A Study on Application of Machine Learning for Analyzing Space Charge Accumulation Behavior in Low-Density Polyethylene

カテゴリ: 部門大会

論文No: 3-B-a2-1

グループ名: 【A】令和６年電気学会基礎・材料・共通部門大会

発行日: 2024/08/26

タイトル(英語): A Study on Application of Machine Learning for Analyzing Space Charge Accumulation Behavior in Low-Density Polyethylene

著者名: Imichi Ruri(Ehime University), Yudate Shinji(Ehime University), Ozaki Ryotaro(Ehime University), Kadowaki Kazunori(Ehime University)

キーワード: machine learning|space charge|neural network|low-density polyethylene

要約(日本語): This study examines the application of machine learning techniques to analyze space charge accumulation behavior in low-density polyethylene (LDPE). Initially, a set of simulation results was used to train the machine learning models. It was determined that at least 15 data sets were required to achieve reliable performance from the machine learning algorithms. Subsequently, the approach was validated using 15 actual experimental data sets. The results demonstrate that machine learning can approximately predict and analyze space charge accumulation in LDPE.

要約(英語): This study examines the application of machine learning techniques to analyze space charge accumulation behavior in low-density polyethylene (LDPE). Initially, a set of simulation results was used to train the machine learning models. It was determined that at least 15 data sets were required to achieve reliable performance from the machine learning algorithms. Subsequently, the approach was validated using 15 actual experimental data sets. The results demonstrate that machine learning can approximately predict and analyze space charge accumulation in LDPE.

PDFファイルサイズ: 292 Kバイト