prediction of natural gas price using gmdh type neural network:a case study of usa market

نویسندگان

hamid abrishami

fatemeh bourbour

ma’asoumeh aghajani

چکیده

in this paper, a model based on gmdh type neural network, is used to predict gas price in the spot market while using oil spot market price, gas spot market price, gas future market price, oil future market price and average temperature of the weather. the results suggest that gmdh neural network model, according to the root mean squared error (rmse) and direction statistics (dstat) statistics are more effective than ols method. also, first lag of gas price in the future market is the most efficient variable in predicting gas price in spot market.

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عنوان ژورنال:
the international journal of humanities

ناشر: tarbiat modarres university

ISSN 1735-5060

دوره 21

شماره 3 2015

میزبانی شده توسط پلتفرم ابری doprax.com

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