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Modeling and forecasting long-term natural gas (NG) consumption in Iran, using particle swarm optimization (PSO)
2010 (English)Independent thesis Advanced level (degree of Master (Two Years))Student thesis
Abstract [en]

The gradual changes in the world development have brought energy issues back into high profile. An ongoing challenge for countries around the world is to balance the development gains against its effects on the environment. The energy management is the key factor of any sustainable development program. All the aspects of development in agriculture, power generation, social welfare and industry in Iran are crucially related to the energy and its revenue. Forecasting end-use natural gas consumption is an important Factor for efficient system operation and a basis for planning decisions. In this thesis, particle swarm optimization (PSO) used to forecast long run natural gas consumption in Iran. Gas consumption data in Iran for the previous 34 years is used to predict the consumption for the coming years. Four linear and nonlinear models proposed and six factors such as Gross Domestic Product (GDP), Population, National Income (NI), Temperature, Consumer Price Index (CPI) and yearly Natural Gas (NG) demand investigated.

Place, publisher, year, edition, pages
2010. , 56 p.
Keyword [en]
Modeling, Forecasting, Natural Gas (NG), Particle Swarm Intelligence (PSO), Iran
Identifiers
URN: urn:nbn:se:du-5085OAI: oai:dalea.du.se:5085DiVA: diva2:518957
Uppsok
Technology
Supervisors
Available from: 2010-11-16 Created: 2010-11-16 Last updated: 2015-12-07Bibliographically approved

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf