A Forecasting Model for Deciding Annual Vaccine Demand

Autor:	Chi-Ming Chang, Ruey-kei Chiu, Yen-Chun Chang
Rok vydání:	2008
Předmět:	Decision support system Operations research Artificial neural network Moving average Computer science Autoregressive integrated moving average Immunization (finance) Purchasing
Zdroj:	ICNC (7)
DOI:	10.1109/icnc.2008.862
Popis:	This paper presents a computer-based forecast model for building a decision support system for forecasting the annual vaccine demand of a specific vaccine. The model is formatted by employing a combination technique including the Neural Network and Auto-Regressive Integrated Moving Average. The result generated from the system may be taken by the governmental immunization authority to make a better decision for budgeting and purchasing the annual requirement of specific vaccines.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::604d3256f7d77072322d0262f29b9234 https://doi.org/10.1109/icnc.2008.862 Zobrazit plný text záznamu