Traffic prediction using a Generic Self-Evolving Takagi-Sugeno-Kang (GSETSK) fuzzy neural network

• المؤلفون الرئيسيون: Nguyen, Ngoc Nam, Quek, Chai, Cheu, Eng Yeow
• مؤلفون آخرون: School of Computer Engineering
• التنسيق: Conference or Workshop Item
• اللغة: English
• منشور في: 2013
• الموضوعات: DRNTU::Engineering::Computer science and engineering
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/98295; http://hdl.handle.net/10220/12367
• المؤسسة: Nanyang Technological University

This paper analyses traffic prediction based on a Generic Self-Evolving Takagi-Sugeno-Kang (GSETSK) fuzzy neural network. Traffic prediction is a problem that requires online adaptive systems with high accuracy performance. The proposed GSETSK framework can learn incrementally with high accuracy wit...