Truncation Method for Chance Measure

Chun Qin Zhang; Yang Fang

doi:10.4028/www.scientific.net/AMM.457-458.974

Paper Titles

Design of Slope Deformation Monitoring System Based on WSN
p.953

A Design for Carrier Wave Catching to Micro-Dynamic Signal in USB/UCB
p.960

The Research and Design of Data Aggregation Technique in WSNs
p.965

Application of Local Wave Method in the Structural Health Monitoring Signal Decomposition
p.969

Truncation Method for Chance Measure
p.974

Comparison of Sewage Treatment Mixer in Three Pool Face Boundary Conditions
p.979

Research of User Experience and Data Mining for Stereo Vision
p.984

Study on Molecular Weight of Natural Rubber with Different Initial Moisture Contents Dried by Microwave
p.988

The New Fast Algorithm Based on Transposed Matrix for Frequent Sets Mining of Association Rule
p.992

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 457-458Truncation Method for Chance Measure

Truncation Method for Chance Measure

Abstract:

Chance measure is a non-additive measure. In this paper, we derive the truncation method for chance measure. This result is a natural extension of the classical truncation method to the case where the measure tool is non-additive. The properties of chance measure are further discussed. Then the truncation method will be given on chance space. This work generalizes the research and applications of the truncation method.

You might also be interested in these eBooks

Frontiers of Mechanical Engineering and Materials Engineering II

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 457-458)

Pages:

974-978

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.457-458.974

Citation:

Cite this paper

Online since:

October 2013

Authors:

Chun Qin Zhang, Yang Fang

Keywords:

Chance Measure, Converges with Chance Measure 1, Hybrid Variables, Truncation Method

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Sugeno M, Theory of fuzzy integrals and its applications. Tokyo: Tokyo Insitute of Technology, (1974).

Google Scholar

[2] Zadeh L A, Fuzzy sets as a basis for a theory of possibility, Fuzzy Sets and Systems, vol. 100, 1978, pp.3-28.

DOI: 10.1016/0165-0114(78)90029-5

Google Scholar

[3] Zadeh L A. A theory of approximate reasoning, in Mathematical Frontiers of the Social and Policy Sciences, vol. 2, J. Hayes, D. Michie and R. M. Thrall, eds. Boulder, Cororado: Westview Press, 1979, pp.207-213.

Google Scholar

[4] Wang Z Y and Klir G J, Fuzzy measure theory, New York: Plenum Press, 1992, pp.39-72.

Google Scholar

[5] Li X and Liu B, Chance measure for hybrid events with fuzziness and randomness, Soft Computing, vol. 13, 2009, pp.105-115.

DOI: 10.1007/s00500-008-0308-x

Google Scholar

[6] Liang Z S and Deng J X, Probability Theory and Mathematical Statistics, Beijing: Advanced Education Press, 1988, pp.1-63.

Google Scholar

[7] Liu B D and Liu Y K, Expected value of fuzzy variable and fuzzy expected value models, IEEE Transactions of Fuzzy Systems, vol. 10, 2002, pp.445-450.

DOI: 10.1109/tfuzz.2002.800692

Google Scholar

[8] Liu B D, Uncertainty Theory, 3rd ed. Beijing: Uncertainty Theory Laboratory, 2009, pp.211-238.

Google Scholar

[9] Liu B D, Random fuzzy dependent-chance programming and its hybrid intelligent algorithm, Information Sciences, vol. 141, 2002, pp.259-271.

DOI: 10.1016/s0020-0255(02)00176-7

Google Scholar

[10] Liu Y K and Liu B D, Random fuzzy programming with chance measure defined by fuzzy integrals, Mathematical and computer modeling, vol. 36, 2002, pp.509-524.

DOI: 10.1016/s0895-7177(02)00180-2

Google Scholar

[11] Li X and Liu B D, Hybrid logic and uncertain logic, Journal of Uncertain Systems, vol. 3, 2009, pp.83-94.

Google Scholar

[12] Ren C G, Hu S H and Li X, Some improvements to an extended Borel strong law of large numbers, Journal of Anhui University (Natural Science Edition), vol. 35, 2011, pp.25-28.

Google Scholar

[13] Yuan D M, The truncaton of random variables35 and a strong deviation theorem, Journal of Mathematics, vol. 23, 2003, pp.349-353.

Google Scholar