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What is Neuro-Fuzzy System (NFS)

Chapter 6
Handbook of Research on Business Social Networking: Organizational, Managerial, and Technological Dimensions
Also known as Fuzzy Neural Network (FNN) refers to combinations of artificial neural networks and fuzzy logic that synergize these two techniques by combining the human-like reasoning style of fuzzy systems with the learning and connectionist structure of neural networks. Neuro-fuzzy system incorporates the human-like reasoning style of fuzzy systems through the use of fuzzy sets and a linguistic model consisting of a set of IF-THEN fuzzy rules. The main strength of neuro-fuzzy systems is that they are universal approximators with the ability to solicit interpretable IF-THEN rules.
Published in Chapter:
A Neuro-Fuzzy Partner Selection System for Business Social Networks
T. T. Wong (The Hong Kong Polytechnic University, Hong Kong) and Loretta K.W. Sze (The Hong Kong Polytechnic University, Hong Kong)
Copyright: © 2012 |Pages: 21
DOI: 10.4018/978-1-61350-168-9.ch006
Abstract
Enterprises are now facing growing global competition and the continual success in the marketplace depends very much on how efficient and effective companies are able to respond to customer demands. Business social network sites (BSNS) have provided a powerful tool to link up manufacturers, suppliers, distributors, and customers. Among the emerging business social networks, decision support functionality addressing the issue of selecting business partners is an important domain to be studied, and it is the objective of this chapter to propose a practical partner selection decision support system. Essentially, a neural-network data mining system is used to generate information for subsequent fuzzy multi-objective analysis. It demonstrates the benefits of integrating information technology, artificial intelligence, and multi-objective decision making to form a practical aid that capitalizes on the merits of BSNS. A special feature is that the trust among companies can be incorporated as an evaluation criterion.
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