Woon Yang Tan's research while affiliated with University of Kuala Lumpur and other places

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Publications (3)

Figure 1. Architecture of LSTM blocks.
Figure 3. Firefly algorithm flowchart. Figure 3. Firefly algorithm...
Figure 5. Map of study location at the Klang River Catchment. The flash...
Best LSTM and ANN models for prediction.
+3 LSTM forecasting models.
Three Steps towards Better Forecasting for Streamflow Deep Learning
Article
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  • Dec 2022
Elevating the accuracy of streamflow forecasting has always been a challenge. This paper proposes a three-step artificial intelligence model improvement for streamflow forecasting. Step 1 uses long short-term memory (LSTM), an improvement on the conventional artificial neural network (ANN). Step 2 performs multi-step ahead forecasting while establi...
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A Review on Heavy Duty Mobile Flood Wall Barrier: Way Forward for Malaysia
Chapter
  • Oct 2022
Climate change have led to extreme weather events such as higher rainfall frequency that can cause severe flooding. In Malaysia, there is an increasing trend on extreme rainfall events and short temporal rainfall, particularly during the inter-monsoon season. In order to protect private properties and public premises from flooding, Mobile Flood Wal...
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State-of-the-Art Development of Two-Waves Artificial Intelligence Modeling Techniques for River Streamflow Forecasting
Article
  • Jun 2022
Streamflow forecasting is the most well studied hydrological science but still portray numerous unknown knowledge. The conventional physical-based model is unable to yield a high accuracy of forecast due to the embedded noises, non-linear and stochastic nature of hydrological data. This paper is to review the recent development of the artificial in...
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Citations

... All influencing parameters on flyrock are considered in two categories: controllable and uncontrollable factors, and in order to achieve a reliable attitude, both factors should be assumed [10][11][12]. Inexact drilling, inappropriate blasthole diameter, incorrect powder factor, insufficient stemming, unsuitable delay time, and inadequate data distributions, and simple construction make these models one of the applicable methods in geotechnics [57][58][59]. Pham et al. [60] presented a new model for the classification of soils using Adaboost and enhanced tree methods. For this purpose, they gathered 440 data samples of soil features and achieved acceptable results. ...
Reference: Several Tree-Based Solutions for Predicting Flyrock Distance Due to Mine Blasting
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