Huynh Ngoc Phien

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Flood forecasting remains a very important task. Good forecast values with sufficient lead times can help reduce flood damages significantly. This paper proposes two types of black-box model obtained by using multiple regression analysis and back-propagation neural networks in forecasting 6-h water levels at three important stations on the upstream section(More)
Although various techniques and materials have been used for making cranioplasty implants, personalized cranioplasty implants are high in cost because of expensive materials and production technology, long design and manufacturing time, and intensive labor use. This research was a part of our research project in ASEAN countries to investigate feasible(More)
Currently, there are numerous effective models for managing error propagation in data manipulation and analysis. But the method is still lack in handling spatial consistency. This paper focuses on the algorithms and models of error propagation for spatial consistency, investigating the basic types of spatial data inconsistency and the procedures for(More)
Skull defects are treated by cranioplasty techniques, which are required to protect underlying brain, correct major aesthetic deformities, or both. This research is a part of our research project in ASEAN countries to investigate (i) the methods for design and manufacturing of cranioplasty implants, and (ii) the feasible technical solutions of minimizing(More)
A new approach based on vector field clustering for tool path optimization of 5-axis CNC machining is presented in this paper. The strategy of the approach is to produce an efficient tool path with respect to the optimal cutting direction vector field. The optimal cutting direction maximizes the machining strip width. We use the normalized cut clustering(More)
The amount of water stored in a reservoir can be utilized more efficiently if it is possible to forecast future inflows. However, not many techniques for seasonal streamflow forecasting have been devised. Recently, a particular scheme has been introduced, in which regression analysis is used in model identification and parameter estimation, and a time(More)
In this study, we explore the use of Knowledge Based Artificial Neural Networks (KBANN), pioneered by Shavlik and Towell, 1994 [25], to learn user preferences under certainty. We start by describing the problem of choosing a used motorcar, where it is reasonable to make several assumptions about preferential independence and monotonicity. We then show how(More)