Automatic General of a Neural Network Architecture Using Evolutionary Computation

E. Vonk; L.C. Jain; L.P.J. Veelenturf; R. Johnson

doi:10.1109/ETD.1995.403479

Automatic General of a Neural Network Architecture Using Evolutionary Computation

E. Vonk, L.C. Jain, L.P.J. Veelenturf, R. Johnson

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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Abstract

This paper reports the application of evolutionary computation in the automatic generation of a neural network architecture. It is a usual practice to use trial and error to find a suitable neural network architecture. This is not only time consuming but may not generate an optimal solution for a given problem. The use of evolutionary computation is a step towards automation in architecture generation. In this paper a brief introduction to the field is given as well as an implementation of automatic neural network generation using genetic programming

Original language	English
Title of host publication	Proceedings Electronic Technology Directions to the Year 2000 (ETD2000)
Place of Publication	Los Alamitos, CA
Publisher	IEEE
Number of pages	6
ISBN (Print)	9780818670855
DOIs	https://doi.org/10.1109/ETD.1995.403479
Publication status	Published - 23 May 1995
Event	Electronic Technology Directions to the Year 2000, Adelaide, Australia, ETD2000, 1995 - Duration: 1 Jan 1995 → 1 Jan 1995

Other

Other	Electronic Technology Directions to the Year 2000, Adelaide, Australia, ETD2000, 1995
Period	1/01/95 → 1/01/95

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10.1109/ETD.1995.403479

Vonk1995automaticFinal published version, 470 KB

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title = "Automatic General of a Neural Network Architecture Using Evolutionary Computation",

abstract = "This paper reports the application of evolutionary computation in the automatic generation of a neural network architecture. It is a usual practice to use trial and error to find a suitable neural network architecture. This is not only time consuming but may not generate an optimal solution for a given problem. The use of evolutionary computation is a step towards automation in architecture generation. In this paper a brief introduction to the field is given as well as an implementation of automatic neural network generation using genetic programming",

author = "E. Vonk and L.C. Jain and L.P.J. Veelenturf and R. Johnson",

year = "1995",

month = may,

day = "23",

doi = "10.1109/ETD.1995.403479",

language = "English",

isbn = "9780818670855",

booktitle = "Proceedings Electronic Technology Directions to the Year 2000 (ETD2000)",

publisher = "IEEE",

address = "United States",

note = "Electronic Technology Directions to the Year 2000, Adelaide, Australia, ETD2000, 1995 ; Conference date: 01-01-1995 Through 01-01-1995",

}

Vonk, E, Jain, LC, Veelenturf, LPJ & Johnson, R 1995, Automatic General of a Neural Network Architecture Using Evolutionary Computation. in Proceedings Electronic Technology Directions to the Year 2000 (ETD2000). IEEE, Los Alamitos, CA, Electronic Technology Directions to the Year 2000, Adelaide, Australia, ETD2000, 1995, 1/01/95. https://doi.org/10.1109/ETD.1995.403479

TY - GEN

T1 - Automatic General of a Neural Network Architecture Using Evolutionary Computation

AU - Vonk, E.

AU - Jain, L.C.

AU - Veelenturf, L.P.J.

AU - Johnson, R.

PY - 1995/5/23

Y1 - 1995/5/23

N2 - This paper reports the application of evolutionary computation in the automatic generation of a neural network architecture. It is a usual practice to use trial and error to find a suitable neural network architecture. This is not only time consuming but may not generate an optimal solution for a given problem. The use of evolutionary computation is a step towards automation in architecture generation. In this paper a brief introduction to the field is given as well as an implementation of automatic neural network generation using genetic programming

AB - This paper reports the application of evolutionary computation in the automatic generation of a neural network architecture. It is a usual practice to use trial and error to find a suitable neural network architecture. This is not only time consuming but may not generate an optimal solution for a given problem. The use of evolutionary computation is a step towards automation in architecture generation. In this paper a brief introduction to the field is given as well as an implementation of automatic neural network generation using genetic programming

U2 - 10.1109/ETD.1995.403479

DO - 10.1109/ETD.1995.403479

M3 - Conference contribution

SN - 9780818670855

BT - Proceedings Electronic Technology Directions to the Year 2000 (ETD2000)

PB - IEEE

CY - Los Alamitos, CA

T2 - Electronic Technology Directions to the Year 2000, Adelaide, Australia, ETD2000, 1995

Y2 - 1 January 1995 through 1 January 1995

ER -

Automatic General of a Neural Network Architecture Using Evolutionary Computation

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