Developed and maintained the NotInvalidUsername/DSA3101_Group8_Project1 repository, delivering a theme park simulation platform using agent-based modeling and queueing theory. Built a scalable 9x9 park model with dynamic guest movement and ride positioning, integrating predictive data pipelines for attraction demand forecasting. Enhanced the project with Streamlit-based UI demos, automated testing assets, and comprehensive data preprocessing leveraging Python, Pandas, and SimPy. Improved code quality through iterative refactoring, dependency management, and documentation updates. Expanded analytics with advanced visualizations and runtime optimizations, supporting clearer stakeholder communication and faster validation. Addressed bugs and maintained reproducibility by restoring critical assets and restructuring the codebase.
April 2025: End-to-end development across testing assets, UI demonstration, modeling enhancements, and maintainability improvements, delivering tangible business value through faster validation, clearer stakeholder demos, and scalable analytics.
April 2025: End-to-end development across testing assets, UI demonstration, modeling enhancements, and maintainability improvements, delivering tangible business value through faster validation, clearer stakeholder demos, and scalable analytics.
March 2025 performance summary for NotInvalidUsername/DSA3101_Group8_Project1. Delivered foundational agent-based model (ABM) core for a theme park simulation, including queueing, dynamic guest movement, fixed ride locations, and a dynamic ride-position model within a scalable 9x9 park footprint. Established groundwork for integrating queue theory and ride optimization, enabling more accurate capacity planning and experience modeling. Built a Predictive Model Data Pipeline for Attraction Demand with extensive preprocessing and feature engineering across incidents, weather, disasters, holidays, and attendance to support demand forecasting. Restored critical simulation notebook to maintain continuity after accidental deletion and preserved project reproducibility. Improved code quality and maintainability through iterative commits and repository hygiene.
March 2025 performance summary for NotInvalidUsername/DSA3101_Group8_Project1. Delivered foundational agent-based model (ABM) core for a theme park simulation, including queueing, dynamic guest movement, fixed ride locations, and a dynamic ride-position model within a scalable 9x9 park footprint. Established groundwork for integrating queue theory and ride optimization, enabling more accurate capacity planning and experience modeling. Built a Predictive Model Data Pipeline for Attraction Demand with extensive preprocessing and feature engineering across incidents, weather, disasters, holidays, and attendance to support demand forecasting. Restored critical simulation notebook to maintain continuity after accidental deletion and preserved project reproducibility. Improved code quality and maintainability through iterative commits and repository hygiene.
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