Many problems in real life can be seen as Expensive Optimization Problems (EOPs).
Compared with traditional optimization problems, the evaluation cost of candidate solutions …

Building envelope parameters and geometric configurations can considerably influence the
building energy performance. However, determining the best trade-offs of different building …

Statistical models can be used as surrogates of detailed simulation models. Their key
advantage is that they are evaluated at low computational cost which can remove …

Worldwide, the residential buildings are consuming a considerable amount of energy. The
high potential of buildings towards energy efficiency has drawn special attention to the …

Abstract The challenge in Net Zero Energy Building (NZEB) design is to find the best
combination of design strategies that will face the energy performance problems of a …

In most of the countries, buildings are often one of the major energy consumers, leading to
the necessity of achieving sustainable building designs, and to the mandatory use of …

Multi-label learning algorithms have significant challenges due to high-dimensional feature
space and noises in multi-label datasets. Feature selection methods are effective techniques …

In this paper, ensemble feature selection is modeled as a bi-objective optimization problem
regarding features' relevancy and redundancy degree. The proposed method, which is …

This article proposes a two-stage design optimization approach which is applied to a
prototype passively designed high-rise residential building under different ventilation modes …

Passive design strategies are important for achieving building sustainability given their
proved influences over the building performance in both energy and indoor environmental …