dc.contributor.author | Megherbi, Mohamed | |
dc.contributor.author | Slimani, Ferhat | |
dc.contributor.author | Hedir, Abdallah | |
dc.contributor.author | Moudoud, Mustapha | |
dc.contributor.author | DURMUŞ, Ali | |
dc.contributor.author | Amir, Mounir | |
dc.date.accessioned | 2021-12-10T09:31:33Z | |
dc.date.available | 2021-12-10T09:31:33Z | |
dc.date.issued | 2021 | |
dc.identifier.citation | Slimani F., Hedir A., Moudoud M., DURMUŞ A., Amir M., Megherbi M., "Prediction of long-term physical properties of low density polyethylene (LDPE) cable insulation materials by artificial neural network modeling approach under environmental constraints", TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES, cilt.29, sa.5, ss.2437-2449, 2021 | |
dc.identifier.issn | 1300-0632 | |
dc.identifier.other | av_0167146a-88dd-4fb1-aa6e-96690dd6c0b5 | |
dc.identifier.other | vv_1032021 | |
dc.identifier.uri | http://hdl.handle.net/20.500.12627/167922 | |
dc.identifier.uri | https://doi.org/10.3906/elk-2105-27 | |
dc.description.abstract | This study quantifies long-term physical properties of low density polyethylene (LDPE) cables insulations exposed to environmental constraints such as UV radiation and temperature via both experimental measurements and mathematical modeling approach. For this purpose, tensile test and electrical breakdown test were carried out to determine elongation at break, tensile strength, and dielectric strength of unaged and aged specimens, respectively. Experimental results showed that both UV and temperature exposures affected the LDPE properties, significantly. A supervised artificial neural network (ANN) trained by the Levenb erg-Marquardt algorithm was designed for predicting the long-term characteristics of specimens and also for minimizing the experimental procedures. Modeling work showed that the proposed ANN yielded successful estimations and predictions about the service life of thermoplastic cable insulation materials for maintaining the process. | |
dc.language.iso | eng | |
dc.subject | Computer Science Applications | |
dc.subject | Physical Sciences | |
dc.subject | BİLGİSAYAR BİLİMİ, YAPAY ZEKA | |
dc.subject | Bilgisayar Bilimi | |
dc.subject | Mühendislik, Bilişim ve Teknoloji (ENG) | |
dc.subject | MÜHENDİSLİK, ELEKTRİK VE ELEKTRONİK | |
dc.subject | Mühendislik | |
dc.subject | Bilgi Sistemleri, Haberleşme ve Kontrol Mühendisliği | |
dc.subject | Sinyal İşleme | |
dc.subject | Bilgisayar Bilimleri | |
dc.subject | Algoritmalar | |
dc.subject | Mühendislik ve Teknoloji | |
dc.subject | Signal Processing | |
dc.subject | General Engineering | |
dc.subject | Artificial Intelligence | |
dc.subject | General Computer Science | |
dc.subject | Engineering (miscellaneous) | |
dc.subject | Electrical and Electronic Engineering | |
dc.subject | Computer Science (miscellaneous) | |
dc.subject | Computer Vision and Pattern Recognition | |
dc.title | Prediction of long-term physical properties of low density polyethylene (LDPE) cable insulation materials by artificial neural network modeling approach under environmental constraints | |
dc.type | Makale | |
dc.relation.journal | TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES | |
dc.contributor.department | Université Mouloud Mammeri De Tizi Ouzou , , | |
dc.identifier.volume | 29 | |
dc.identifier.issue | 5 | |
dc.identifier.startpage | 2437 | |
dc.identifier.endpage | 2449 | |
dc.contributor.firstauthorID | 2750157 | |