Kwok-Wing Chau

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1 Dept. of Civil and Structural Engineering, Hong Kong Polytechnic University, 4 Hung Hom, Kowloon, Hong Kong, People’s Republic of China 5 6 2 Changjiang Institute of Survey, Planning, Design and Research, 7 Changjiang Water Resources Commission, 8 430010, Wuhan, HuBei, People’s Republic of China 9 10 3 Department of Civil Engineering, Ryerson University,(More)
Abstract: In this paper, an efficient approach to search for the global threshold of image using Gaussian mixture model is proposed. Firstly, a gray-level histogram of an image is represented as a function of the frequencies of gray-level. Then,to fit the Gaussian mixtures to the histogram of image, the Expectation Maximization (EM) algorithm is developed(More)
Abstract Accurate timeand site-specific forecasts of streamflow and reservoir inflow are important in effective hydropower reservoir management and scheduling. Traditionally, autoregressive movingaverage (ARMA) models have been used in modelling water resource time series as a standard representation of stochastic time series. Recently, artificial neural(More)
In the recent past, machine learning (ML) techniques such as artificial neural networks (ANN) have been increasingly used to model algal bloom dynamics. In the present paper, along with ANN, we select genetic programming (GP) for modelling and prediction of algal blooms in Tolo Harbour, Hong Kong. The study of the weights of the trained ANN and also the(More)
Currently, the numerical simulation of flow and/or water quality becomes more and more sophisticated. There arises a demand on the integration of recent knowledge management (KM), artificial intelligence technology with the conventional hydraulic algorithmic models in order to assist novice application users in selection and manipulation of various(More)
With the development of computing technology, numerical models are often employed to simulate flow and water quality processes in coastal environments. However, the emphasis has conventionally been placed on algorithmic procedures to solve specific problems. These numerical models, being insufficiently user-friendly, lack knowledge transfers in model(More)
Recently, classifier ensemble methods are gaining more and more attention in the machine-learning and data-mining communities. In most cases, the performance of an ensemble is better than a single classifier. Many methods for creating diverse classifiers were developed during the past decade. When these diverse classifiers are generated, it is important to(More)
Artificial Neural Networks (ANNs) have been successfully employed for predicting and forecasting groundwater levels up to some time steps ahead. In this paper, we present an application of feed forward neural networks (FFNs) for long period simulations of hourly groundwater levels in a coastal unconfined aquifer sited in the Lagoon of Venice, Italy. After(More)
C. L. Wu and K. W. Chau* 2 Dept. of Civil and Structural Engineering, Hong Kong Polytechnic University, 3 Hung Hom, Kowloon, Hong Kong, People’s Republic of China 4 5 *Email: cekwchau@polyu.edu.hk 6 ABSTRACT 7 Data-driven techniques such as Auto-Regressive Moving Average (ARMA), K-Nearest-Neighbors (KNN), and 8 Artificial Neural Networks (ANN), are widely(More)