TY - JOUR ID - 1262 TI - Forecasting Gold Price using Data Mining Techniques by Considering New Factors JO - Journal of AI and Data Mining JA - JADM LA - en SN - 2322-5211 AU - Hatamlou, A.R. AU - Deljavan, M. AD - Department of Computer Science, Khoy Branch, Islamic Azad University, Khoy, Iran. AD - Department of Computer Science, Urmia Branch, Islamic Azad University, Urmia, Iran. Y1 - 2019 PY - 2019 VL - 7 IS - 3 SP - 411 EP - 420 KW - Gold price forecast KW - data mining KW - time series KW - neural networks KW - regression DO - 10.22044/jadm.2018.6114.1727 N2 - Gold price forecast is of great importance. Many models were presented by researchers to forecast gold price. It seems that although different models could forecast gold price under different conditions, the new factors affecting gold price forecast have a significant importance and effect on the increase of forecast accuracy. In this paper, different factors were studied in comparison to the previous studies on gold price forecast. In terms of time span, the collected data were divided into three groups of daily, monthly and annually. The conducted tests using new factors indicate accuracy improvement up to 2% in neural networks methods, 7/3% in time series method and 5/6% in linear regression method. UR - https://jad.shahroodut.ac.ir/article_1262.html L1 - https://jad.shahroodut.ac.ir/article_1262_c0e3e477464bd17e86b6e558947ce238.pdf ER -