نمایش مختصر رکورد

dc.contributor.authorQanbari, Mahdiehen_US
dc.contributor.authorJavadi, Shahramen_US
dc.contributor.authorSabbaghi-Nadooshan, Rezaen_US
dc.date.accessioned1399-07-09T06:45:06Zfa_IR
dc.date.accessioned2020-09-30T06:45:06Z
dc.date.available1399-07-09T06:45:06Zfa_IR
dc.date.available2020-09-30T06:45:06Z
dc.date.issued2013-08-01en_US
dc.date.issued1392-05-10fa_IR
dc.date.submitted2015-04-13en_US
dc.date.submitted1394-01-24fa_IR
dc.identifier.citationQanbari, Mahdieh, Javadi, Shahram, Sabbaghi-Nadooshan, Reza. (2013). The Forecasting of Iran Natural Gas Consumption Based On Neural-Fuzzy System Until 2020. International Journal of Smart Electrical Engineering, 02(3), 181-184.en_US
dc.identifier.issn2251-9246
dc.identifier.issn2345-6221
dc.identifier.urihttp://ijsee.iauctb.ac.ir/article_510111.html
dc.identifier.urihttps://iranjournals.nlai.ir/handle/123456789/308607
dc.description.abstractIn this paper, an Adaptive-Network-based Fuzzy Inference System (ANFIS) is used for forecasting of natural gas consumption. It is clear that natural gas consumption prediction for future, surly can help Statesmen to decide more certain. There are many variables which effect on gas consumption but two variables that named Gross Domestic Product (GDP) and population, are selected as two input variables. The input variables data and output variable (gas consumption) data are collected in years 1993 till 2012. Pre-process is done on the primary data to obtain better results then finally our outputs are post-processed. In this paper, many fuzzy models are applied and the results and error of every model are investigated. All ANFIS outputs are compared with real output by considering Mean Absolute Percentage Error (MAPE). The best model, which has the lowest MAPE, is chosen for forecasting gas consumption. In this paper, the values of gas consumption are forecasted from 2013 to 2020en_US
dc.format.extent1084
dc.format.mimetypeapplication/pdf
dc.languageEnglish
dc.language.isoen_US
dc.publisherIslamic Azad University,Central Tehran Branchen_US
dc.relation.ispartofInternational Journal of Smart Electrical Engineeringen_US
dc.subject(ANFIS)en_US
dc.subjectNatural Gas Consumptionen_US
dc.subjectGDPen_US
dc.titleThe Forecasting of Iran Natural Gas Consumption Based On Neural-Fuzzy System Until 2020en_US
dc.typeTexten_US
dc.contributor.departmentDepartment of Electrical Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran.en_US
dc.contributor.departmentAssistant Professor, Electrical Engineering Dept., Islamic Azad University, Central Tehran Branch, Tehran, Iranen_US
dc.contributor.departmentAssistant Professor, Electrical Engineering Dept., Islamic Azad University, Central Tehran Branch, Tehran, Iranen_US
dc.citation.volume02
dc.citation.issue3
dc.citation.spage181
dc.citation.epage184
nlai.contributor.orcid0000-0002-5950-8592


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