Forecasting The Quarterly Production Of Rice And Corn In Davao del Sur: A Time Series Analysis

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DC Field	Value	Language
dc.contributor.author	Caquilala, Cedric M.	-
dc.date.accessioned	2024-05-06T05:41:11Z	-
dc.date.available	2024-05-06T05:41:11Z	-
dc.date.issued	2023-07	-
dc.identifier.uri	http://dspace.cas.upm.edu.ph:8080/xmlui/handle/123456789/2684	-
dc.description.abstract	Time Series Analysis is a valuable tool in making informed decisions. The Philippines would greatly benefit in using this for crop production, especially rice and corn, since the country is a large producer and consumer said products. The study aims to develop a system that predicts rice and corn production using datasets from Davao del Sur using SARIMA, Bayesian SARIMA, Holt-Winters, and LSTM. The obtained models provide, at the lowest, an 8.42% MAPE for rice and 19.87% MAPE for corn. In addition, the system developed allows the user to develop their own models.	en_US
dc.subject	Time series analysis	en_US
dc.subject	SARIMA	en_US
dc.subject	Bayesian SARIMA	en_US
dc.subject	Holt-Winters	en_US
dc.subject	Long Short-Term Memory (LSTM)	en_US
dc.title	Forecasting The Quarterly Production Of Rice And Corn In Davao del Sur: A Time Series Analysis	en_US
dc.type	Thesis	en_US
Appears in Collections:	Computer Science SP

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