Modeling of reliability with possibility theory

Delmotte, François; Borne, Pierre

doi:10.1109/3468.650324

Cited by 38 publications

(19 citation statements)

References 10 publications

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“…Delmotte [28] defines some criteria to determine automatically according to a cost function. The second difficulty lies in the practical computation of the output: the apparent combinational explosion can be reduced, in some particular cases, as follows.…”

Section: ) Adaptive Quantified Fusion (Aq)mentioning

confidence: 99%

Fuzzy fusion techniques for linear features detection in multitemporal SAR images

Chanussot¹,

Mauris²,

Lambert³

1999

IEEE Trans. Geosci. Remote Sensing

144

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Abstract-This paper is concerned with the automatic detection of linear features in SAR satellite data, with application to road network extraction. After a directional prefiltering step, a morphological line detector is presented. To improve the detection performances, the results obtained on multitemporal data are fused. Different fusion strategies involving different fusion operators are then presented. Since extensions of classical set union and intersection do not lead to satisfactory results (the corresponding operators are either too indulgent or too severe), the first strategy consists of fusing the data using a compromise operator. The second strategy consists of fusing the results computed with two operators that have opposite properties, in order to obtain a final intermediate result. Thanks to the wide range of properties they provide, fuzzy operators are used to test and compare these two fusion strategies on real ERS-1 multitemporal data.

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Section: ) Adaptive Quantified Fusion (Aq)mentioning

confidence: 99%

Fuzzy fusion techniques for linear features detection in multitemporal SAR images

Chanussot¹,

Mauris²,

Lambert³

1999

IEEE Trans. Geosci. Remote Sensing

144

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“…For instance, new attributes extracted by image processing operators could be used to define more new discriminant contrasts. A key point is the development of fusion techniques [6], [7], [9]: Fusion of different detectors or different contrasts, but also fusion of the detection results obtained from several recurrences [13]. In [19], we have proposed a new method to remove reverberation echoes issued from the sea bottom.…”

Section: Discussionmentioning

confidence: 99%

Morphological and Statistical Approaches to Improve Detection in the Presence of Reverberation

Ginolhac¹,

Chanussot²,

Hory³

2005

IEEE J. Oceanic Eng.

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Abstract-The detection of a target echo in a sonar image is usually a difficult task since the reverberation, consisting of a large number of spurious echoes, generates a lot of false alarms. In this paper, we propose two new detectors derived from image processing algorithms. These detectors are respectively based on a morphological and a statistical contrast. Each detector only requires setting a few parameters. This setting is done using some prior knowledge about the data (shape of the emitted signal and the used antenna, characteristics of the reverberation). Nevertheless, an extensive statistical study of the detection performances proves that the proposed methods are robust and that even an imprecise setting of the parameters leads to satisfactory results. Applied to the real data, these detectors and their sequential combination lead to a significant improvement on the performances: The false alarm rate is drastically reduced while the detection probability is preserved. Based on different contrasts, these detectors have complementary behaviors. Therefore, a further improvement is achieved by a fusion of the different results to classify the remaining echoes as whether spurious or true detection.

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“…The first adoption of fuzzy methodology in reliability and failure analysis, i.e., the proposed notion of component possibility as a reliability index, may be dated back to Kaufman's study (Kaufmann, 1983), although the motivation and exact meaning of component possibility were not explained at that time and now fuzzy-based approaches are appearing in various areas of reliability evaluation (Bai and Asgarpoor, 2004) and modeling (Delmotte and Borne, 1998).…”

