Development of design system of coastal and river structures using neural network

利用神经网络开发海岸和河流结构设计系统

• 批准号: 06555148
• 负责人: MASE Hajime
• 金额: $ 3.58万
• 依托单位: KYOTO UNIVERSITY
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (B)
• 财政年份: 1994
• 资助国家: 日本
• 起止时间: 1994 至 1996
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-06555148/
• 关键词: neural network; rubble mound breakwater; armor layr; ニュートラルネットワーク; 消波ブロック; 護岸; 混成防波堤; 河川護岸; 天然河岸; 衝撃砕波力

The stability of rocky slope under wave attack have been investigated by mainly hydraulic model tests, and empirical formulae have been proposed based on the test results. Van der Meer (1988) proposed a formula for the rocky slope stability based on a large number of irregular wave experiments. However, the formula is insufficient to represent the damage level. Kaku et al. (1991) and Smith et al. (1992) newly proposed an empirical formula to improve the degree of agreement between the measured and predicted damage levels. The formula, however, is not universal ; which requires a change of the coefficients in the formula for different data source.It is desired to make a universal formula or a methodology to arrange the experimental data having ambiguous mutual relationships between physical factors (Mase et al., 1995). A neural network modeled on the structure of brain is effective to deal with information having not clear relations between causes and effects. This study shows the efficiency of neural network method to assess the stability of rubble mound breakwaters and armor layrs. In addition to show the efficiency, sensitivity of some parameters governing the stability (taking up the damage level as a parameter representing stability) is evaluated by utilizing the neural network where the number of acting waves, the stability number, and the surf similarity parameter are always employed to represent at least the characteristics of breakwaters and waves. For the case of rubble mound breakwaters, the permeability coefficient and the dimensionless water depth were found to be significant. However, for the case of armor layr, the difference of sensitivity of input parameters was little.

本文主要通过水工模型试验研究了波浪作用下岩质边坡的稳定性，并根据试验结果提出了经验公式。Van der Meer（1988）在大量不规则波试验的基础上，提出了岩质边坡稳定性公式。然而，该公式不足以表示损伤程度。Kaku等人（1991）和Smith等人（1992）最近提出了一个经验公式，以提高测量和预测损伤水平之间的一致程度。然而，这个公式并不普遍；这需要根据不同的数据源改变公式中的系数。对于物理因素之间相互关系模糊的实验数据，需要制定一个通用公式或方法进行整理（Mase et al., 1995）。以大脑结构为模型的神经网络可以有效地处理因果关系不明确的信息。研究结果表明，神经网络方法在碎石丘、防波堤和护甲层稳定性评价中的有效性。利用神经网络对控制稳定性的一些参数（以损伤等级作为代表稳定性的参数）的灵敏度进行了评价，其中作用波数、稳定数和冲浪相似度参数总是至少代表防波堤和波浪的特征。对于碎石丘式防波堤，其渗透系数和无量纲水深显著。而对于装甲层，输入参数的灵敏度差异不大。

项目成果

後藤仁志: "ニューラルネットワークを用いた護岸被災形態の類型化" 水工学論文集. 第38巻. 833-836 (1994)

Hitoshi Goto：“使用神经网络对海堤的损坏模式进行分类”，《水利工程学报》，第 38 卷，833-836（1994 年）。

Hajime Mase: "Evalnation of Artificial Armour Layer Stability by Newral Network Methoe" Proc. 26th Congress of IAHR. 341-346 (1995)

Hajime Mase：“通过 Newral Network Methoe 评估人工装甲层稳定性”Proc。

Mase, H.and Takayama, T.: "Evaluation of sensitivity of parameters affecting stability assessment of rubble mound breakwater" Proc.Japanese Conf.Coastal Eng.Vol.43, JSCE. 801-805 (1996)

Mase, H. 和 Takayama, T.：“影响碎石堆防波堤稳定性评估的参数敏感性评估”Proc.Japan Conf.Coastal Eng.Vol.43，JSCE。

Mase, H.and Takayama, T.: "Stability assessment of rubble mound breakwater and armor layr" Proc.7th Int.Conf.Offshore and Polar Eng., Hawaii, USA. (in print).(1997)

Mase, H. 和 Takayama, T.：“碎石堆防波堤和装甲层的稳定性评估”Proc.7th Int.Conf.Offshore and Polar Eng.，美国夏威夷。

間瀬肇・高山知司: "ニュートラルネットワークによる捨石防波堤の安定性に及ぼす支配因の影響度評価" 海岸工学論文集. 43. 801-805 (1996)

Hajime Mase 和 Satoshi Takayama：“使用中性网络评估控制因素对碎石防波堤稳定性的影响”海岸工程杂志 43. 801-805 (1996)。