
Wenxin enhanced the DSA3101-Group-Project-Group-3 repository by developing a data-driven simulation feature that updates attraction weights based on real wait-time data and introduces zone-aware ride selection. Using Python, Wenxin applied algorithm optimization and data simulation techniques to replace static dummy weights with dynamic metrics, resulting in more accurate modeling of ride popularity. The new logic prioritizes ride selection within each zone, reflecting realistic visitor behavior and supporting improved capacity planning. All changes were consolidated into a single, traceable commit, demonstrating a focused and reproducible engineering approach. The work addressed simulation realism without introducing new bugs during the period.

March 2025 Performance Summary: Delivered a data-driven enhancement to the DSA3101 project by updating attraction weights using real wait-time data and introducing zone-aware ride selection. These changes increase the accuracy of ride popularity metrics and improve the realism of the visitor-choice simulation, enabling better capacity planning and strategic decision-making. All work is tracked in a single change set for traceability.
March 2025 Performance Summary: Delivered a data-driven enhancement to the DSA3101 project by updating attraction weights using real wait-time data and introducing zone-aware ride selection. These changes increase the accuracy of ride popularity metrics and improve the realism of the visitor-choice simulation, enabling better capacity planning and strategic decision-making. All work is tracked in a single change set for traceability.
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