Neuro-fuzzy systems (NFS) combine two artificial intelligence (AI) techniques, namely neural networks and fuzzy logic systems. This approach takes advantage of the strengths of each technique, while simultaneously overcoming their respective limitations. The combination has enabled NFS to be deployed in many business applications for well over a decade.

This paper provides a detailed review of the application of NFS in a number of business application domains between 2005 and 2015. The authors reviewed many research articles from reputable journals for that time period where NFS was used to address a particular business problem. The business functions covered in this paper include: finance, marketing and distribution, human resource management (HRM), production and operations, business planning (that is, strategic planning), and information systems.

“Production and operations was the dominant application area” with a number of uses, including “control, fault detection and diagnosis, scheduling, [and] supervision.” Finance as well as marketing and distribution were heavy users of NFS, while HRM came in dead last with few uses.

Readers who may want to apply AI to one of the business areas covered can gain a very good sense of whether or not NFS may be appropriate for their particular business problem. Moreover, the paper provides many references for readers who are interested.