2010
DOI: 10.1016/j.apenergy.2009.07.008
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Modeling and estimation of the natural gas consumption for residential and commercial sectors in Iran

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Cited by 109 publications
(61 citation statements)
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“…In 2007, industrial use accounted for 54% of the Brazilian natural gas demand [15]. The participation of home consumption in Brazil's energy matrix is very small when compared with countries such as Poland [16], Iran [9] and Turkey [17]. Aydinalp et al [18] used neural network (NN) to model residential energy consumption in Canada.…”
Section: Consumption Of Natural Gasmentioning
confidence: 99%
See 1 more Smart Citation
“…In 2007, industrial use accounted for 54% of the Brazilian natural gas demand [15]. The participation of home consumption in Brazil's energy matrix is very small when compared with countries such as Poland [16], Iran [9] and Turkey [17]. Aydinalp et al [18] used neural network (NN) to model residential energy consumption in Canada.…”
Section: Consumption Of Natural Gasmentioning
confidence: 99%
“…The logistic model [9] was used to model annual and seasonal natural gas consumption for residential and commercial sectors in Iran. The logistics parameters were estimated using optimization techniques as NLP (nonlinear programming) and GA (genetic algorithm).…”
Section: Logistic Modelmentioning
confidence: 99%
“…The effect of energy policy on the different segments of consumers can be studied based on the way these different segments consume this energy source. A substantial amount of effort has been put into the gas demand forecasting [11][12][13][14][15][16] and into the determinant factors of residential gas consumption [17,18]. The study of energy savings has been conducted for buildings, as well, mostly inserted in projects for the development of sustainable cities [19,20].…”
Section: Introductionmentioning
confidence: 99%
“…As new techniques of energy demand forecasting they discussed Support vector regression, ant colony and particle swarm [15]. These models can be categorized into three main approaches: time-series approach [3,9], econometric approach [7, 12,] and artificial intelligence (AI) approach [14].…”
Section: Introductionmentioning
confidence: 99%