Healthcare Expenditure Prediction in Turkey by Using Genetic Algorithm Based Grey Forecasting Models

Tuncay Özcan () and Fatih Tüysüz ()
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Tuncay Özcan: İstanbul University
Fatih Tüysüz: İstanbul University

Chapter Chapter 7 in Operations Research Applications in Health Care Management, 2018, pp 159-190 from Springer

Abstract: Abstract This chapter aims to predict the health care expenditure (HCE) per capita which is an important indicator of a country’s health status and economic growth. Accurate estimation of HCE can guide efficient health care policy making and resource allocation. Grey forecasting models are applied for predicting the HCE per capita of Turkey. Three different strategies are proposed which are rolling mechanism, training data size optimization and parameter optimization to improve the forecasting accuracy of these models. Genetic algorithm (GA) which is one of the most widely used meta-heuristic optimization techniques is applied for training data size and parameter optimization of the grey forecasting models. The application results indicate that the optimization of parameters and training data size together with rolling mechanism highly improve the forecasting performance of the grey models.

Keywords: Grey Forecasting Model; Training Data Size; Mechanistic Role; Minimum MAPE; Autoregressive Integrated Moving Average (ARIMA) (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:spr:isochp:978-3-319-65455-3_7

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DOI: 10.1007/978-3-319-65455-3_7

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