Page 92 - Contributed Paper Session (CPS) - Volume 1

CPS1119 Fethi Şaban ÖZBEK
Method: Neural Networks
Records used in training: 116
Model type: Classification
User: ---
Application: IBM SPSS Modeler Common 15.0.0.3
Date built: October 31, 2018 2:36:57 PM AST
Predictors used in model
Price -1

ANN models were effective for forecasting agricultural commodity prices in
that all accuracies were very high; 99.2, 90.9, 99.0, 91.7 for wheat, barley, maize
(seed), and raw cotton, respectively.
Applying the above models of ANN, the forecasting results for the period
from October 2018 (2018-Oct.) to December 2019 (2019-Dec.) are shown in
Figure 1. The results of forecasting models show that the prices of wheat
fluctuate between 0.97 TL/KG and 0.93 TL/kg between 2018-October and
2019-December. And the prices fluctuate between 0.84 TL/KG and 0.81 TL/kg,
0.87 TL/kg and 0.84 TL/kg, 2.26 TL/kg and 2.24 TL/kg for maize (seed), barley
and raw cotton, respectively.

Wheat price (TL/kg) Maize (seed) price
(TL/kg)
1.2
1.0 1
0.8 0.8
0.6 0.6
0.4 0.4
0.2 0.2
0.0 0
2009-Jan. 2010-Apr. 2011-July 2012-Oct. 2014-Jan. 2015-Apr. 2016-July 2017-Oct. 2019-Jan. 2009-Jan. 2010-Mar. 2011-May 2012-July 2013-Sep. 2014-Nov. 2016-Jan. 2017-Mar. 2018-May 2019-July

Barley price (TL/kg) Raw cotton price
(TL/kg)
1.0
0.8 3.0
0.6 2.0
0.4
0.2 1.0
0.0 0.0 2010-… 2014-… 2017-…
2009-Jan. 2010-Apr. 2011-July 2012-Oct. 2014-Jan. 2015-Apr. 2016-July 2017-Oct. 2019-Jan. 2009-Jan. 2011-May 2012-July 2013-Sep. 2016-Jan. 2018-May 2019-July

Fig. 1. Prices of wheat, barley, maize (seed), and raw cotton, 2009-Jan.-2019-Dec., TL/kg

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