A Causal Factor Analysis of Traffic Obstacles Due to the 2001 Heavy Snow Using Neural Network: A Case Study of Trunk Road in Ishikawa

• 宮原 賢

• 池本 敏和

• 北浦 勝

• 宮島 昌克

• Miyashita Satoshi

• Ikemoto Toshikazu

• Kitaura Masaru

• Miyajima Masakatsu

Bibliographic Information

Other Title

• ニューラルネットワークを用いた2001年大雪による交通障害の要因分析: 石川県内の主要幹線をケーススタディとして
• ニューラル ネットワーク オ モチイタ 2001ネン オオユキ ニ ヨル コウツウ ショウガイ ノ ヨウイン ブンセキ イシカワ ケンナイ ノ シュヨウ カンセン オ ケーススタディ ト シテ

Abstract

金沢大学理工研究域地球社会基盤学系

It is extremely important to consider traffic blockage due to heavy snow. In this study, we used observed data of traffic interception due to snow between January 11 and 20, 2001 in Ishikawa and investigated the mechanism of such an event based on neural network approach. We performed sensitivity analysis to compare the effect of input parameters on output values. The sensitivity is defined as a mean value of various output values in each of the seven divisions which were assigned between plus one standard deviation and minus one standard deviation. Mitigation measures such as increasing snow-melting facilities and decreasing the number of passing vehicles of each route were discussed.

Journal

• 日本雪工学会誌 = Journal of Snow Engineering of Japan

  日本雪工学会誌 = Journal of Snow Engineering of Japan 20 (4), 374-378, 2004-10-01

  日本雪工学会 Japan Society for Snow Engineering

Details

• CRID: 1390291767497987968
• NII Article ID: 10018631216
• NII Article ID: 120007192395
• NII Book ID: AN10063773
• ISSN: 09133526
• ISSN: 18824358
• DOI: 10.24517/00065510
• NDL BIB ID: 7134606
• Web Site: http://hdl.handle.net/2297/00065510
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I7134606
• Text Lang: ja
• Data Source:
  • JaLC
  • IRDB
  • NDL
  • CiNii Articles