FdAI: Demand Forecast Model for Medical Tourism in India

Forecasting is involved in the estimation of statements about particular events concerned those are uncertain events or computation of future. The ultimate purpose ofthe forecasting model is to acquire knowledge about uncertain events. Medical tourism is an emerging economy in several countries with incipient of apatient from one country to diverse countries for medical needs. However, due to the pandemic of COVID-19 patients were subjected to peregrinate restrictions that affect the movement of people. In this scenario, room booking is a substantial concern for the management of resources to withstand demand for those who are engaged in medical tourism. This paper presented a Forecast Demand Artificial Intelligence (FdAI) model for demand forecasting. The proposed FdAI model incorporates a Q-learning-based reinforcement learning model for the automatic computation of demand estimation. The proposed FdAI model remains processed with ARIMA, SARIMA, and Prophet model for accurate of demand forecast related to medical tourism. Proposed FdAI–ARIMA provides the standard error value variance of 0.0001527, the statistics variance value of 8.5467 witha p-value of 1.2671e− 17. The simulation analysis expressed that the proposed FdAI model accurately estimates the demand higher month with minimal Mean square error. Also, the proposed FdAI computed that demand forecasting becomes significantly increased in the upward trend. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd 2024.