Corpus ID: 698434

AN INTELLIGENT FUZZY INFERENCE MODEL FOR CUSTOMER REQUIREMENTS MANAGEMENT

@inproceedings{Fung2002ANIF,
  title={AN INTELLIGENT FUZZY INFERENCE MODEL FOR CUSTOMER REQUIREMENTS MANAGEMENT},
  author={Richard Y. K. Fung and Jiafu Tang},
  year={2002}
}
Being able to capture, understand and respond to the needs and wants of the customers is essential to the survival and prosperity of an organisation. Some of the well known contemporary techniques and methodologies for analysing and processing the customer attributes and projecting the relevant product specifications. This paper begins with an overview of the essential roles, the changing emphasis and the dynamic characteristics of the contemporary customer demand with a view to promoting a… Expand
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References

SHOWING 1-9 OF 9 REFERENCES
Outline of a New Approach to the Analysis of Complex Systems and Decision Processes
  • L. Zadeh
  • Computer Science
  • IEEE Trans. Syst. Man Cybern.
  • 1973
TLDR
By relying on the use of linguistic variables and fuzzy algorithms, the approach provides an approximate and yet effective means of describing the behavior of systems which are too complex or too ill-defined to admit of precise mathematical analysis. Expand
The Analytic Hierarchy Process
The Analytic Hierarchy Process (AHP), introduced by Thomas Saaty (1980), is an effective tool for dealing with complex decision making, and may aid the decision maker to set priorities and make theExpand
House of Quality
Fundamentals of decision making and priority theory
The Fuzzzy Systems Handbook: a practitioner's guide to building, using, and maintaining fizzy systems
  • AP Professional
  • 1994
An introduction to Quality Function Deployment
  • Akao
  • 1990
Policy Management through Quality Function Deployment
  • Quality Progress
  • 1988
a practitioner's guide to building, using, and maintaining fizzy systems
  • AP Professional, Cambridge, MA, U.S.A. Lotfi A. Zadeh (196.5) Fuzzy Sets, Information and Control. New York, Academic Press 8, 338-3.53. Lotfi A. Zadeh
  • 1973
5) Fuzzy Sets, Information and Control
  • 5) Fuzzy Sets, Information and Control