Constructing membership functions using statistical data
Fuzzy Sets and Systems
The Max-Min Delphi method and fuzzy Delphi method via fuzzy integration
Fuzzy Sets and Systems
Constructing membership functions using interpolation and measurement theory
Fuzzy Sets and Systems
An efficient approach for large scale project planning based on fuzzy Delphi method
Fuzzy Sets and Systems
An Algorithm for Computing a Shape-Preserving Osculatory Quadratic Spline
ACM Transactions on Mathematical Software (TOMS)
Algorithm 574: Shape-Preserving Osculatory Quadratic Splines [E1, E2]
ACM Transactions on Mathematical Software (TOMS)
Scalar- and planar-valued curve fitting using splines under tension
Communications of the ACM
Fuzzy Sets and Systems: Theory and Applications
Fuzzy Sets and Systems: Theory and Applications
Fuzzy Mathematical Models in Engineering and Management Science
Fuzzy Mathematical Models in Engineering and Management Science
Expert Systems with Applications: An International Journal
Fuzzy Delphi and back-propagation model for sales forecasting in PCB industry
Expert Systems with Applications: An International Journal
The construction of a comprehensive model for production strategy evaluation
Fuzzy Optimization and Decision Making
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Fuzzy back-propagation network for PCB sales forecasting
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part I
How to handle uncertainties in AHP: The Cloud Delphi hierarchical analysis
Information Sciences: an International Journal
An integrated decision making model for district revitalization and regeneration project selection
Decision Support Systems
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A new fuzzy Delphi method is proposed. The method employs the fuzzy statistics and technique of the conjugate gradient search to fit membership functions. Membership functions besides triangles may be derived for the fuzzy forecasts. A procedure termed as stabilization rather than convergence of the iterative interval-valued surveys is utilized, in which the @a-level set of the fuzzy forecasts is used. The testing of stability of the process is conducted on the fuzzy forecasts between two consecutive iterations instead of within each iteration. An application of this method to the problem of managerial talent assessment for a company located in Taiwan and the obtained results are provided.