Exploiting OSC models by using neural networks with an innovative pruning algorithm

Grazia Lo Sciuto; Giacomo Capizzi; Christian Napoli; Rafi Shikler; Dawid Połap; Marcin Woźniak

doi:10.1007/978-3-319-91262-2_62

Exploiting OSC models by using neural networks with an innovative pruning algorithm

Grazia Lo Sciuto
, Giacomo Capizzi
, Christian Napoli
, Rafi Shikler
, Dawid Połap
, Marcin Woźniak

Katedra Modelowania Sztucznej Inteligencji (RMS/RMS2)

University of Catania
Ben-Gurion University of the Negev

Wyniki badań: Rozdział w książce/raport/materiał konferencyjny › Wkład w konferencję › recenzja

4 Cytowania z bazy Scopus

Abstrakt

In this paper we have investigated the relationship between the current and the active layer thickness of an organic solar cell (OSC) in order to improve its efficiency by means of a back propagation neural network. In order to preserve the generalization properties of the adopted neural network (NN) in this paper is presented also an innovative pruning technique. The extensive simulations performed show a good agreement between simulated and experimental data with an overall error of about 3%. The obtained results demostrate that the use of an MLP with associated an appropriate pruning algorithm to preserve its generalization capacities permits to accurately reproduce the relationship between the active layer thicknesses and the measured maximum power in an OSC. This neural model can be of great use in manufacturing processes.

Język oryginału	angielski
Tytuł publikacji goszczącej	Artificial Intelligence and Soft Computing - 17th International Conference, ICAISC 2018, Proceedings
Redaktorzy	Ryszard Tadeusiewicz, Leszek Rutkowski, Witold Pedrycz, Rafal Scherer, Marcin Korytkowski, Jacek M. Zurada
Wydawca	Springer Verlag
Strony	711-722
Liczba stron	12
ISBN (drukowany)	9783319912615
Identyfikatory DOI	https://doi.org/10.1007/978-3-319-91262-2_62
Status publikacji	Opublikowano - 2018
Wydarzenie	17th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2018 - Zakopane, Polska Czas trwania: 3 cze 2018 → 7 cze 2018

Seria publikacji

Nazwa	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Tom	10842 LNAI
ISSN (drukowany)	0302-9743
ISSN (elektroniczny)	1611-3349

Konferencja

Konferencja	17th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2018
Kraj/Terytorium	Polska
Miejscowość	Zakopane
Okres	3/06/18 → 7/06/18

Cele SDG ONZ

Ten wynik przyczynia się do realizacji następujących celów zrównoważonego rozwoju

Cel 7 Przystępna i czysta energia
Cel 9 Przemysł, innowacje i infrastruktura

Obszary tematyczne ASJC Scopus

Informatyka teoretyczna
Informatyka ogólna

Uzyskaj dostęp do dokumentu

10.1007/978-3-319-91262-2_62

Inne pliki i linki

Link do publikacji w Scopus

Cytowanie

Lo Sciuto, G., Capizzi, G., Napoli, C., Shikler, R., Połap, D., & Woźniak, M. (2018). Exploiting OSC models by using neural networks with an innovative pruning algorithm. W R. Tadeusiewicz, L. Rutkowski, W. Pedrycz, R. Scherer, M. Korytkowski, & J. M. Zurada (Red.), Artificial Intelligence and Soft Computing - 17th International Conference, ICAISC 2018, Proceedings (str. 711-722). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Tom 10842 LNAI). Springer Verlag. https://doi.org/10.1007/978-3-319-91262-2_62

Lo Sciuto, Grazia ; Capizzi, Giacomo ; Napoli, Christian i in. / Exploiting OSC models by using neural networks with an innovative pruning algorithm. Artificial Intelligence and Soft Computing - 17th International Conference, ICAISC 2018, Proceedings. redaktor / Ryszard Tadeusiewicz ; Leszek Rutkowski ; Witold Pedrycz ; Rafal Scherer ; Marcin Korytkowski ; Jacek M. Zurada. Springer Verlag, 2018. str. 711-722 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{08b3333a6de34359a9bed2c3626ba3a5,

title = "Exploiting OSC models by using neural networks with an innovative pruning algorithm",

abstract = "In this paper we have investigated the relationship between the current and the active layer thickness of an organic solar cell (OSC) in order to improve its efficiency by means of a back propagation neural network. In order to preserve the generalization properties of the adopted neural network (NN) in this paper is presented also an innovative pruning technique. The extensive simulations performed show a good agreement between simulated and experimental data with an overall error of about 3\%. The obtained results demostrate that the use of an MLP with associated an appropriate pruning algorithm to preserve its generalization capacities permits to accurately reproduce the relationship between the active layer thicknesses and the measured maximum power in an OSC. This neural model can be of great use in manufacturing processes.",

