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A new simulation method based on artificial neural networks for a special class of nanomagnetic materials design

S. MOHORIANU1,* , M. LOZOVAN1, C. BACIU2

Affiliation

  1. National Institute of Research and Development for Technical Physics – IFT Iasi, 47 Mangeron Boulevard, 700050 Iasi, Romania
  2. Gh. Asachi” University, 11 Carol I Boulevard, 700050, Iasi, Romania

Abstract

A method for the simulation of some new advanced nanomagnetic materials with the Artificial Neural Network (ANN) is given. A Neural Network is an adaptable system that learn relationships through repeated presentation of data and is capable of generalizing to new, previously unseen data. Neural networks are used here for both, regression and classification. Since ANN’s learn from the data, the data must be valid for the results to be meaningful. A successful neural network simulation requires the specification of many parameters. This is a hard condition and we show that our work give an important contribution. The performance is highly dependent on the choice of these parameters. By adapting its weights, the neural network works towards the optimal solution based on a measurement of its performance. In our model we intend to use for the input data the following: the chemical composition, the thermal treatments and possibly some structure data. As output data we chose: Hall Effect, and the magnetoresistance effect for FeCrCuNbSiB class nanomaterials..

Keywords

Nanomagnetic materials, Artificial neural network, Simulation, Targeted design.

Submitted at: Nov. 14, 2006
Accepted at: May 15, 2007

Citation

S. MOHORIANU, M. LOZOVAN, C. BACIU, A new simulation method based on artificial neural networks for a special class of nanomagnetic materials design, Journal of Optoelectronics and Advanced Materials Vol. 9, Iss. 5, pp. 1499-1504 (2007)