GNU Fuzzy

Neural networks and fuzzy systems are both part of what we call soft computing or computational intelligence. Both approaches can be applied to similar classes of problems. Although fuzzy approaches have been successful in control applications in the 1990s this success has not noticeably spread to other domains. Neural networks in contrast enjoy a more steady and widespread commercial success be it in credit card fraud detection or as modules in almost every large data mining software system. Fuzzy systems have not yet enjoyed widespread success in the domain of business applications. It seems software vendors lack incentive for implementing fuzzy software because the benefits have not been made clear by the research community and because fuzzy software is more difficult to implement and use than, for example, neural networks. In order for fuzzy systems to succeed in business applications I suggest to look into building a fuzzy tool kit in a community process to provide an open source reference implementation. This paper looks at some of the key considerations that are important for building a fuzzy tool kit that can support the take-up of fuzzy systems in business applications.