Advanced search
Add to list

Using parametric functions to solve systems of linear fuzzy equations: an improved algorithm

Author
Organization
Abstract
Buckley and Qu proposed a method to solve systems of linear fuzzy equations. Basically, in their method the solutions of all systems of linear crisp equations formed by the a-levels are calculated. We proposed a new method for solving systems of linear fuzzy equations based on a practical algorithm using parametric functions in which the variables are given by the fuzzy coefficients of the system. By observing the monotonicity of the parametric functions in each variable, i.e. each fuzzy coefficient in the system, we improve the algorithm by calculating less parametric functions and less evaluations of these parametric functions. We show that our algorithm is much more efficient than the method of Buckley and Qu.
Keywords
systems of fuzzy linear equations, fuzzy numbers

Citation

Please use this url to cite or link to this publication:

MLA
Vroman, Annelies, et al. “Using Parametric Functions to Solve Systems of Linear Fuzzy Equations: An Improved Algorithm.” Applied Artificial Intelligence, edited by Da Ruan et al., World Scientific, 2006, pp. 43–50.
APA
Vroman, A., Deschrijver, G., & Kerre, E. (2006). Using parametric functions to solve systems of linear fuzzy equations: an improved algorithm. In D. Ruan, P. D’Hondt, P. F. Fantoni, M. De Cock, M. Nachtegael, & E. Kerre (Eds.), Applied Artificial Intelligence (pp. 43–50). Singapore, Singapore: World Scientific.
Chicago author-date
Vroman, Annelies, Glad Deschrijver, and Etienne Kerre. 2006. “Using Parametric Functions to Solve Systems of Linear Fuzzy Equations: An Improved Algorithm.” In Applied Artificial Intelligence, edited by Da Ruan, Pierre D’Hondt, Paolo F Fantoni, Martine De Cock, Mike Nachtegael, and Etienne Kerre, 43–50. Singapore, Singapore: World Scientific.
Chicago author-date (all authors)
Vroman, Annelies, Glad Deschrijver, and Etienne Kerre. 2006. “Using Parametric Functions to Solve Systems of Linear Fuzzy Equations: An Improved Algorithm.” In Applied Artificial Intelligence, ed by. Da Ruan, Pierre D’Hondt, Paolo F Fantoni, Martine De Cock, Mike Nachtegael, and Etienne Kerre, 43–50. Singapore, Singapore: World Scientific.
Vancouver
1.
Vroman A, Deschrijver G, Kerre E. Using parametric functions to solve systems of linear fuzzy equations: an improved algorithm. In: Ruan D, D’Hondt P, Fantoni PF, De Cock M, Nachtegael M, Kerre E, editors. Applied Artificial Intelligence. Singapore, Singapore: World Scientific; 2006. p. 43–50.
IEEE
[1]
A. Vroman, G. Deschrijver, and E. Kerre, “Using parametric functions to solve systems of linear fuzzy equations: an improved algorithm,” in Applied Artificial Intelligence, Genoa, Italy, 2006, pp. 43–50.
@inproceedings{406214,
  abstract     = {{Buckley and Qu proposed a method to solve systems of linear fuzzy equations. Basically, in their method the solutions of all systems of linear crisp equations formed by the a-levels are calculated. We proposed a new method for solving systems of linear fuzzy equations based on a practical algorithm using parametric functions in which the variables are given by the fuzzy coefficients of the system. By observing the monotonicity of the parametric functions in each variable, i.e. each fuzzy coefficient in the system, we improve the algorithm by calculating less parametric functions and less evaluations of these parametric functions. We show that our algorithm is much more efficient than the method of Buckley and Qu.}},
  author       = {{Vroman, Annelies and Deschrijver, Glad and Kerre, Etienne}},
  booktitle    = {{Applied Artificial Intelligence}},
  editor       = {{Ruan, Da and D'Hondt, Pierre and Fantoni, Paolo F and De Cock, Martine and Nachtegael, Mike and Kerre, Etienne}},
  isbn         = {{9789812566904}},
  keywords     = {{systems of fuzzy linear equations,fuzzy numbers}},
  language     = {{eng}},
  location     = {{Genoa, Italy}},
  pages        = {{43--50}},
  publisher    = {{World Scientific}},
  title        = {{Using parametric functions to solve systems of linear fuzzy equations: an improved algorithm}},
  year         = {{2006}},
}

Web of Science
Times cited: