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Estimating energy and exergy production and consumption values using three different genetic algorithm approaches. Part 1: Model development

机译:使用三种不同的遗传算法方法估算能源和火用生产和消耗值。第1部分:模型开发

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摘要

The present study, consisting of two parts, proposes new models for estimating energy and exergy production and consumption values using the genetic algorithm approach. Part 1 of this study deals with the model development, while the application and testing with various scenarios will be treated in Part 2. In this regard, the genetic algorithm energy (GAEN) and genetic algorithm exergy (GAEX) estimating models have been proposed. During the energy and exergy estimation, independent variables are the GDP, population, and the ratio of export to import. The three forms of the GAEN and GAEX are developed, of which one is linear, second is exponential and the third is a mix of the exponential and linear form of the equations. Among them, the best fit models in terms of average relative errors and for the testing period are selected for future estimation and proposed both for GAEN and GAEX. It may be concluded that the models proposed here can be used as an alternative solution and estimation techniques to available estimation techniques.
机译:本研究由两部分组成,提出了使用遗传算法方法估算能源和火用生产和消耗值的新模型。本研究的第1部分涉及模型的开发,而第2部分将介绍在各种场景下的应用和测试。在这方面,已经提出了遗传算法能量(GAEN)和遗传算法火用(GAEX)估计模型。在能源和火用能值估计期间,自变量是GDP,人口和进出口比。提出了GAEN和GAEX的三种形式,其中一种是线性的,第二种是指数的,第三种是方程式的指数和线性形式的混合。其中,就平均相对误差和测试期间而言,选择最佳拟合模型以进行未来估算,并针对GAEN和GAEX提出建议。可以得出结论,此处提出的模型可以用作可用估计技术的替代解决方案和估计技术。

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