Long-term prediction of discharges in Manwan Reservoir using artificial neural network models

Author name used in this publication: Kwokwing Chau2004-2005 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

A comparison of performance of several artificial intelligence methods for forecasting monthly discharge time series

Author name used in this publication: Chun-Tian Cheng2009-2010 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

Long-term prediction of discharges in Manwan Hydropower using adaptive-network-based fuzzy inference systems models

Author name used in this publication: Chun-Tian ChengAuthor name used in this publication: Ying-Guang SunAuthor name used in this publication: Kwokwing ChauAuthor name used in this publication: Jian-Yi Lin2004-2005 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

Evaluation of several algorithms in forecasting flood

Series: Lecture notes in computer scienceAuthor name used in this publication: K.W. Chau2005-2006 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

A split-step particle swarm optimization algorithm in river stage forecasting

Author name used in this publication: K. W. Chau2007-2008 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

Using Predictive Model for Strategic Control of Multi-reservoir System Storage Capacity

AbstractThe paper will describe the algorithm based on adaptive optimization of multi reservoir control, which the medium-term water flow predictions into the reservoirs for several months ahead repeatedly use. Hydrological prediction model was created using ANN method and values of control outflows are searching by optimization based on evolutionary algorithms optimization technique. The objective function was descripted as the sum of squares deviations between required and actual controlled water outflow from reservoirs where objective function is minimized. The algorithm of adaptive control is applied to the operation storage control of selected reservoir system, which open water reservoirs Vir and Brno are created

Predicting monthly streamflow using data-driven models coupled with data-preprocessing techniques

Author name used in this publication: K. W. Chau2009-2010 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

Prediction of construction litigation outcome using a split-step PSO algorithm

2006-2007 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

Evaluation of Several Algorithms in Forecasting Flood

Precise flood forecasting is desirable so as to have more lead time for taking appropriate prevention measures as well as evacuation actions. Although conceptual prediction models have apparent advantages in assisting physical understandings of the hydrological process, the spatial and temporal variability of characteristics of watershed and the number of variables involved in the modeling of the physical processes render them difficult to be manipulated other than by specialists. In this study, two hybrid models, namely, based on genetic algorithm-based artificial neural network and adaptive-network-based fuzzy inference system algorithms, are employed for flood forecasting in a channel reach of the Yangtze River. The new contributions made by this paper are the application of these two algorithms on flood forecasting problems in real prototype cases and the comparison of their performances with a benchmarking linear regression model in this field. It is found that these hybrid algorithms with a “black-box” approach are worthy tools since they not only explore a new solution approach but also demonstrate good accuracy performance.Department of Civil and Environmental EngineeringSeries: Lecture notes in computer scienceAuthor name used in this publication: K.W. Cha