Lattice Constant Prediction of Complex Cubic Peroveskite A<sub>2</sub>BCO<sub>6</sub> using Extreme Learning Machine-Reference-Cited by-同舟云学术

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Lattice Constant Prediction of Complex Cubic Peroveskite A₂BCO₆ using Extreme Learning Machine

Published:2022-11-26 Issue: Volume: Page:
ISSN:
Container-title:2022 International Conference of Advanced Technology in Electronic and Electrical Engineering (ICATEEE)
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Author:

Inas Bouzateur¹,Hamza Bennacer²,Assam Ouali Mohamed¹,Mohamed Ladjal¹,Issam Ziane Mohamed³,Moufdi Hadjab⁴

Affiliation:

1. University of M’Sila,LASS, Laboratory of Analysis of Signalset and Systems,Algeria

2. University of M’Sila,ECP3M, University of Mostaganem, Algeria,Algeria

3. The Higher School in Electrical and Energetic Engineering (ESGEE),Oran,Algeria

4. University of M’Sila,Departement of Electronics,Algeria

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10093233/10093088/10093696.pdf?arnumber=10093696

Reference18 articles.

1. Extreme learning machine and swarm-based support vector regression methods for predicting crystal lattice parameters of pseudo-cubic/cubic perovskites

2. Empirical method for modeling crystal lattice parameters of A2XY6 cubic crystals using grid search-based extreme learning machine

3. A study on effectiveness of extreme learning machine

4. Prediction of the unit cell edge length of cubic A 2 2+ BB′ O6 perovskites by multiple linear regression and artificial neural networks;dimitrovska;Central European Journal of Chemistry,2005

5. Predictions of new ABO3 perovskite compounds by combining machine learning and density functional theory

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