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首页> 外文期刊>Building and Environment >A decision support model for improving a multi-family housing complex based on CO_2 emission from gas energy consumption
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A decision support model for improving a multi-family housing complex based on CO_2 emission from gas energy consumption

机译：基于天然气能耗产生的CO_2排放量的多户住宅综合体的决策支持模型

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摘要

Improvement of residential environments has recently been promoted by the Korean government as part of its energy-saving measures. The objective of this research is to develop a decision support model for selecting the multi-family housing complex with the potential to be effective in saving energy. In this research, 362 cases of multi-family housings located in Seoul were selected to collect characteristics and data on gas energy consumption from 2009 to 2010. The following were carried out: (i) using the Decision Tree, a group of multi-family housings was established based on gas energy consumption; (ii) using case-based reasoning, a number of similar multi-family housings were retrieved from the same group of multi-family housings; and (iii) using a combination of genetic algorithms, artificial neural network, and multiple regression analysis, prediction accuracy was improved. The results of this research can be useful in the following: (i) preliminary research for continuously managing the gas energy consumption of multi-family housings; (ii) basic research for predicting gas energy consumption based on the characteristics of multi-family housings; and (iii) practical research for selecting an optimum multi-family housing complex (with the potential to be effective in saving gas energy), which can make the application of an enerey-savine program more effective as a decision support model.
机译：作为节能措施的一部分，韩国政府最近促进了居住环境的改善。这项研究的目的是开发一种决策支持模型，以选择具有节能潜力的多户住宅建筑群。在这项研究中，选择了362例位于首尔的多户住宅，以收集2009年至2010年天然气能源消耗的特征和数据。进行了以下操作：（i）使用决策树，一组多户根据天然气消耗量建立住房； （ii）使用基于案例的推理，从同一组多户住房中检索了许多类似的多户住房； （iii）结合使用遗传算法，人工神经网络和多元回归分析，提高了预测准确性。该研究的结果可用于以下方面：（i）进行连续管理多户住宅的天然气能耗的初步研究； （ii）根据多户住宅的特点预测燃气能耗的基础研究； （iii）选择最佳的多户住宅建筑群（有可能有效节省燃气能源）的实践研究，这可以使恩里·萨文计划的应用作为决策支持模型更为有效。

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