Based on ANN and many-objective optimization to improve the performance and economy of village houses in Chinese cold regions

Guo, Juanli; Zhou, Jian; Li, Mingchen; Lu, Siao

doi:10.1080/19401493.2023.2183259

Journal of Building Performance Simulation

2023

DOI: 10.1080/19401493.2023.2183259

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Based on ANN and many-objective optimization to improve the performance and economy of village houses in Chinese cold regions

Juanli Guo

Jian Zhou

Mingchen Li

et al.

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2024

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Cited by 3 publications

(6 citation statements)

References 31 publications

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“…In recent years, the construction industry has increasingly adopted new materials and technologies to reduce energy consumption, such as double-layered exterior walls [40], phase-change walls [40], and passive radiant cooling [23,28,31,32,36,40,41,44,51,63,66,78,85,91]. These advancements necessitate more accurate and specialized modules to achieve joint simulation between building energy simulation programs (BESP) and different modules.…”

mentioning

confidence: 99%

“…Design-Builder is widely recognized as the most popular simulation software [23,26,28,31,32,42,44,45,53,65,68,76,83,88]. Additionally, Autodesk REVIT [42,87,[89][90][91] and SketchUp [67,72,86], as Building Information Modeling (BIM) software, are also commonly used. These programs support users in constructing building models more straightforwardly and then converting them into dedicated models for respective simulation kernels for conducting building performance simulation and result analysis.…”

mentioning

confidence: 99%

“…phase-change walls [40], and passive radiant cooling [23,28,31,32,36,40,41,44,51,63,66,78,85,91]. These advancements necessitate more accurate and specialized modules to achieve joint simulation between building energy simulation programs (BESP) and different modules.…”

mentioning

confidence: 99%

“…Hybrid machine learning algorithms (such as random forests, NSGA-II, and NSGA-III intelligent algorithms) have performed well in multi-objective optimization. Therefore, they are suitable for multi-objective problems in the field of building performance optimization and are commonly used in the sustainable renovation of residential buildings in China [64,85,91]. The multi-objective optimization problem can be summarized as follows:…”

mentioning

confidence: 99%

“…Subsequently, the distance between each non-dominated solution and the ideal and anti-ideal solutions is calculated separately. The comprehensive distance serves as the basis for assessing solution equality and enables the computation of TOPSIS scores [49,64,76,86,91].…”

mentioning

confidence: 99%

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Sustainable-Driven Renovation of Existing Residential Buildings in China: A Systematic Exploration Based on Review and Solution Approaches

Huang,

2024

Sustainability

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Under the backdrop of China’s national strategy to achieve carbon neutrality by 2060, efforts are underway across governmental, corporate, societal, and individual sectors to actively explore energy-saving renovations in existing buildings. Given that residential buildings constitute a significant proportion of the total energy consumption throughout the lifecycle of buildings in China, sustainable renovation of residential structures can contribute significantly to implementing China’s carbon emission reduction policies. While there exists a plethora of technological means in the market aimed at improving the energy performance of residential buildings, there still needs to be a more systematic discussion on the framework for sustainable renovation of existing Chinese residential buildings, with knowledge dissemination still needing to be more cohesive. In this context, this paper provides a comprehensive review of the field, utilizing bibliometric methods. Through a systematic review of selected peer-reviewed literature from the Web of Science and Scopus databases, the study focuses on the sustainable renovation of existing Chinese residential buildings, categorizing the process into three main stages: sustainable renovation, building performance simulation and suitability assessment. The paper also reviews the research methods adopted by previous researchers in the renovation, simulation and assessment stages, considering various optimization algorithms, variables, objectives, and software tools. Subsequently, the paper synthesizes a research framework comprising these three stages combined for different research objectives, aiming to assist policymakers, designers, and researchers in gaining a comprehensive understanding of the implementation status of sustainable renovation in existing Chinese residential buildings, identifying barriers to implementation, and formulating more efficient renovation policies and strategies for the future.

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mentioning

confidence: 99%

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confidence: 99%

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confidence: 99%

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confidence: 99%

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confidence: 99%

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Sustainable-Driven Renovation of Existing Residential Buildings in China: A Systematic Exploration Based on Review and Solution Approaches

Huang,

2024

Sustainability

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Multi-objective optimization of plant community characteristics in urban green spaces

Yu,

Song,

Jiang

et al. 2024

Urban Forestry & Urban Greening

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Research on Optimized Design of Rural Housing in Cold Regions Based on Parametrization and Machine Learning

Sun,

Xue,

Wang

2024

Sustainability

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With the rapid development of urbanization, the emergence of more self-built buildings in the countryside has brought about energy waste problems and decreased comfort. Achieving the low-carbon goal and improving the quality of the human living environment through architectural and planning means have become vital issues. In this study, from a parametric perspective, model building and performance simulation are carried out using Rhino and Grasshopper, and a multi-objective optimization method and a neural network model are used as the theoretical basis to train the prediction model after data collection and processing. The model validation of R2 = 0.988 and MSE = 0.0148 indicates that the model can accurately reflect the program’s performance. By establishing a rapid prediction model for the performance of rural residential buildings, decision-makers can perform performance predictions under various parameter combinations at the early design stage, facilitating the screening of building types with high energy consumption and costs. The method can improve the efficiency of decision-making at the early stage of design, help save decision-making costs by screening high-energy-consuming building types, improve the living conditions of residents, reduce carbon emissions, and contribute to the sustainable development of residential building renewal design in rural areas.

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Based on ANN and many-objective optimization to improve the performance and economy of village houses in Chinese cold regions

Cited by 3 publications

References 31 publications

Sustainable-Driven Renovation of Existing Residential Buildings in China: A Systematic Exploration Based on Review and Solution Approaches

Sustainable-Driven Renovation of Existing Residential Buildings in China: A Systematic Exploration Based on Review and Solution Approaches

Multi-objective optimization of plant community characteristics in urban green spaces

Research on Optimized Design of Rural Housing in Cold Regions Based on Parametrization and Machine Learning

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