author = "\{Lo Sciuto\}, Grazia and Giacomo Capizzi and Christian Napoli and Rafi Shikler and Dawid Po{\l}ap and Marcin Wo{\'z}niak",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG, part of Springer Nature 2018.; 17th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2018 ; Conference date: 03-06-2018 Through 07-06-2018",

year = "2018",

doi = "10.1007/978-3-319-91262-2\_62",

language = "English",

isbn = "9783319912615",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "711--722",

editor = "Ryszard Tadeusiewicz and Leszek Rutkowski and Witold Pedrycz and Rafal Scherer and Marcin Korytkowski and Zurada, \{Jacek M.\}",

booktitle = "Artificial Intelligence and Soft Computing - 17th International Conference, ICAISC 2018, Proceedings",

address = "Germany",

}

Lo Sciuto, G, Capizzi, G, Napoli, C, Shikler, R, Połap, D & Woźniak, M 2018, Exploiting OSC models by using neural networks with an innovative pruning algorithm. w R Tadeusiewicz, L Rutkowski, W Pedrycz, R Scherer, M Korytkowski & JM Zurada (red), Artificial Intelligence and Soft Computing - 17th International Conference, ICAISC 2018, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), tom 10842 LNAI, Springer Verlag, str. 711-722, 17th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2018, Zakopane, Polska, 3/06/18. https://doi.org/10.1007/978-3-319-91262-2_62

Exploiting OSC models by using neural networks with an innovative pruning algorithm. / Lo Sciuto, Grazia; Capizzi, Giacomo; Napoli, Christian i in.
Artificial Intelligence and Soft Computing - 17th International Conference, ICAISC 2018, Proceedings. red. / Ryszard Tadeusiewicz; Leszek Rutkowski; Witold Pedrycz; Rafal Scherer; Marcin Korytkowski; Jacek M. Zurada. Springer Verlag, 2018. str. 711-722 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Tom 10842 LNAI).

Wyniki badań: Rozdział w książce/raport/materiał konferencyjny › Wkład w konferencję › recenzja

TY - GEN

T1 - Exploiting OSC models by using neural networks with an innovative pruning algorithm

AU - Lo Sciuto, Grazia

AU - Capizzi, Giacomo

AU - Napoli, Christian

AU - Shikler, Rafi

AU - Połap, Dawid

AU - Woźniak, Marcin

N1 - Publisher Copyright: © Springer International Publishing AG, part of Springer Nature 2018.

PY - 2018

Y1 - 2018

N2 - In this paper we have investigated the relationship between the current and the active layer thickness of an organic solar cell (OSC) in order to improve its efficiency by means of a back propagation neural network. In order to preserve the generalization properties of the adopted neural network (NN) in this paper is presented also an innovative pruning technique. The extensive simulations performed show a good agreement between simulated and experimental data with an overall error of about 3%. The obtained results demostrate that the use of an MLP with associated an appropriate pruning algorithm to preserve its generalization capacities permits to accurately reproduce the relationship between the active layer thicknesses and the measured maximum power in an OSC. This neural model can be of great use in manufacturing processes.

AB - In this paper we have investigated the relationship between the current and the active layer thickness of an organic solar cell (OSC) in order to improve its efficiency by means of a back propagation neural network. In order to preserve the generalization properties of the adopted neural network (NN) in this paper is presented also an innovative pruning technique. The extensive simulations performed show a good agreement between simulated and experimental data with an overall error of about 3%. The obtained results demostrate that the use of an MLP with associated an appropriate pruning algorithm to preserve its generalization capacities permits to accurately reproduce the relationship between the active layer thicknesses and the measured maximum power in an OSC. This neural model can be of great use in manufacturing processes.

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U2 - 10.1007/978-3-319-91262-2_62

DO - 10.1007/978-3-319-91262-2_62

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AN - SCOPUS:85048048456

SN - 9783319912615

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 711

EP - 722

BT - Artificial Intelligence and Soft Computing - 17th International Conference, ICAISC 2018, Proceedings

A2 - Tadeusiewicz, Ryszard

A2 - Rutkowski, Leszek

A2 - Pedrycz, Witold

A2 - Scherer, Rafal

A2 - Korytkowski, Marcin

A2 - Zurada, Jacek M.

PB - Springer Verlag

T2 - 17th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2018

Y2 - 3 June 2018 through 7 June 2018

ER -

Lo Sciuto G, Capizzi G, Napoli C, Shikler R, Połap D , Woźniak M. Exploiting OSC models by using neural networks with an innovative pruning algorithm. W Tadeusiewicz R, Rutkowski L, Pedrycz W, Scherer R, Korytkowski M, Zurada JM, redaktorzy, Artificial Intelligence and Soft Computing - 17th International Conference, ICAISC 2018, Proceedings. Springer Verlag. 2018. str. 711-722. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-91262-2_62

Exploiting OSC models by using neural networks with an innovative pruning algorithm

Abstrakt

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Konferencja

Cele SDG ONZ

Obszary tematyczne ASJC Scopus

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