Mutao Huang

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In multi-objective particle swarm optimization (MOPSO) methods, selecting good local guides (the global best particle) for each particle of the population from a set of Pareto-optimal solutions has a great impact on the convergence and diversity of solutions. This paper introduces the particle angle division method as a new method for finding the global(More)
Large amounts of valuable geosciences data have been collected due to the advances in digital earth technology. How to provide an efficient way through which researchers can easily retrieve desired data to facilitate data analysis and system modeling poses great challenges to the geosciences community. This paper presents a Geo-web services based system(More)
The support vector regression (SVR) is a novel and robust machine learning approach that has been successfully applied to solve problems related to river flow forecasting. However, an important step in the SVR modeling methodology that has received little attention is the selection of appropriate model inputs. This paper presents an input determination(More)
To tackle the problems of low modeling efficiencies involved in implementing runoff forecasting using conventional modeling technologies, a visual modeling tool is established by integrating a visual modeling editor with the artificial neural network (ANN) modular to support interactive and fast modeling of the complex and dynamic runoff process. The(More)
In order to address the problems involved in low modeling efficiencies and complex programming design involved in implementing runoff forecasting using conventional modeling technologies,this paper presents a novel visual modeling system that integrates the visual modeling technology with the support vector machine (SVM) based model with the purpose of(More)
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