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Original Articles

MEASUREMENT OF POSSIBILISTIC HISTOGRAMS FROM INTERVAL DATA

Pages 9-33 | Received 26 Jan 1996, Published online: 25 Jun 2007

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LUISM. DE CAMPOS & JUANF. HUETE. (2001) MEASUREMENT OF POSSIBILITY DISTRIBUTIONS. International Journal of General Systems 30:3, pages 309-346.
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Articles from other publishers (24)

Didier Dubois & Henri Prade. 2023. Granular, Fuzzy, and Soft Computing. Granular, Fuzzy, and Soft Computing 859 876 .
Angela Blanco-Fernández & Peter Winker. (2016) Data generation processes and statistical management of interval data. AStA Advances in Statistical Analysis 100:4, pages 475-494.
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Didier Dubois & Henri Prade. (2016) Practical Methods for Constructing Possibility Distributions. International Journal of Intelligent Systems 31:3, pages 215-239.
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Didier Dubois & Henry Prade. 2015. Springer Handbook of Computational Intelligence. Springer Handbook of Computational Intelligence 31 60 .
Didier Dubois & Henri Prade. 2014. Encyclopedia of Complexity and Systems Science. Encyclopedia of Complexity and Systems Science 1 20 .
Li-Ping He, Hong-zhong Huang, Shunpeng Zhu & Dan Ling. (2013) Uncertainty quantification in fatigue lifetime data analysis: a possibilistic approach. Uncertainty quantification in fatigue lifetime data analysis: a possibilistic approach.
Didier Dubois & Henri Prade. 2012. Computational Complexity. Computational Complexity 2240 2252 .
Liping He, Hong-Zhong Huang, Yu Pang, Yu Liu & Zhonglai Wang. (2011) Development of possibility distributions for fatigue lifetime data analysis. Development of possibility distributions for fatigue lifetime data analysis.
Timothy J. Ross. 2010. Fuzzy Logic with Engineering Applications. Fuzzy Logic with Engineering Applications 530 578 .
Didier Dubois & Henri Prade. 2009. Encyclopedia of Complexity and Systems Science. Encyclopedia of Complexity and Systems Science 6927 6939 .
E. AltunokM. M. Reda TahaT. J. Ross. (2007) Possibilistic Approach for Damage Detection in Structural Health Monitoring. Journal of Structural Engineering 133:9, pages 1247-1256.
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Didier Dubois. (2006) Possibility theory and statistical reasoning. Computational Statistics & Data Analysis 51:1, pages 47-69.
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Didier Dubois & Henri Prade. 2006. Decision Theory and Multi-Agent Planning. Decision Theory and Multi-Agent Planning 89 109 .
T.T. Shannon. (2005) Blind Source Separation with Possibilistic Variables. Blind Source Separation with Possibilistic Variables.
Scott Ferson, Cliff A. Joslyn, Jon C. Helton, William L. Oberkampf & Kari Sentz. (2004) Summary from the epistemic uncertainty workshop: consensus amid diversity. Reliability Engineering & System Safety 85:1-3, pages 355-369.
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Jane M Booker & Laura A McNamara. (2004) Solving black box computation problems using expert knowledge theory and methods. Reliability Engineering & System Safety 85:1-3, pages 331-340.
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C. Joslyn. (2003) Multi-interval elicitation of random intervals for engineering reliability analysis. Multi-interval elicitation of random intervals for engineering reliability analysis.
D. Dubois & H. Prade. (2003) Possibility theory and its applications: a retrospective and prospective view. Possibility theory and its applications: a retrospective and prospective view.
C. Joslyn & J.C. Helton. (2002) Bounds on belief and plausibility of functionally propagated random sets. Bounds on belief and plausibility of functionally propagated random sets.
Didier Dubois & Henri Prade. 2002. Soft Methods in Probability, Statistics and Data Analysis. Soft Methods in Probability, Statistics and Data Analysis 3 26 .
C. Joslyn. (2001) Measures of distortion in possibilistic approximations of consistent random sets and intervals. Measures of distortion in possibilistic approximations of consistent random sets and intervals.
Luis M. Campos & Juan F. Huete. 2000. Information, Uncertainty and Fusion. Information, Uncertainty and Fusion 233 244 .
Didier Dubois, Hung T. Nguyen & Henri Prade. 2000. Fundamentals of Fuzzy Sets. Fundamentals of Fuzzy Sets 343 438 .
Bilal M. Ayyub & Madan M. GuptaCliff Joslyn. 1998. Uncertainty Analysis in Engineering and Sciences: Fuzzy Logic, Statistics, and Neural Network Approach. Uncertainty Analysis in Engineering and Sciences: Fuzzy Logic, Statistics, and Neural Network Approach 37 51 .

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