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

Department of Electrical & Computer Engineering

Ben-Gurion University of the Negev

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

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.

Original language	American English
Title of host publication	Artificial Intelligence and Soft Computing - 17th International Conference, ICAISC 2018, Proceedings
Editors	Ryszard Tadeusiewicz, Leszek Rutkowski, Witold Pedrycz, Rafal Scherer, Marcin Korytkowski, Jacek M. Zurada
Publisher	Springer Verlag
Pages	711-722
Number of pages	12
ISBN (Print)	9783319912615
DOIs	https://doi.org/10.1007/978-3-319-91262-2_62
State	Published - 1 Jan 2018
Event	17th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2018 - Zakopane, Poland Duration: 3 Jun 2018 → 7 Jun 2018

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10842 LNAI

Conference

Conference	17th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2018
Country/Territory	Poland
City	Zakopane
Period	3/06/18 → 7/06/18

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy
SDG 9 Industry, Innovation, and Infrastructure

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
General Computer Science

Access to Document

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

Cite this

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. In R. Tadeusiewicz, L. Rutkowski, W. Pedrycz, R. Scherer, M. Korytkowski, & J. M. Zurada (Eds.), Artificial Intelligence and Soft Computing - 17th International Conference, ICAISC 2018, Proceedings (pp. 711-722). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10842 LNAI). Springer Verlag. https://doi.org/10.1007/978-3-319-91262-2_62

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

@inproceedings{ee33dbd56e7443d9b6345d0e89a63f7e,

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",

month = jan,

day = "1",

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

language = "American 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. in R Tadeusiewicz, L Rutkowski, W Pedrycz, R Scherer, M Korytkowski & JM Zurada (eds), 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), vol. 10842 LNAI, Springer Verlag, pp. 711-722, 17th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2018, Zakopane, Poland, 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 et al.
Artificial Intelligence and Soft Computing - 17th International Conference, ICAISC 2018, Proceedings. ed. / Ryszard Tadeusiewicz; Leszek Rutkowski; Witold Pedrycz; Rafal Scherer; Marcin Korytkowski; Jacek M. Zurada. Springer Verlag, 2018. p. 711-722 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10842 LNAI).

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

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

PY - 2018/1/1

Y1 - 2018/1/1

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.

UR - http://www.scopus.com/inward/record.url?scp=85048048456&partnerID=8YFLogxK

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

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

M3 - Conference contribution

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. In Tadeusiewicz R, Rutkowski L, Pedrycz W, Scherer R, Korytkowski M, Zurada JM, editors, Artificial Intelligence and Soft Computing - 17th International Conference, ICAISC 2018, Proceedings. Springer Verlag. 2018. p. 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

Abstract

Publication series

Conference

UN SDGs

All Science Journal Classification (ASJC) codes

Access to Document

Other files and links

Fingerprint

Cite this