| Id : | 2711 | |
Author : | Liu G.; Zhao T.; Yan H.; Wu H.; Wang F. | |
Title | Evaluation of Urban Green Building Design Schemes to Achieve Sustainability Based on the Projection Pursuit Model Optimized by the Atomic Orbital Search |
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| Reference : | Liu G.; Zhao T.; Yan H.; Wu H.; Wang F. Evaluation of Urban Green Building Design Schemes to Achieve Sustainability Based on the Projection Pursuit Model Optimized by the Atomic Orbital Search,Sustainability (Switzerland) 14 17 |
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| Link to article | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137925533&doi=10.3390%2fsu141711007&partnerID=40&md5=a3f0a3a2159f6c2011ce4f45af27a643 |
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| Abstract | The popularization and use of green buildings are of great significance for reducing the carbon emissions of buildings and achieving sustainable development. Scientific evaluation of the green building design scheme is the key factor in ensuring the popularization and use of green buildings. To overcome the shortage of a systematic evaluation index system and comprehensive evaluation method, an evaluation index system of green building design schemes and an evaluation method based on the projection pursuit model were developed. First, according to the needs of green building development, an evaluation index system of green building design schemes was systematically constructed from the five aspects of the economy, the resource utilization index, environmental impacts, technical management, and social impacts. The calculation methods of all secondary indexes are provided in detail. Then, a novel evaluation method based on the projection pursuit model optimized by the atomic orbital search was constructed. This method searches for key influencing factors and determines the evaluation grade from the evaluation data structure, and realizes the scientific and objective evaluations of green building design schemes. Finally, the Nanchang Hengda Project was selected to conduct a detailed empirical study. The research results show that the incremental net present value of the investment, the energy consumption of the air conditioning system, and the ratio of the window area to the indoor area are the most important secondary indexes. Moreover, the environmental impact index was found to be the most important primary index. Via comparisons with different optimization algorithms and evaluation methods, the superiority of the proposed model is proven. © 2022 by the authors. |
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