Shape reconstruction of multiple cracks from ECT signals by means of a stochastic method

M. Rebican;  Zhenmao Chen; N. Yusa; L. Janousek; K. Miya

doi:10.1109/tmag.2006.870967

Shape reconstruction of multiple cracks from ECT signals by means of a stochastic method

IEEE Transactions on Magnetics ◽

10.1109/tmag.2006.870967 ◽

2006 ◽

Vol 42 (4) ◽

pp. 1079-1082 ◽

Cited By ~ 33

Author(s):

M. Rebican ◽

Zhenmao Chen ◽

N. Yusa ◽

L. Janousek ◽

K. Miya

Keyword(s):

Shape Reconstruction ◽

Stochastic Method ◽

Multiple Cracks

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Digital modulation classification using constellation shape reconstruction

Future Communication Technology ◽

10.2495/icct130651 ◽

2014 ◽

Author(s):

Gangcan Sun ◽

Pingping Li ◽

Zhongyong Wang

Keyword(s):

Shape Reconstruction ◽

Modulation Classification ◽

Digital Modulation ◽

Digital Modulation Classification

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IDENTIFICATION OF WIEBE AND WOSCHNI PARAMETERS USING STOCHASTIC METHOD OF DIFFERENTIAL EVOLUTION

10.26678/abcm.encit2020.cit20-0563 ◽

2020 ◽

Author(s):

Lucas Peixoto ◽

Stephan Hennings Och ◽

Carlos augusto Henning Laurindo ◽

Paulo Philippi ◽

Luís Mauro Moura

Keyword(s):

Differential Evolution ◽

Stochastic Method

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An Adaptive ANOVA-Based Data-Driven Stochastic Method for Elliptic PDE with Random Coefficients

10.21236/ada560090 ◽

2012 ◽

Cited By ~ 1

Author(s):

Xin Hu ◽

Guang Lin ◽

Thomas Y. Hou ◽

Pengchong Yan

Keyword(s):

Random Coefficients ◽

Stochastic Method ◽

Data Driven ◽

Elliptic Pde

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Quantification of Multiple Cracks Using MM-wave Antenna Sensor Network

10.21236/ada563782 ◽

2011 ◽

Cited By ~ 1

Author(s):

Haiying Huang

Keyword(s):

Sensor Network ◽

Multiple Cracks ◽

Wave Antenna

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Nappes d'huile: prediction de leurs deplacements comme agent efficace d'un plan de mesure d'urgence

Water Quality Research Journal ◽

10.2166/wqrj.1979.008 ◽

1979 ◽

Vol 14 (1) ◽

pp. 89-109

Author(s):

B. Coupal ◽

M. de Broissia

Keyword(s):

Monte Carlo ◽

Markov Chain ◽

Finite Elements ◽

Mass Balance ◽

Stochastic Method ◽

Stochastic Methods ◽

Deterministic Approach ◽

First Order ◽

The Third ◽

Comme Agent

Abstract The movement of oil slicks on open waters has been predicted, using both deterministic and stochastic methods. The first method, named slick rose, consists in locating an area specifying the position of the slick during the first hours after the spill. The second method combines a deterministic approach for the simulation of current parameters to a stochastic method simulating the wind parameters. A Markov chain of the first order followed by a Monte Carlo approach enables the simulation of both phenomena. The third method presented in this paper describes a mass balance on the spilt oil, solved by the method of finite elements. The three methods are complementary to each other and constitute an important point for a contingency plan.

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