prediction of natural gas price using gmdh type neural network:a case study of usa market
Authors
abstract
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.
similar resources
Prediction of pore facies using GMDH-type neural networks: a case study from the South Pars gas field, Persian Gulf basin
The current study proposes a two-step approach for pore facies characterization in the carbonate reservoirs with an example from the Kangan and Dalanformations in the South Pars gas field. In the first step, pore facies were determined based on Mercury Injection Capillary Pressure (MICP) data incorporation with the Hierarchical Clustering Analysis (HCA) method. In the next step, polynomial meta...
full textPrediction of Deformation of Circular Plates Subjected to Impulsive Loading Using GMDH-type Neural Network
In this paper, experimental responses of the clamped mild steel, copper, and aluminium circular plates are presented subjected to blast loading. The GMDH-type neural networks (Group Method of Data Handling) are then used for the modelling of the mid-point deflection thickness ratio of the circular plates using those experimental results. The aim of such modelling is to show how the mid-point de...
full texta study on insurer solvency by panel data model: the case of iranian insurance market
the aim of this thesis is an approach for assessing insurer’s solvency for iranian insurance companies. we use of economic data with both time series and cross-sectional variation, thus by using the panel data model will survey the insurer solvency.
hazard evaluation of gas condensate stabilization and dehydration unit of parsian gas refinery using hazop procedures
شناسایی مخاطرات در واحد 400 پالایشگاه گاز پارسیان. در این پروزه با بکارگیری از تکنیک hazop به شناسا یی مخاطرات ، انحرافات ممکن و در صورت لزوم ارایه راهکارهای مناسب جهت افزایش ایمنی فرا یند پرداخته میگردد. شرایط عملیاتی مخاطره آمیز نظیر فشار و دمای بالا و وجود ترکیبات مختلف سمی و قابل انفجار در واحدهای پالایش گاز، ضرورت توجه به موارد ایمنی در این چنین واحدهایی را مشخص می سازد. مطالعه hazop یک ر...
Forecasting Stock Market Using Wavelet Transforms and Neural Networks and ARIMA (Case study of price index of Tehran Stock Exchange)
The goal of this research is to predict total stock market index of Tehran Stock Exchange, using the compound method of ARIMA and neural network in order for the active participations of finance market as well as macro decision makers to be able to predict trend of the market. First, the series of price index was decomposed by wavelet transform, then the smooth's series predicted by using...
full textMy Resources
Save resource for easier access later
Journal title:
the international journal of humanitiesPublisher: tarbiat modarres university
ISSN 1735-5060
volume 21
issue 3 2015
Hosted on Doprax cloud platform doprax.com
copyright © 2015-2023