A NEURAL FUZZY NETWORK FOR CUSTOMER REQUIREMENTS
When developing new products it is very important for design teams to understand customer requirements, because the success of products is dependent of customer satisfaction level. The chance of new product’s success in a marketplace is higher if the customer is satisfied with it. Usually, the customer requirements are confused, contradictory or incomplete, because they are expressed using linguistic terms. In this paper we make a study, using the fuzzy analytic hierarchy process to determine the weights for customer requirements, and use this information as input in a neural fuzzy network for obtain alternatives the most appropriate to customer requirements.Key words: fuzzy network, customer level
S., Abe, Neural Networks and Fuzzy Systems, Kluwer Academic Publishers, (1997).
G., Bojadziev, Fuzzy Logic for Business, Finance and Management, World Scientific Publishing Company, (2007).
N., Dzamashvili, Understanding and supporting requirements engineering decision in market-driven software product development, Blekinge Institute of Technology, (2010).
S., Tzafestas, Fuzzy Logic and neural network handbook, Ed C.H,. (2000).
L., Zadeh., Fuzzy sets, Information and control, (1965).
L.,Zadeh, Fuzzy logic, IEEE Computer vol 21, (1988).
- There are currently no refbacks.