کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
499908 863065 2007 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
The use of neural network approximation models to speed up the optimisation process in electrical impedance tomography
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
پیش نمایش صفحه اول مقاله
The use of neural network approximation models to speed up the optimisation process in electrical impedance tomography
چکیده انگلیسی

A reduced approximation model technique based on neural networks is developed in order to increase the rate of convergence of an evolution strategy (ES) used for solving a non-destructive evaluation problem. The inverse problem investigated consists of identifying the geometry of discontinuities in a conductive material from Cauchy data measurements taken on the boundary. In this study, we use neural network (NN) approximation models in order to increase the rate of convergence of the optimisation algorithm and to efficiently detect, from a computational time point of view a subsurface cavity, such as a circle. The algorithm developed by combining evolution strategies and neural networks is found to be a robust, fast and efficient method for detecting the size and location of subsurface cavities.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computer Methods in Applied Mechanics and Engineering - Volume 197, Issues 1–4, 1 December 2007, Pages 103–114
نویسندگان
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