problem in [34].”
- Gbest-guided artificial bee colony algorithm for numerical function optimization (2010, methodology): “According to their experimental results, ABC algorithm can be an alternative to design low-and high-order digital IIR filters [14].”
- An artificial bee colony algorithm for the capacitated vehicle routing problem (2011, methodology): “However, ABC has been applied to solve other problems with great success (Baykaso ğ ly et al., 2007; Kang et al., 2009; Karaboga, 2009; Karaboga and Basturk, 2007, 2008; Karaboga and Ozturk, 2009; Singh, 2009).”
- A survey: algorithms simulating bee swarm intelligence (2009, methodology): “Karaboga (2009) used ABC algorithm in signal processing area for designing digital IIR filters.”
- Evolutionary techniques in optimizing machining parameters: Review and recent applications (2007-2011) (2012, methodology): “The abilities of ABC algorithm have been discussed by Rao et al. (2008), Karaboga (2009), Benala, Jampala, Villa, and Konathala (2009), Akay and Karaboga (2010), Karaboga and Akay (2009) Rao and Pawar (2010b) and Akay and Karaboga (2009).”
- A survey on new generation metaheuristic algorithms (2019, methodology): “Karaboga (2009) proposes a new ABC algorithm for designing digital Infinite Impulse Response filters.”
- A conceptual comparison of the Cuckoo-search, particle swarm optimization, differential evolution and artificial bee colony algorithms (2011, methodology): “…Swagatam et al. 2009; Janez et al. 2007), Artificial bee colony algorithm (Karaboga and Akay 2009a; Karaboga and Basturk 2007a,b; Janez et al. 2007; Karaboga 2009; Fei et al. 2009), Cuckoo Search Algorithm (Yang and Deb 2009; Deb et al. 2002), Gravitational Search Algorithm (Rashedi et al. 2009;…”
- Adaptive network based fuzzy inference system (ANFIS) training approaches: a comprehensive survey (2018, background): “Artificial neural network training (Karaboga and Kaya 2007), engineering (Karaboga 2009), image processing (Akay and Karaboga 2011), data mining (Karaboga et al. 2012), sensor networks (Okdem et al. 2011), protein structure optimization (Bahamish and Abdullah 2010) are some of the areas in which…”