Parametric optimization of an architectural object’s form as a method to improve its energy efficiency

Vasilenko, N. A.

doi:10.1088/1757-899x/552/1/012027

Cited by 4 publications

(3 citation statements)

References 7 publications

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“…Iterate one step forward from point α 1 to point α 2 , and so on, many iterations. e iteration form from step k to step (k + 1) is shown in equation (8).…”

Section: Parameter Optimizationmentioning

confidence: 99%

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Improved Chaotic Algorithm-Based Optimization Technology of Architectural Engineering Drawing Parameters

2022

Computational Intelligence and Neuroscience

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The traditional methods deal with large sample data sets of architectural engineering drawings and they have high time complexity and space complexity as well. Their searching time is long and sometimes the results are unsatisfactory. Therefore, this paper proposes an optimization method designed for architectural engineering drawing parameters to overcome the limitations of the traditional methods. It is based on the improved chaotic algorithm. The algorithm proposes the optimization model of architectural engineering drawing (AED) parameters in the first phase. In the second phase, an improved chaos algorithm is used to optimize the parameters of architectural engineering drawing, and the modeling strategy of visual parameter optimization environment is constructed. Finally, the visualization parameter optimization process of architectural engineering drawing is completed. Through experiments, it is evidently observed that the method presented in this paper can effectively reduce the optimization time, improve the lighting illumination of buildings, and improve the optimization precision of architectural engineering drawing parameters. The proposed method considers multiple parameters and it has greater application ability in the field of architectural designs.

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“…Iterate one step forward from point α 1 to point α 2 , and so on, many iterations. e iteration form from step k to step (k + 1) is shown in equation (8).…”

Section: Parameter Optimizationmentioning

confidence: 99%

“…It shows high clustering accuracy. In [ 8 ], the authors state that the parametric optimization of an architectural object is an important design task. They also state that improvement is needed in the area of quality of a design solution.…”

Section: Introductionmentioning

confidence: 99%

Improved Chaotic Algorithm-Based Optimization Technology of Architectural Engineering Drawing Parameters

2022

Computational Intelligence and Neuroscience

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“…In recent years, with the rapid development of China's basic industry, building structure design also needs to make continuous adjustments and changes with the development of the times [1][2][3][4]. At present, architectural design is the basic condition to ensure the safety and stability of the main body of the building structure [5]. Good structural design optimization can not only improve the appearance quality and functional value of the building but also help to improve the quality of people's daily lives [6].…”

Section: Introductionmentioning

confidence: 99%

Application of Visual Recognition Based on BP Neural Network in Architectural Design Optimization

Liang

Wang

2022

Computational Intelligence and Neuroscience

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In order to establish the mapping relationship between architectural design parameters and building performance and optimize architectural design parameters, an architectural design optimization method based on BP neural network is proposed. The selected main design parameters of building ventilation include spacing coefficient, air outlet area, and height from the bottom of the window sill to the ground. Take the comprehensive performance of building ventilation design as the main optimization objective to optimize the building design. First, nine groups of samples of building optimization design are obtained through uniform experimental design. Then, based on the architectural design sample data obtained by BP neural network training, the mapping relationship between architectural design parameters and building performance is established, and based on this mapping, the optimal design parameters of the building are calculated. The research results have a certain reference value for architectural design optimization.

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Forecasting of the group of power system’s technical condition composite index and demand for heat energy by office buildings using an artificial neural network

Guzhov

Andreeva

Sofronitsky

2021

IOP Conf. Ser.: Mater. Sci. Eng.

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Support of a sustained reduction of energy resource consumption by implementing advanced energy-efficient technologies, including alternative and renewable energy sources, requires a well-reasoned selection of the cost-effective measures so it can be replicated at the «green construction» sites. One of the basic approaches in forming of the present-day policy in the ecofriendly and energy-saving trends became a scaling effect of what has been achieved from the «green construction» technologies implementation at similar sites in Moscow. The actuality and scientific novelty of this paper lie in the development of the evaluation algorithm of energy and as a result of echo-economic efficiency of different measures for energy-saving, the adaptation of the forecasting methodology for building’s technical condition index application, review of the alternative and renewable energy source technologies implementation at the «green construction» sites in the Moscow region, analysis of the technical and ecological efficiency actual values of the utilized energy-saving methods and technologies. Monitoring and dispatching of a large number of separate power plants require special ways of collecting, processing, and analyzing information about the condition of water, heat, fuel, and electricity supply systems to ensure reliability and stability of the equipment functioning. Failures necessitate maintenance works at facilities by way of equipment repair as well as replacement. The consumers may impose penalties on the heat supply company for violating heat energy supply obligations as well as on the building’s owner for incorrect equipment maintenance. The objective of this paper is to determine an approach that helps to develop a software program, based on the neural network programming, to calculate the forecasting composite index of building’s energy system, «green construction» facilities ecological and economic efficiency examination and feasibility evaluation of their further replication in Moscow region.

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Parametric optimization of an architectural object’s form as a method to improve its energy efficiency

Cited by 4 publications

References 7 publications

Improved Chaotic Algorithm-Based Optimization Technology of Architectural Engineering Drawing Parameters

Improved Chaotic Algorithm-Based Optimization Technology of Architectural Engineering Drawing Parameters

Application of Visual Recognition Based on BP Neural Network in Architectural Design Optimization

Forecasting of the group of power system’s technical condition composite index and demand for heat energy by office buildings using an artificial neural network

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