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Thailand has been ranked as one of the most dangerous countries in terms of death from road accidents, representing ineffective road safety policies. The crucial mission of the Thai government is to provide safety and reduce accidents for road users on the highway system. This paper aims to explore the potential of using Business Intelligence (BI) in accident analysis. The availability of open accident data provides an opportunity for the BI, which can provide an advanced platform for conducting data visualization and analytics in both spatial and temporal dimensions in order to illustrate when and where the accidents occur. The accident data and provincial data were combined by using the Talend Data Integration tool. The combined data was then loaded into a MySQL database for data visualization using Tableau. The dashboard was designed and created by using Tableau as an analytical visualization tool to provide insights into highway accidents. This system is advised to be adopted by the Thai government, which can be used for data visualization and analytics to provide a mechanism to formulate strategy options and formulate appropriate contingency plans to improve the accident situation. [ABSTRACT FROM AUTHOR]

Rubber price instability causes great economic problems for rubber plantation in Thailand. Intercropping is an alternative way for rubber farmers in problem-solving. In this paper, we established decision-making system for plant selection in rubber fields under social, economic, and environment criteria with the use of fuzzy multicriteria decision-making (FMCDM) to rank plant options. Firstly, we modified the traditional FMCDM by defuzzification with norm centroid and developed the fuzzifier maps the norm centroid to triangular fuzzy number (TFN). According to fuzzification, the final rating evaluation of plant options are determined by total utility values. Finally, ranking of the plant options is obtained. Our modifications provided an alternative decision-making process with softer computational capability compared with the traditional method. In addition to soft computing, data visualization and analysis of the possibility in each factors could be investigated. This decision-making system was implemented in Phang-Nga Province, Thailand. Its outputs assisted the rubber farmer in selecting suitable plants for cultivation. Pros and cons of each plant options and area-based approaches were easily seen by data visualizations. This decision-making system provided beneficial information which support precision developments for rubber farmer and government agencies. [ABSTRACT FROM AUTHOR]

The functional data model has recently received increasing attention particularly in their application to mortality forecasting. The advantage of this method over the well-known Lee-Carter model is the ability to treat the underlying process as functional, and provide estimations that are robust to outliers. This research investigates the accuracy of functional data approach in estimating the mortality rates and life expectancy at births in developing countries including Malaysia, Indonesia, Thailand and Singapore. The functional data method was applied to these countries' mortality data, and the out-sample forecast errors showed that, in terms of overall, the functional data model was more accurate than that of the original Lee-Carter model for males and females. The results provide evidence that the functional model is accurate to forecast the life expectancy at births for developing countries. [ABSTRACT FROM AUTHOR]