Imposing restrictions on density functions utilised in computing with words
Gemeinder, Marcus
International Journal of Applied Mathematics and Computer Science, Tome 12 (2002), p. 383-390 / Harvested from The Polish Digital Mathematics Library

Applying the generalised extension principle within the area of Computing with Words typically leads to complex maximisation problems. If distributed quantities-such as, e.g., size distributions within human populations-are considered, density functions representing these distributions become involved. Very often the optimising density functions do not resemble those found in nature; for instance, an optimising density function could consist of two single Dirac pulses positioned near the opposite bounds of the interval limiting the possible values of the quantity considered. Therefore, in this article, density functions with certain shapes which enable us to overcome this lack of resemblance are considered. Furthermore, some considerations on solving the resulting maximisation problems are reported.

Publié le : 2002-01-01
EUDML-ID : urn:eudml:doc:207595
@article{bwmeta1.element.bwnjournal-article-amcv12i3p383bwm,
     author = {Gemeinder, Marcus},
     title = {Imposing restrictions on density functions utilised in computing with words},
     journal = {International Journal of Applied Mathematics and Computer Science},
     volume = {12},
     year = {2002},
     pages = {383-390},
     zbl = {1062.68124},
     language = {en},
     url = {http://dml.mathdoc.fr/item/bwmeta1.element.bwnjournal-article-amcv12i3p383bwm}
}
Gemeinder, Marcus. Imposing restrictions on density functions utilised in computing with words. International Journal of Applied Mathematics and Computer Science, Tome 12 (2002) pp. 383-390. http://gdmltest.u-ga.fr/item/bwmeta1.element.bwnjournal-article-amcv12i3p383bwm/

[000] Baker J. E. (1987): Reducing bias and inefficiency in the selection algorithm, In: Genetic Algorithms and their Applications: Proceedings of the 2nd International Conference on Genetic Algorithms (J. J. Grefenstette, Ed.). - Hillsdale, N.J.: Lawrence Erlbaum Associates, Inc., Publishers.

[001] Gemeinder M. (2000): Fuzzy constraint propagation with evolutionary algorithms. - Proc. East West Fuzzy Colloquium, HS Zittau Gorlitz, Germany, pp. 196-203.

[002] Gemeinder M. (2001a): Restricted density functions for approximate reasoning on distributed quantities. - Proc. 9th Zittau Fuzzy Colloquium, HS ZittauGorlitz, Germany, pp. 29-35.

[003] Gemeinder M. (2001B): Computing with words: Multi-objective GAs for approximate reasoning, In: Computational Intelligence, Theory and Applications, Proc. 7th Fuzzy Days, LNCS 2206 (B. Reusch, Ed.) - Berlin: Springer Verlag. | Zbl 1043.68703

[004] Hermann M. (2001): Numerische Mathematik. - Munchen: Oldenbourg Wissenschaftsverlag.

[005] Nissen V. (1997): Einfuhrung in evolutionare Algorithmen: Optimierung nach dem Vorbild der Evolution. -Braunschweig Wiesbaden: Vieweg.

[006] Pohlheim H. (1999): Evolutionare Algorithmen: Verfahren, Operatoren und Hinweise fur die Praxis. - Berlin: Springer Verlag.

[007] Pozrikidis C. (1998): Numerical Computation in Science and Engineering. - Oxford: Oxford University Press, Inc. | Zbl 0971.65001

[008] Zadeh L. A. (1979): A theory of approximate reasoning. -Machine Intell., Vol. 9, pp. 149-194.

[009] Zadeh L. A. (1999): From computing with numbers to computing with words - From manipulation of measurements to manipulation of perceptions. - IEEE Trans. Circ. Syst., Vol. 45, No. 1, pp. 105-119. | Zbl 0954.68513

[010] Zadeh L. A. (2001a): The Robert Example. - BISC Mailing-list, March 2001.

[011] Zadeh L. A. (2001b): A new direction in AI - Towards a computational theory of perceptions. - 7th Fuzzy Days in Dortmund, Germany, Invited Lecture.