Abstract
There are several tools of artificial intelligence (AI) that help utilize human knowledge about the systems to enhance performance of the system. Some of the major AI tools are artificial neural networks (ANNs), fuzzy logic, genetic algorithms, and expert systems. This research exploits capabilities of neural networks and fuzzy logic to develop adaptive intelligent handoff algorithms. The focus of this chapter is on fuzzy logic systems and ANNs. Concepts of fuzzy logic theory and components of a popular fuzzy logic system (FLS) are discussed. Two ANN paradigms, multi-layer perceptron (MLP) and radial basis function network (RBFN), are introduced. The training process of these ANNs is explained.
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© 2001 Springer Science+Business Media New York
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Tripathi, N.D., Reed, J.H., Vanlandingham, H.F. (2001). Fuzzy Logic and Neural Networks. In: Radio Resource Management in Cellular Systems. The Springer International Series in Engineering and Computer Science, vol 618. Springer, Boston, MA. https://doi.org/10.1007/0-306-47318-6_2
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DOI: https://doi.org/10.1007/0-306-47318-6_2
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4419-4897-7
Online ISBN: 978-0-306-47318-0
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