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Pregled bibliografske jedinice broj: 38904

An Evolution and Biology Based Approach to the optimization of the Extrusion Process


Lozina, Željan; Duplančić, Igor; Prgin, Jere
An Evolution and Biology Based Approach to the optimization of the Extrusion Process // Proceedings of 7th International Aluminum Extrusion Technology Seminar / Peacock, Robert (ur.).
Chicago (IL): Aluminium Extruders Council, 2000. str. 109 - 118 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


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Naslov
An Evolution and Biology Based Approach to the optimization of the Extrusion Process

Autori
Lozina, Željan ; Duplančić, Igor ; Prgin, Jere

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings of 7th International Aluminum Extrusion Technology Seminar / Peacock, Robert - Chicago (IL) : Aluminium Extruders Council, 2000, 109 - 118

Skup
ET 2000

Mjesto i datum
Chicago (IL), Sjedinjene Američke Države, 16.05.2000. - 19.05.2000

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
optimization;extrusion process; neural network; genetic algorithm

Sažetak
A new approach to the optimization of extrusion process has been performed with Neural Network (ANN) and Genetic Algorithm (GA) based procedure. ANN trained on the technology process track record should be able to describe complex dependencies between influence parameters and product outgoing characteristics and is also supposed to be the fitness function. The optimization of the technological process based on genetic algorithm is proposed. The influence parameters are treated as heritage and combined with ANN forward pass being the fitness function. The ANN is trained presenting extrusion experiment data-patterns. The objective (fitness) function value is calculated with ANN forward pass. The optimization results are compared with a more conservative approach using experiment planing and regression analysis. The mean error of the difference between regression and ANN approach is used as a comparison measure. The influence of different training parameters and choice of training patterns are investigated. Optimization is performed on the extrusion of thick-walled AlZnMg (7000) hollow sections. Optimization variables are: billet temperature; extrusion rate; and Zr content. The output is tensile strength of the longitudinal welds. The advantages of the method presented are its robustness and flexibility.

Izvorni jezik
Engleski

Znanstvena područja
Strojarstvo



POVEZANOST RADA


Projekti:
023033

Ustanove:
Fakultet elektrotehnike, strojarstva i brodogradnje, Split

Profili:

Avatar Url Igor Duplančić (autor)

Avatar Url Jere Prgin (autor)

Avatar Url Željan Lozina (autor)


Citiraj ovu publikaciju:

Lozina, Željan; Duplančić, Igor; Prgin, Jere
An Evolution and Biology Based Approach to the optimization of the Extrusion Process // Proceedings of 7th International Aluminum Extrusion Technology Seminar / Peacock, Robert (ur.).
Chicago (IL): Aluminium Extruders Council, 2000. str. 109 - 118 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
Lozina, Ž., Duplančić, I. & Prgin, J. (2000) An Evolution and Biology Based Approach to the optimization of the Extrusion Process. U: Peacock, R. (ur.)Proceedings of 7th International Aluminum Extrusion Technology Seminar.
@article{article, author = {Lozina, \v{Z}eljan and Duplan\v{c}i\'{c}, Igor and Prgin, Jere}, editor = {Peacock, R.}, year = {2000}, pages = {109 - 118}, keywords = {optimization, extrusion process, neural network, genetic algorithm}, title = {An Evolution and Biology Based Approach to the optimization of the Extrusion Process}, keyword = {optimization, extrusion process, neural network, genetic algorithm}, publisher = {Aluminium Extruders Council}, publisherplace = {Chicago (IL), Sjedinjene Ameri\v{c}ke Dr\v{z}ave} }
@article{article, author = {Lozina, \v{Z}eljan and Duplan\v{c}i\'{c}, Igor and Prgin, Jere}, editor = {Peacock, R.}, year = {2000}, pages = {109 - 118}, keywords = {optimization, extrusion process, neural network, genetic algorithm}, title = {An Evolution and Biology Based Approach to the optimization of the Extrusion Process}, keyword = {optimization, extrusion process, neural network, genetic algorithm}, publisher = {Aluminium Extruders Council}, publisherplace = {Chicago (IL), Sjedinjene Ameri\v{c}ke Dr\v{z}ave} }




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