Recent advances in neuro-fuzzy system: A survey
Abstrak
Abstract Neuro-fuzzy systems have attracted the growing interest of researchers in various scientific and engineering areas due to its effective learning and reasoning capabilities. The neuro-fuzzy systems combine the learning power of artificial neural networks and explicit knowledge representation of fuzzy inference systems. This paper proposes a review of different neuro-fuzzy systems based on the classification of research articles from 2000 to 2017. The main purpose of this survey is to help readers have a general overview of the state-of-the-arts of neuro-fuzzy systems and easily refer suitable methods according to their research interests. Different neuro-fuzzy models are compared and a table is presented summarizing the different learning structures and learning criteria with their applications.
Topik & Kata Kunci
Penulis (2)
K. Shihabudheen
G. Pillai
Akses Cepat
PDF tidak tersedia langsung
Cek di sumber asli →- Tahun Terbit
- 2018
- Bahasa
- en
- Total Sitasi
- 220×
- Sumber Database
- Semantic Scholar
- DOI
- 10.1016/J.KNOSYS.2018.04.014
- Akses
- Open Access ✓