An Artificial Neural Network (ANN) model trained using a Microsoft dataset is integrated with an AnyLogic simulation environment to predict patient Length of Stay (LOS) in real time. The workflow begins by preprocessing historical hospital data in Python, followed by constructing and training the ANN model using appropriate input variab
Real-time SimPy control plane to dynamically update parameters and stream outputs via external systems like Kafka, Redis, or Postgres. Built for event-driven digital twins.
Traceable, tool-building discrete-event simulation toolkit for SimPy models, exposed over MCP.
This project implements and evaluates Deep Reinforcement Learning agents (DQN and PPO) for managing replenishment policies in a two-product warehouse system, comparing their performance against classical (s,S) baseline policies.
Discrete-event simulator for medical emergency department resource allocation
🩺 Simulate medical resource allocation in hospitals, optimizing ICU beds and ventilators for critical and non-critical patients using humane hybrid logic.
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