Section: Reliabilitymentioning

confidence: 99%

“…In the area of reliability engineering, reliability estimation and design are investigated by (Mourelatos and Zhou, 2004), Kozine and Filimonov (2000); Moller et al (1999;Huang (1995;; Huang et al (2006a;; Huang (2012); Li et al (2012); Pang et al (2012); Wang et al (2011;2012) and Xiao et al (2012). Modeling of reliability using a new data fusion rule is proposed by Delmotte and Borne (1998); Sun et al (2008) and Yang et al (2011a); Possibility-based design optimization is studied and developed by (Mourelatos and Zhou, 2004;Youn, 2005;Youn and Choi, 2004a;Youn et al, 2004;Choi et al, 2004;2012b;Zhang et al, 2010b). Fuzzy reliability theory in the context of possibility theory is proposed and developed by (Cai et al, 1991a;1991b;1993;Utkin and Gurov, 1996;Onisawa, 1988;Huang et al, 2004;.…”

Section: General Topics Of Applicationsmentioning

confidence: 99%

“…As a more general tool for uncertainty analysis, evidence theory has also been applied to many areas, including artificial intelligence (particularly in the development of expert systems) (Bae et al, 2004b;Nikolaidis and Haftka, 2001), object detection and approximate reasoning (Lowrance et al, 1986;Perrin et al, 2004;Xu and Smets, 1996;Borotschnig et al, 1999), design optimization (Mourelatos and Zhou, 2005), multidisciplinary design optimization (Agarwal et al, 2004), uncertainty quantification (Bae et al, 2004a;, risk and reliability evaluation (Yang et al, 2011b), remote sensing classification (Lee et al, 1987), pattern recognition and image analysis, decision making (Buckley, 1988;Limbourg, 2005), data fusion (Delmotte and Borne, 1998;Hall and Llinas, 1997;Sun et al, 2008;Yang et al, 2011a) and fault diagnosis (Fan and Zuo, 2006a;Wu et al, 1990). The popularity of evidence theory has risen, however, because evidence theory requires epistemological assumptions that are at odds with those underlying classical and Bayesian probability theories (Fioretti, 2004).…”

Section: General Topics Of Applicationsmentioning

confidence: 99%

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Possibility and Evidence-Based Reliability Analysis and Design Optimization

Huang

Liu

et al. 2013

American Journal of Engineering and Applied Sciences

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Engineering design under uncertainty has gained considerable attention in recent years. A great multitude of new design optimization methodologies and reliability analysis approaches are put forth with the aim of accommodating various uncertainties. Uncertainties in practical engineering applications are commonly classified into two categories, i.e., aleatory uncertainty and epistemic uncertainty. Aleatory uncertainty arises because of unpredictable variation in the performance and processes of systems, it is irreducible even adding more data or knowledge. On the other hand, epistemic uncertainty stems from lack of knowledge of the system due to limited data, measurement limitations, or simplified approximations in modeling system behavior and it can be reduced by obtaining more data or knowledge. More specifically, aleatory uncertainty is naturally represented by a statistical distribution and its associated parameters can be characterized by sufficient data. If, however, the data is limited and can be quantified in a statistical sense, epistemic uncertainty can be considered as an alternative tool in such a situation. Of the several optional treatments for epistemic uncertainty, possibility theory and evidence theory have proved to be the most computationally efficient and stable for reliability analysis and engineering design optimization. This study first attempts to provide a better understanding of uncertainty in engineering design by giving a comprehensive overview of its classifications, theories and design considerations. Then a review is conducted of general topics such as the foundations and applications of possibility theory and evidence theory. This overview includes the most recent results from theoretical research, computational developments and performance improvement of possibility theory and evidence theory with an emphasis on revealing the capability and characteristics of quantifying uncertainty from different perspectives. Possibility and evidence theory-based reliability methods have many advantages for practical engineering when compared with traditional probability-based reliability methods. They can work well under limited data while the latter need large amounts of information, more than possible in engineering practice due to aleatory and epistemic uncertainties. The possible directions for future work are summarized.

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Modeling of reliability with possibility theory

Cited by 38 publications

References 10 publications

Fuzzy fusion techniques for linear features detection in multitemporal SAR images

Fuzzy fusion techniques for linear features detection in multitemporal SAR images

Morphological and Statistical Approaches to Improve Detection in the Presence of Reverberation

Possibility and Evidence-Based Reliability Analysis and Design Optimization

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