Selected hybrid nonlinear model for the maximum simultaneous electric power demand in a developing country

G. Shakouri, J. Nazarzadeh, S. Nikravesh
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Abstract

Governments are interested in energy supply industry and so consider it essential to predict energy demand, as well as the private sector. Solution of the problem depends on availability of a model. This paper proposes a systematically developed model. It is based on a previously performed exogeneity investigation of various quantified variables. A certain nonlinear model among a collection of 100 models with different inputs is chosen as the most appropriate model. Structure of all nonlinear competing models is established according to logical conjunctive and disjunctive relationships between variables. Different combinations of the exogenous variables generate these models. At first, unacceptable models are put away applying coefficient sign significance criterion and error validity. An automated fuzzy decision-making process determines the winner model, which is a hybrid nonlinear model, among the other remaining models.
选取发展中国家最大同时电力需求的混合非线性模型
各国政府对能源供应行业很感兴趣,因此认为预测能源需求至关重要,私营部门也是如此。问题的解决取决于模型的可用性。本文提出了一个系统发展的模型。它是基于以前执行的各种量化变量的外生性调查。从100个不同输入的非线性模型中选择某一个模型作为最合适的模型。根据变量之间的逻辑合取关系建立了所有非线性竞争模型的结构。外生变量的不同组合产生了这些模型。首先采用系数、符号显著性准则和误差效度准则对不可接受的模型进行处理。一个自动化的模糊决策过程决定了获胜者模型,这是一个混合非线性模型,在其他模型中。
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