Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
PREDICTION PROGRAM AND WATERWAY MANAGEMENT SYSTEM BASED ON LEARNING MODEL OF WATERWAY CONTROL
To solve the problem in which, although it is desirable to manage waterways through data acquisition and machine learning, it has been difficult to acquire data from various locations of waterways due to the lack of a maintenance-free, running water-powered measurement and communication system that can be installed relatively easily in inaccessible areas such as sewer systems and mountainous areas, and that can acquire flow rate and water level data, and in addition, a communication network that can function even during power outages is desirable as a disaster countermeasure.SOLUTION: The objective of this invention is to install a maintenance-free, running water-powered measurement and communication system at various locations in a water area, acquire observation data and external environmental data from the system, as well as management and control data from dams and sluice gates, and use machine learning to estimate the flow distribution and inundation prediction of the waterway network using the observation data, external environmental data, and management and control data as inputs. In waterways where power generation amount for continuous communication can be secured, the measurement and communication equipment itself is used as a communication relay, or the power generation mechanism is used as a power source for the communication infrastructure.SELECTED DRAWING: Figure 3
【課題】データ取得と機械学習による水路管理が望ましいが、下水道や山間部などのアクセスの悪い地点において比較的簡単に設置でき、流量や水位データを取得するメンテナンスフリーかつ流水発電可能な計測通信システムがなかったために水路各所のデータ取得が困難だった。また、停電時にも機能する通信網が災害対策として望ましい。【解決手段】メンテナンスフリーかつ流水発電可能な計測通信システムを水域各所に設置し、そこからの観測データと外部環境データや、ダムや水門等の管理制御データを取得して機械学習により学習し、観測データと外部環境データと管理制御データを入力として水路網の流量分布や氾濫の予測を推定することを目的とする。また、継続的な通信を行う発電量が確保できる水路では計測通信機そのものを通信中継機として、あるいは発電機構を通信インフラの電源とする【選択図】図３
PREDICTION PROGRAM AND WATERWAY MANAGEMENT SYSTEM BASED ON LEARNING MODEL OF WATERWAY CONTROL
To solve the problem in which, although it is desirable to manage waterways through data acquisition and machine learning, it has been difficult to acquire data from various locations of waterways due to the lack of a maintenance-free, running water-powered measurement and communication system that can be installed relatively easily in inaccessible areas such as sewer systems and mountainous areas, and that can acquire flow rate and water level data, and in addition, a communication network that can function even during power outages is desirable as a disaster countermeasure.SOLUTION: The objective of this invention is to install a maintenance-free, running water-powered measurement and communication system at various locations in a water area, acquire observation data and external environmental data from the system, as well as management and control data from dams and sluice gates, and use machine learning to estimate the flow distribution and inundation prediction of the waterway network using the observation data, external environmental data, and management and control data as inputs. In waterways where power generation amount for continuous communication can be secured, the measurement and communication equipment itself is used as a communication relay, or the power generation mechanism is used as a power source for the communication infrastructure.SELECTED DRAWING: Figure 3
【課題】データ取得と機械学習による水路管理が望ましいが、下水道や山間部などのアクセスの悪い地点において比較的簡単に設置でき、流量や水位データを取得するメンテナンスフリーかつ流水発電可能な計測通信システムがなかったために水路各所のデータ取得が困難だった。また、停電時にも機能する通信網が災害対策として望ましい。【解決手段】メンテナンスフリーかつ流水発電可能な計測通信システムを水域各所に設置し、そこからの観測データと外部環境データや、ダムや水門等の管理制御データを取得して機械学習により学習し、観測データと外部環境データと管理制御データを入力として水路網の流量分布や氾濫の予測を推定することを目的とする。また、継続的な通信を行う発電量が確保できる水路では計測通信機そのものを通信中継機として、あるいは発電機構を通信インフラの電源とする【選択図】図３
PREDICTION PROGRAM AND WATERWAY MANAGEMENT SYSTEM BASED ON LEARNING MODEL OF WATERWAY CONTROL
水路制御の学習モデルによる予測プログラムおよび水路管理システム
UEDA KEISHIRO (Autor:in) / UEDA TAKEJI (Autor:in)
19.08.2021
Patent
Elektronische Ressource
Japanisch
British Library Online Contents | 2007