Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
GROUND SUBSIDENCE PREDICTION SYSTEM
To provide a ground subsidence prediction system that can accurately predict ground subsidence at a specific point as an estimated ground subsidence point.SOLUTION: The ground subsidence prediction system comprises: a first learning unit 11 that learns the calculation of a value of a subsidence parameter at an arbitrary point from ground information at the arbitrary point by machine learning; an area information storage unit 12 that stores map data of a predetermined area and known point information; an estimated point setting unit 21 that sets the estimated point on the map; a peripheral information extraction unit 22 that extracts known point information for each known point existing around the estimated point; a peripheral subsidence parameter calculation unit 23 that causes the first learning unit 11 to calculate the value of the subsidence parameter from the extracted known point information for each known point; and a subsidence parameter estimation unit 24 that calculates the value of the subsidence parameter at the estimated point based on the subsidence parameter for each known point calculated by the peripheral subsidence parameter calculation unit 23.SELECTED DRAWING: Figure 2
【課題】特定の地点を地盤沈下の推定地点として、推定地点の地盤沈下を正確に予測することができる地盤沈下予測システムを提供する。【解決手段】任意の地点の地盤情報から前記任意の地点の沈下パラメータの値の算出を機械学習により学習した第１学習部１１と、所定の地域の地図データと既知地点情報とが格納された地域情報格納部１２と、地図上の推定地点を設定する推定地点設定部２１と、推定地点の周辺に存在する既知地点ごとの既知地点情報を抽出する周辺情報抽出部２２と、抽出した既知地点ごとの既知地点情報から、沈下パラメータの値を第１学習部１１に算出させる周辺沈下パラメータ算出部２３と、周辺沈下パラメータ算出部２３に算出させた前記既知地点ごとの沈下パラメータに基づいて、推定地点の沈下パラメータの値を算出する沈下パラメータ推定部２４と、を備える。【選択図】図２
GROUND SUBSIDENCE PREDICTION SYSTEM
To provide a ground subsidence prediction system that can accurately predict ground subsidence at a specific point as an estimated ground subsidence point.SOLUTION: The ground subsidence prediction system comprises: a first learning unit 11 that learns the calculation of a value of a subsidence parameter at an arbitrary point from ground information at the arbitrary point by machine learning; an area information storage unit 12 that stores map data of a predetermined area and known point information; an estimated point setting unit 21 that sets the estimated point on the map; a peripheral information extraction unit 22 that extracts known point information for each known point existing around the estimated point; a peripheral subsidence parameter calculation unit 23 that causes the first learning unit 11 to calculate the value of the subsidence parameter from the extracted known point information for each known point; and a subsidence parameter estimation unit 24 that calculates the value of the subsidence parameter at the estimated point based on the subsidence parameter for each known point calculated by the peripheral subsidence parameter calculation unit 23.SELECTED DRAWING: Figure 2
【課題】特定の地点を地盤沈下の推定地点として、推定地点の地盤沈下を正確に予測することができる地盤沈下予測システムを提供する。【解決手段】任意の地点の地盤情報から前記任意の地点の沈下パラメータの値の算出を機械学習により学習した第１学習部１１と、所定の地域の地図データと既知地点情報とが格納された地域情報格納部１２と、地図上の推定地点を設定する推定地点設定部２１と、推定地点の周辺に存在する既知地点ごとの既知地点情報を抽出する周辺情報抽出部２２と、抽出した既知地点ごとの既知地点情報から、沈下パラメータの値を第１学習部１１に算出させる周辺沈下パラメータ算出部２３と、周辺沈下パラメータ算出部２３に算出させた前記既知地点ごとの沈下パラメータに基づいて、推定地点の沈下パラメータの値を算出する沈下パラメータ推定部２４と、を備える。【選択図】図２
GROUND SUBSIDENCE PREDICTION SYSTEM
地盤沈下予測システム
NISHI TAKUMA (Autor:in) / SARATANI AKIKO (Autor:in) / YOSHIDA FUMIHISA (Autor:in)
28.01.2021
Patent
Elektronische Ressource
Japanisch
IPC:
E02D
FOUNDATIONS
,
Gründungen
| TIBKAT | 1989
| TIBKAT | 1977
Prediction of ground subsidence above tunnels in Cairo
| British Library Conference Proceedings | 1997