Abstract
In this paper, we demonstrate that the fuzziness of fuzzy information can come not only from the measuring scale, but also from the incompleteness of sample knowledge. Fundamentally, by developing the method of information distribution to information diffusion principle, we establish the embryonic form of the theory of fuzzy information optimization processing, which is connected with incompleteness. An application in fuzzy neuron to estimate earthquake intensity shows that information diffusion methods have obvious advantages and future applications.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
L.A. Zadeh, “Fuzzy sets,” Information and Control 8 (1965), 338–353.
L. A. Zadeh, “Fuzzy sets as a basis for a theory of possibility,” Fuzzy Sets and Systems 1 (1978), 3–28.
L.A. Zadeh, “Syllogistic reasoning in fuzzy logic and its application to usuality and reasoning with dispositions,” IEEE Trans. Systems, Man and Cybernetics SMC-15 (1985), 754–763.
A. Kaufmann, An Introduction to the Theory of Fuzzy Sets, Academic Press, New York (1975).
D. Dubois and H. Prade, Fuzzy Sets and Systems: Theory and Applications, Academic Press, New York (1980).
H.-J. Zimmermann, “Fuzzy programming and linear programming with several objective functions,” Fuzzy Sets and Systems 1 (1978), 45–55.
E.H. Mamdani, “Application of fuzzy logic to approximate reasoning using linguistic synthesis,” Proceedings of the 6th International Symposium on Multiple-Valued Logic (1976), Utah, IEEE76 CH1111–4C, 196–202.
C.V. Negoita, “On the application of the fuzzy sets separation theorem for automatic classification in information retrieval systems,” Information Sciences 5 (1973), 279–286.
J. C. Bezdek and J. C. Dunn, “Optimal fuzzy partitions: a heuristic for estimating the parameters in a mixture of normal distributions,” IEEE Trans. Comp. 24(8) (1975), 835–838.
R. R. Yager, “Some procedures for selecting fuzzy-set-theoretic operators,” Int. J; General Systems 8 (1982), 115–124.
W. Bandler and L. Kohout, “Semantics of implication operators and fuzzy relation products,” Int. J. Man-Machine Studies 12 (1980), 89–116.
I.R. Goodman, “Fuzzy set as equivalent classes of random sets,” in: Recent Developments in Fuzzy Set and Possibility Theory (R.R. Yager, Ed.), Pergamon Press, New York (1982).
P.Z. Wang and E. Sanchez, “Treating a fuzzy subset as a project able random set,” in: Fuzzy Information and Decision (M. M. Gupta, E. Sanchez, Eds.), Pergamon Press (1982).
C. Huang and Z. Liu, Isoseismal Area Estimation of Yunnan Province by Fuzzy mathematics in Earthquake Researches, Seismological Press (1985).
Z. Liu, “Application of the information distribution concept to the estimation of earthquake intensity,” Analysis of Fuzzy Information Vol. III, CRC Press, USA (1987), 67–73.
Z. Liu and C. Huang, “Information distribution method relevant in fuzzy information analysis,” Fuzzy Sets and Systems 36 (1990), 67–76.
J. Wang, “Further study on the fuzzy mathematical method in evaluation of seismic liquefaction potential,” Proceedings of International Symposiums on Engineering Problems in Seismic Areas (1986), Italy, 47–56.
C. Huang, “Fuzzy information process in classic random statistics,” Fuzzy Systems and Mathematics 4(1) (1990), 8–15.
Z. Liu et al, “A fuzzy quantitative study on the effect of active fault distribution on isoseismal area in Yunnan,” J. of Seismology 87(1) (1987), 9–16.
X. Xiu and C. Huang, “Fuzzy identification between dynamic response of structure and structural earthquake damage,” Earthquake engineering and engineering vibration 9(2) (1989), 57–66.
Z. Wang, Probability Theory Basis and Applications, Science Press, (1976), 214–218.
X. Chen et al., Non-Parametric Statistics, Shanghai Science and Technology Press (1989), 284–292.
C. Huang, The Principle of Information Diffusion and Thought Computation and Their Applications in Earthquake Engineering, PhD Dissertation, Beijing Normal University (1993).
E. Parzen, “On estimation of a probability density function and mode,” Ann. Math Statist. 33 (1962), 1065–1076.
D.E. Rumelhart and J. L. McClelland, Parallel Distributed Processing: Explorations in the Microstructure of Cognition, Vols. 1 and 2, MIT Press, Cambridge, MA (1973).
Y. H. Pao, Adaptive Pattern Recognition and Neural Networks, Addison-Wesley Publishing Company, Inc. (1989).
P.Z. Wang, Fuzzy Sets and Falling Shadows of Random Sets, Beijing Normal University Press, Beijing (1985) (in Chinese).
C. Huang and Y. Fen, “Non-parameter estimation of management simulation input by fuzzy sets method,” J. of Beijing University of Aeronautics and Astronautics 20(3) (1994), 306–314 (in Chinese).
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1996 Kluwer Academic Publishers
About this chapter
Cite this chapter
Huang, C., Ruan, D. (1996). Information Diffusion Principle and Application in Fuzzy Neuron. In: Ruan, D. (eds) Fuzzy Logic Foundations and Industrial Applications. International Series in Intelligent Technologies, vol 8. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-1441-7_9
Download citation
DOI: https://doi.org/10.1007/978-1-4613-1441-7_9
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4612-8627-1
Online ISBN: 978-1-4613-1441-7
eBook Packages: Springer Book Archive