The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Dalam makalah ini, algoritma genetik digunakan untuk menentukan bentuk silinder pengalir yang tertanam dalam separuh ruang. Andaikan bahawa silinder pengalir bentuk yang tidak diketahui tertimbus dalam satu setengah ruang dan menyerakkan insiden medan dari separuh ruang lain di mana fail berselerak diukur. Berdasarkan keadaan sempadan dan medan berselerak yang diukur, satu set persamaan kamiran tak linear diterbitkan dan masalah pengimejan dirumus semula menjadi masalah pengoptimuman. Algoritma genetik kemudiannya digunakan untuk mengetahui penyelesaian ekstrem hampir global bagi fungsi objek supaya bentuk penyerakan konduktif boleh dibina semula dengan sesuai. Dalam kajian kami, walaupun apabila tekaan awal jauh daripada yang tepat, algoritma genetik boleh mengelakkan keterlaluan tempatan dan menumpu kepada penyelesaian yang agak baik. Dalam kes sedemikian, kaedah berasaskan kecerunan sering terperangkap dalam keterlaluan tempatan. Keputusan berangka dibentangkan dan pembinaan semula yang baik diperoleh dengan dan tanpa bunyi Gaussian aditif.
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Salinan
Chien-Ching CHIU, Ching-Lieh LI, Wei CHAN, "Image Reconstruction of a Buried Conductor by the Genetic Algorithm" in IEICE TRANSACTIONS on Electronics,
vol. E84-C, no. 12, pp. 1946-1951, December 2001, doi: .
Abstract: In this paper, genetic algorithms is employed to determine the shape of a conducting cylinder buried in a half-space. Assume that a conducting cylinder of unknown shape is buried in one half-space and scatters the field incident from another half-space where the scattered filed is measured. Based on the boundary condition and the measured scattered field, a set of nonlinear integral equations is derived and the imaging problem is reformulated into an optimization problem. The genetic algorithm is then employed to find out the nearly global extreme solution of the object function such that the shape of the conducting scatterer can be suitably reconstructed. In our study, even when the initial guess is far away from the exact one, the genetic algorithm can avoid the local extremes and converge to a reasonably good solution. In such cases, the gradient-based methods often get stuck in local extremes. Numerical results are presented and good reconstruction is obtained both with and without the additive Gaussian noise.
URL: https://global.ieice.org/en_transactions/electronics/10.1587/e84-c_12_1946/_p
Salinan
@ARTICLE{e84-c_12_1946,
author={Chien-Ching CHIU, Ching-Lieh LI, Wei CHAN, },
journal={IEICE TRANSACTIONS on Electronics},
title={Image Reconstruction of a Buried Conductor by the Genetic Algorithm},
year={2001},
volume={E84-C},
number={12},
pages={1946-1951},
abstract={In this paper, genetic algorithms is employed to determine the shape of a conducting cylinder buried in a half-space. Assume that a conducting cylinder of unknown shape is buried in one half-space and scatters the field incident from another half-space where the scattered filed is measured. Based on the boundary condition and the measured scattered field, a set of nonlinear integral equations is derived and the imaging problem is reformulated into an optimization problem. The genetic algorithm is then employed to find out the nearly global extreme solution of the object function such that the shape of the conducting scatterer can be suitably reconstructed. In our study, even when the initial guess is far away from the exact one, the genetic algorithm can avoid the local extremes and converge to a reasonably good solution. In such cases, the gradient-based methods often get stuck in local extremes. Numerical results are presented and good reconstruction is obtained both with and without the additive Gaussian noise.},
keywords={},
doi={},
ISSN={},
month={December},}
Salinan
TY - JOUR
TI - Image Reconstruction of a Buried Conductor by the Genetic Algorithm
T2 - IEICE TRANSACTIONS on Electronics
SP - 1946
EP - 1951
AU - Chien-Ching CHIU
AU - Ching-Lieh LI
AU - Wei CHAN
PY - 2001
DO -
JO - IEICE TRANSACTIONS on Electronics
SN -
VL - E84-C
IS - 12
JA - IEICE TRANSACTIONS on Electronics
Y1 - December 2001
AB - In this paper, genetic algorithms is employed to determine the shape of a conducting cylinder buried in a half-space. Assume that a conducting cylinder of unknown shape is buried in one half-space and scatters the field incident from another half-space where the scattered filed is measured. Based on the boundary condition and the measured scattered field, a set of nonlinear integral equations is derived and the imaging problem is reformulated into an optimization problem. The genetic algorithm is then employed to find out the nearly global extreme solution of the object function such that the shape of the conducting scatterer can be suitably reconstructed. In our study, even when the initial guess is far away from the exact one, the genetic algorithm can avoid the local extremes and converge to a reasonably good solution. In such cases, the gradient-based methods often get stuck in local extremes. Numerical results are presented and good reconstruction is obtained both with and without the additive Gaussian noise.
ER -