Amanote Research

Amanote Research

    RegisterSign In

Real-Time Forecasting for Water Levels in Sewer by Machine Learning and Inundation Simulation

Journal of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering)
doi 10.2208/jscejhe.73.i_649
Full Text
Open PDF
Abstract

Available in full text

Date

January 1, 2017

Authors
Yusuke HIDAHiroshi CHIBAYoshihiro ASAOKAHisao NAGABAYASHI
Publisher

Japan Society of Civil Engineers


Related search

Inundation Simulation for Urban Drainage Basin With Storm Sewer System

Journal of Hydrology
Water ScienceTechnology
2000English

Machine Learning for Real-Time Decision Making

2001English

Real-Time Forecasting

2011English

Artificial Intelligence, Machine Learning and Real-Time Probabilistic Data for Cyber Risk (Super) -Forecasting: Red Teaming the Connected World (RETCON)

2020English

Evaluation of VI Index Forecasting Model by Machine Learning for Yahoo! Stock BBS Using Volatility Trading Simulation

2020English

A Machine Learning Approach to Univariate Time Series Forecasting of Quarterly Earnings

Review of Quantitative Finance and Accounting
AccountingManagementFinanceBusiness
2020English

Real-Time Water Demand Forecasting System Through an Agent-Based Architecture

International Journal of Bio-Inspired Computation
Computer ScienceTheoretical Computer Science
2015English

Real Time Electrocardiogram Identification With Multi-Modal Machine Learning Algorithms

Lecture Notes on Data Engineering and Communications Technologies
2017English

Graph Theory Algorithms for Real Time Control of a Sewer Network

English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2025 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy