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Determining the number of real roots of polynomials through neural networks

Research output: Contribution to Journal/Magazine › Journal article › peer-review

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Determining the number of real roots of polynomials through neural networks. / Mourrain, B.; Pavlidis, Nicos; Tasoulis, Dimitrios K et al.
In: Computers and Mathematics with Applications, Vol. 51, No. 3-4, 02.2006, p. 527-536.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Mourrain, B, Pavlidis, N, Tasoulis, DK & Vrahatis, MN 2006, 'Determining the number of real roots of polynomials through neural networks', Computers and Mathematics with Applications, vol. 51, no. 3-4, pp. 527-536. https://doi.org/10.1016/j.camwa.2005.07.012

APA

Mourrain, B., Pavlidis, N., Tasoulis, D. K., & Vrahatis, M. N. (2006). Determining the number of real roots of polynomials through neural networks. Computers and Mathematics with Applications, 51(3-4), 527-536. https://doi.org/10.1016/j.camwa.2005.07.012

Vancouver

Mourrain B, Pavlidis N, Tasoulis DK, Vrahatis MN. Determining the number of real roots of polynomials through neural networks. Computers and Mathematics with Applications. 2006 Feb;51(3-4):527-536. doi: 10.1016/j.camwa.2005.07.012

Author

Mourrain, B. ; Pavlidis, Nicos ; Tasoulis, Dimitrios K et al. / Determining the number of real roots of polynomials through neural networks. In: Computers and Mathematics with Applications. 2006 ; Vol. 51, No. 3-4. pp. 527-536.

Bibtex

@article{88c57946421d4d74ba37e0915bc32343,
title = "Determining the number of real roots of polynomials through neural networks",
abstract = "The ability of feedforward neural networks to identify the number of real roots of univariate polynomials is investigated. Furthermore, their ability to determine whether a system of multivariate polynomial equations has real solutions is examined on a problem of determining the structure of a molecule. The obtained experimental results indicate that neural networks are capable of performing this task with high accuracy even when the training set is very small compared to the test set.",
keywords = "Roots of polynomials, Neural networks , Number of zeros",
author = "B. Mourrain and Nicos Pavlidis and Tasoulis, {Dimitrios K} and Vrahatis, {Michael N.}",
year = "2006",
month = feb,
doi = "10.1016/j.camwa.2005.07.012",
language = "English",
volume = "51",
pages = "527--536",
journal = "Computers and Mathematics with Applications",
issn = "0898-1221",
publisher = "Elsevier Limited",
number = "3-4",

}

RIS

TY - JOUR

T1 - Determining the number of real roots of polynomials through neural networks

AU - Mourrain, B.

AU - Pavlidis, Nicos

AU - Tasoulis, Dimitrios K

AU - Vrahatis, Michael N.

PY - 2006/2

Y1 - 2006/2

N2 - The ability of feedforward neural networks to identify the number of real roots of univariate polynomials is investigated. Furthermore, their ability to determine whether a system of multivariate polynomial equations has real solutions is examined on a problem of determining the structure of a molecule. The obtained experimental results indicate that neural networks are capable of performing this task with high accuracy even when the training set is very small compared to the test set.

AB - The ability of feedforward neural networks to identify the number of real roots of univariate polynomials is investigated. Furthermore, their ability to determine whether a system of multivariate polynomial equations has real solutions is examined on a problem of determining the structure of a molecule. The obtained experimental results indicate that neural networks are capable of performing this task with high accuracy even when the training set is very small compared to the test set.

KW - Roots of polynomials

KW - Neural networks

KW - Number of zeros

U2 - 10.1016/j.camwa.2005.07.012

DO - 10.1016/j.camwa.2005.07.012

M3 - Journal article

VL - 51

SP - 527

EP - 536

JO - Computers and Mathematics with Applications

JF - Computers and Mathematics with Applications

SN - 0898-1221

IS - 3-4

ER -