The "所向吳敵" team (members: Wang Hung-Ta, Li Tsung-Ching, Hsu Yu-Yu, and Liao Cian-Ying; advisor: Professor Wu Cheng-Hung) demonstrated outstanding performance at the 2024郵政大數據競賽, earning the 最佳創意獎 and the 叡揚數據應用創新獎.
In the final round, the team focused on the "Optimal Placement Analysis for iBox" project, analyzing millions of data points provided by the organizers to determine optimal site locations based on multiple influencing factors. The team began with a preliminary analysis using Multiple Linear Regression (MLR) to identify the most impactful indicators and establish a profitability framework. They then take the Autoregressive Integrated Moving Average (ARIMA) model to forecast scenarios where iBox might reach full capacity. Finally, Nonlinear Programming (NLP) was used to integrate multi-layered predictive results, balancing revenue optimization and coverage to derive the optimal analytical solution.
The team's precise predictions and clear presentation earned high praise from the judges, ultimately securing the 最佳創意獎 and the 叡揚數據應用創新獎, showcasing their innovative capabilities and professional expertise in data analytics and application.
