Exploring the design of ecological and energy-saving residential buildings adapted to climate change based on a simulated annealing algorithm

被引:0
|
作者
Zhang H. [1 ]
机构
[1] The Tourism College of Changchun University, Changchun, Jilin
关键词
Big data; Crossover operator; Energy Plus model; Residential building design; Simulated annealing algorithm;
D O I
10.2478/amns.2023.2.00074
中图分类号
学科分类号
摘要
In the context of the digital development of big data and information in recent years, performance-based residential building design and its optimization methods have gradually become a research hotspot of domestic and international attention. The simulated annealing algorithm is a major component of residential buildings' optimal energy efficiency design. Although the crossover operator under the computational traditional simulated annealing algorithm incorporates the respective advantages of the genetic algorithm and simulated annealing algorithm, the purely optimal genetic simulated annealing algorithm is more effective for the evaluation of index analysis and better reflects the superiority of the algorithm. In the Energy Plus model, the three algorithms were used to analyze the design indexes of ecological energy-efficient residential buildings, and the SS values of the MOSA algorithm fluctuated between 10% and 24%, and the performance of the recommended genetic simulated annealing algorithm was significantly better than the other two algorithms. This study effectively solves the difficulties of low efficiency and high failure rate common in design practice when using this technique and is of historical importance to the development of energy-efficient residential buildings in China. © 2023 Hui Zhang, published by Sciendo.
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