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A platform for research: civil engineering, architecture and urbanism
WATER LEVEL PREDICTION DEVICE IN SEWER PIPE, WATER LEVEL PREDICTION METHOD IN SEWER PIPE, AND WATER LEVEL PREDICTION PROGRAM IN SEWER PIPE
To aim for high-precision prediction that appropriately characterizes bidirectional changes in both the spatial direction and time direction in predicting a water level in sewer pipes, while suppressing the time and cost of a prediction model construction.SOLUTION: In a water level prediction device 10 in the sewer pipe drain, a prediction input data generating unit 15 predicts the water level in the sewer pipe of a predicted target point by converting the data group of the actual value and the predicted value including the predicted target point at the local time into an applicable folded form processing to create a prediction input data to be subjected to a folded neural network of the water level prediction value calculating unit 16 to be measured. A folded process and the MaxPooling process is performed for the prediction input data in predicting the water level in the sewer pipe in the folded neural network. Then, the water level in the sewer pipe of the predicted target point is predicted based on data of processing result of MaxPooking and data of the water level of the measurement point vicinity of the predicted target point.SELECTED DRAWING: Figure 1
【課題】下水道管渠内水位の予測にあたり、予測モデル構築の時間とコストを抑えながら、空間方向および時間方向、双方向の変化を適切に特徴量化した高精度な予測を図る。【解決手段】下水道管渠内水位予測装置１０において、予測入力データ生成部１５は予測対象地点を含む地域の時刻の異なるメッシュ降水量の実況値及び予測値のデータ群を畳み込み処理の適用可能な形式に変換することにより当該予測対象地点の下水道管渠内水位を予測する水位予測値算出部１６の畳み込みニューラルネットワークに供される予測用入力データを作成する。前記畳み込みニューラルネットワークにおいて前記下水道管渠内水位を予測にあたり前記予測用入力データに対して畳み込み処理及びMaxPooling処理が施される。次いで、MaxPooling処理結果のデータと予測対象地点の近傍測定点の下水道管渠内水位データとから当該予測対象地点の下水道管渠内水位を予測する。【選択図】図１
WATER LEVEL PREDICTION DEVICE IN SEWER PIPE, WATER LEVEL PREDICTION METHOD IN SEWER PIPE, AND WATER LEVEL PREDICTION PROGRAM IN SEWER PIPE
To aim for high-precision prediction that appropriately characterizes bidirectional changes in both the spatial direction and time direction in predicting a water level in sewer pipes, while suppressing the time and cost of a prediction model construction.SOLUTION: In a water level prediction device 10 in the sewer pipe drain, a prediction input data generating unit 15 predicts the water level in the sewer pipe of a predicted target point by converting the data group of the actual value and the predicted value including the predicted target point at the local time into an applicable folded form processing to create a prediction input data to be subjected to a folded neural network of the water level prediction value calculating unit 16 to be measured. A folded process and the MaxPooling process is performed for the prediction input data in predicting the water level in the sewer pipe in the folded neural network. Then, the water level in the sewer pipe of the predicted target point is predicted based on data of processing result of MaxPooking and data of the water level of the measurement point vicinity of the predicted target point.SELECTED DRAWING: Figure 1
【課題】下水道管渠内水位の予測にあたり、予測モデル構築の時間とコストを抑えながら、空間方向および時間方向、双方向の変化を適切に特徴量化した高精度な予測を図る。【解決手段】下水道管渠内水位予測装置１０において、予測入力データ生成部１５は予測対象地点を含む地域の時刻の異なるメッシュ降水量の実況値及び予測値のデータ群を畳み込み処理の適用可能な形式に変換することにより当該予測対象地点の下水道管渠内水位を予測する水位予測値算出部１６の畳み込みニューラルネットワークに供される予測用入力データを作成する。前記畳み込みニューラルネットワークにおいて前記下水道管渠内水位を予測にあたり前記予測用入力データに対して畳み込み処理及びMaxPooling処理が施される。次いで、MaxPooling処理結果のデータと予測対象地点の近傍測定点の下水道管渠内水位データとから当該予測対象地点の下水道管渠内水位を予測する。【選択図】図１
WATER LEVEL PREDICTION DEVICE IN SEWER PIPE, WATER LEVEL PREDICTION METHOD IN SEWER PIPE, AND WATER LEVEL PREDICTION PROGRAM IN SEWER PIPE
下水道管渠内水位予測装置、下水道管渠内水位予測方法及び下水道管渠内水位予測プログラム
KIMURA YUKI (author) / FUKAI HIRONAGA (author)
2019-06-20
Patent
Electronic Resource
Japanese
Water turning method to sewer pipe and ater turning device to sewer pipe
| European Patent Office | 2018
| Engineering Index Backfile | 1929