ARTIFICIAL NEURAL NETWORKS AND SPATIAL ESTIMATION OF CHERNOBYL FALLOUT

• Kanevsky Mikhail

  Institute of Nuclear Safety

• Arutyunyan Rafael

  Institute of Nuclear Safety

• Bolshov Leonid

  Institute of Nuclear Safety

• Demyanov Vasily

  Institute of Nuclear Safety

• Maignan Michel

  Mathematics/Mineralogy, University of Lausanne

書誌事項

タイトル別名

• Artificial Neural Networks and Spatial

抄録

The present work continues advanced spatial data analysis of surface contamination by radionuclides after severe nuclear accident on Chernobyl NPP. Feedforward neural networks are used for the Cs137 and Sr90 radionuclides prediction mapping and spatial estimations. Neural networks are used to model complex trends over the entire region. Residuals are analyzed with the help of geostatistical approach within the framework of NNRK (neural network residual kriging) model. Another set of data is used to validate obtained results.

収録刊行物

• 情報地質

  情報地質 7 (1-2), 5-11, 1996

  日本情報地質学会

キーワード

• Radioactively contaminated territories
• Artificial neural networks
• Residual kriging

詳細情報

• CRID: 1390001204439467904
• NII論文ID: 130006829201
• NII論文ID: 10004560073
• NII書誌ID: AN0036643X
• DOI: 10.6010/geoinformatics1990.7.1-2_5
• ISSN: 1347541X
• ISSN: 0388502X
• NDL書誌ID: 4002912
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I4002912
• Web Site: https://www.jstage.jst.go.jp/article/geoinformatics1990/7/1-2/7_1-2_5/_pdf
• 本文言語コード: en
• データソース種別:
  • JaLC
  • NDL
  • Crossref
  • CiNii Articles
• 抄録ライセンスフラグ: 使用不可