id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
animalrev-24	KAYGISIZ, Ferhan ; SEZGİN, Funda Hatice 	Forecasting Goat Milk Production in Turkey Using Artificial Neural Networks and Box-Jenkins Models	2017	8	.pdf	application/pdf	4041	211	50	In this study, future forecasts for goat milk production data were made and their compatibility was assessed by ARMA (Autoregressive Moving Average) which is one of the Box-Jenkins models frequently used in time series analyses and applied to level data, and ARIMA (Autoregressive Integrated Moving Average) methods applied to differentiated data along with ANN (Artificial neural networks models). 3. RESULTS AND DISCUSSION Various models were tested to determine the most appropriate model for a ten-year prospective estimation using goat milk production data between 1961 and 2016 and an estimation method was developed by comparing them.	cache/animalrev-24.pdf	txt/animalrev-24.txt
