Titlebook: Computational Intelligence; Engineering of Hybri Mircea Gh. Negoita,Daniel Neagu,Vasile Palade Book 2005 Springer-Verlag Berlin Heidelberg

不給啤

Neuro-Fuzzy Integration in Hybrid Intelligent Systems,tion offers the advantage of homogeneity, as well as the possibility of performing distributed tasks, and working with incomplete and noisy data. From the point of view of knowledge-based systems, symbolic representations have advantages of human interpretation, explicit control, and knowledge abstraction (Kosko 1992; Wermter and Sun 2000).

外面

,New Trends of Developing Hybrid Intelligent Systems – AIS Hybridization and DNA-Hybridization,iplinary development approach of . and . reliant hybridisation algorithms, techniques and application was created by the collective effort of a large spectrum of high technology practitioners; mainly the computer scientists, engineers acting in different technicalfields, biologists and natural environment specialists.

Hyperalgesia

Commonplace

嫌惡

Aerate

粗語(yǔ)

inclusive

Fuzzy Rules Extraction from Connectionist Structures,s to exhibit and explain the results of neural calculus as a parallel inference process. This chapter focuses on a strictly fuzzy approach to neural networks. It presents some interactive fuzzy operators in order to extract connectionist-represented knowledge, based on the concept of .-duality. The

細(xì)胞

instill

Practical Implementation Aspects Regarding Real-World Application of Hybrid Intelligent Systems,could be reviewed, but this is beyond the topic of this book. We tried to introduce just some special original applications. On the other hand, this chapter will also be focused on some combined approaches which involve the main . techniques, but at the same time are both fundamental and with a very