An Artificial Immune System based On-line Learning Neuro-Fuzzy System and Its Applications

• Main Authors: Yuan-Shao Yang, 楊元韶
• Other Authors: Mu-Chun Su
• Format: Others
• Language: zh-TW
• Published: 2004
• Online Access: http://ndltd.ncl.edu.tw/handle/55186086811839901432

碩士 === 國立中央大學 === 資訊工程研究所 === 92 === In some applications, systems should be able to learn new classes and refine existing classes quickly and without destroying old class information. This property is referred to as on-line learning and it is a very appealing property for an efficient pattern recognition system. The immune system is a highly complicated system. Many properties of immune systems attract a great amount of attentions from compute scientists and engineers. In recently years, many artificial immune systems have been proposed. Different artificial immunes systems are inspired by different subsets of the available metaphors. In this paper, we present an on-line learning neuro-fuzzy system which was inspired by part of the mechanisms in immune systems. We name the proposed neuro-fuzzy system as the artificial immune system based neuro-fuzzy system (AISNFS). During the learning procedure, a neuro-fuzzy system can be incrementally constructed. AISNFS can be applied in pattern recognition and function approximation problems. The performance of the propose AISNFS is evaluated by not only some artificial data sets but also some real data sets. Especially, we apply the proposed AISNFS in the compensation of backlight images.