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- W2183379551 abstract "According to the increasing demand of energy as a vital input for industrial sector, the assessment of energy demand is necessary for industrial activities in the country. This assessment could be done based on econometric approaches using different models of mathematical demonstration. Because of non-linear behavior of socio-economic indicators, the energy demand could be assessed by the non-linear forms more effectively. In this study Multi-Layer Perceptron Neural Networks (MLPNN) and Adaptive Network Based Fuzzy Inference System (ANFIS) are used to model Iranian Metal Industries Energy Demand (IMIED) based on socio-economic indicators. Number of employees persons, total investments, value added, gas price, and electricity price are used as socio-economic indicators in this study." @default.
- W2183379551 created "2016-06-24" @default.
- W2183379551 creator A5024607958 @default.
- W2183379551 date "2014-01-01" @default.
- W2183379551 modified "2023-09-24" @default.
- W2183379551 title "Iranian Metal Industries Energy Demand Model: A comparison Between Multi-Layer Perceptron Neural Networks (MLPNN) and Adaptive Network Based Fuzzy Inference System (ANFIS)" @default.
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- W2183379551 hasPublicationYear "2014" @default.
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