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Getting efficient choices in buildings by using Genetic Algorithms: Assessment validation

机译:使用遗传算法获得建筑物中的有效选择:评估验证

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The energy consumption in buildings, can be reduced through a rational choice of the household appliances to be acquired. This choice can be based, on a specific criteria, settled according to the consumer needs. However, such choice, still needs to be optimized, since in general, an efficient equipment has a high investment, although a low energy consumption. Genetic Algorithms (GAs) are used therefore, as an optimization technique, to get efficient and several solutions, based on those pre-selected from the market, and according to a set of criteria. However, there is a need to assess its robustness as well as its consistence in terms of convergence results. The quality of its solutions is also assessed, by comparing GAs results with those, obtained from Simplex method. The problem formulation, and its influence on GAs results, is also considered on this work, where it’s chosen the best one, among four proposed. In this paper it is presented a methodology that allows to promote energy efficiency in buildings, by achieving savings in terms of initial investment, energy consumption and CO_(2) emissions for the consumer. It is shown that GAs, can provide several and optimal solutions, through formulation and parameters suitable.
机译:通过合理选择要购买的家用电器,可以减少建筑物中的能源消耗。该选择可以基于特定标准,根据消费者需求来确定。但是,这样的选择仍然需要优化,因为总的来说,尽管能耗低,但高效的设备具有较高的投资。因此,基于从市场上预先选择的遗传算法并根据一组标准,使用遗传算法(GA)作为一种优化技术来获得有效的几种解决方案。但是,需要根据收敛结果评估其健壮性和一致性。通过将GA结果与从Simplex方法获得的结果进行比较,还可以评估其解决方案的质量。这项工作还考虑了问题的表述及其对GA结果的影响,在提出的四项建议中,它被选为最佳解决方案。在本文中,提出了一种方法,该方法可通过为消费者节省初始投资,能耗和CO_(2)排放量来提高建筑物的能效。结果表明,遗传算法可以通过合适的公式和参数提供多种最佳解决方案。

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