Fundamental Research on Interatomic Potential Database Construction using Neural Network

• TSUCHIDA Daisuke

  Department of Adaptive Machine Systems, Graduate School of Engineering, Osaka University

• NAKATANI Akihiro

  Dept. of Adaptive Machine Systems, Osaka University

• KITAGAWA Hiroshi

  Dept. of Adaptive Machine Systems, Osaka University

Bibliographic Information

Other Title

• 605 ニューラルネットを用いた原子間相互作用データベース構築に関する基礎的研究

Abstract

In this paper we apply a neural network to evaluation problem of interatomic potential that is determined by the arrangement of surrounding atoms. We examine the character of several proposed neural network structures, using simple atomic models. We focus mainly on the quasi-newton method and the backpropagation algorithm. Simulation results show that the quasi-newton method represents a gain concerning number of iteration of weights.

Journal

• The Proceedings of Conference of Kansai Branch

  The Proceedings of Conference of Kansai Branch 2003.78 (0), _6-9_-_6-10_, 2003

  The Japan Society of Mechanical Engineers

Keywords

• Interatomic potential
• Neural network
• Back propagation
• RBF network
• Quasi Newton method

Details

• CRID: 1390282680826821376
• NII Article ID: 110002493589
• DOI: 10.1299/jsmekansai.2003.78._6-9_
• ISSN: 24242756
• Web Site: https://www.jstage.jst.go.jp/article/jsmekansai/2003.78/0/2003.78__6-9_/_pdf
• Text Lang: ja
• Data Source:
  • JaLC
  • Crossref
  • CiNii Articles
• Abstract License Flag: Disallowed