The prediction of Salt water Intrusion by the multi-layered neural network

• SUGITA Hisao

  HACHINOHE NATIONAL COLLEGE OF TECHNOLOGY

• ONODERA Yutaka

  HACHINOHE NATIONAL COLLEGE OF TECHNOLOGY

• YAGUCHI Junichi

  HACHINOHE NATIONAL COLLEGE OF TECHNOLOGY

• FUJIWARA Hirokazu

  HACHINOHE NATIONAL COLLEGE OF TECHNOLOGY

Bibliographic Information

Other Title

• 階層型ニューラルネットによる塩水侵入予測
• カイソウガタ ニューラルネット ニ ヨル シオミズ シンニュウ ヨソク

Abstract

It is difficult to measure the salt-water intrusion in the field though the environment of the Lake Ogawara consists on a delicate balance of the salt-water intrusion and the salinity circulation. In this study, the amount of the salinity outflow-inflow is estimate respectively by a multiple linear regression analysis and fuzzy reasoning by using only the water level of the river mouth and the Lake Ogawara. The tendency of the amount of the salinity outflow-inflow in winter was able to estimate by the multi-layered neural network.

Journal

• RESEACH REPORTS National Institute of Technology,Hachinohe College

  RESEACH REPORTS National Institute of Technology,Hachinohe College 39 (0), 67-72, 2004-12-20

  National Institute of Technology,Hachinohe College

Details

• CRID: 1390001288094858624
• NII Article ID: 110004323072
• NII Book ID: AN00205099
• DOI: 10.24704/hnctech.39.0_67
• ISSN: 24332003
• ISSN: 03854124
• NDL BIB ID: 7227173
• Web Site: http://id.ndl.go.jp/bib/7227173
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I7227173
• Text Lang: ja
• Data Source:
  • JaLC
  • NDL
  • CiNii Articles
  • KAKEN
• Abstract License Flag: Disallowed