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Abstract:   (214 Views)
Now creating perception in computer software is one of the most important challenges of digital architecture. Because computer software is one of the most important tools of architects or designers and is widely used in project design. In designing with the help of digital software, reaching the optimal design and layout is one of the most important and influential steps. But computer software does not have any inherent intuition about the design process, and this is the main reason for not handing over design processes to computers. Therefore, the aim of this research is to explain a computational method based on quantitative and qualitative data samples to create relative intuition in machines through the combination of evolutionary algorithms and machine learning. The quantitative and qualitative research method is based on genetic algorithms, machine learning (k-means clustering), and instance-based learning. The results of this research show that unlike methods based on the combination of genetic algorithms and genetic programming, it is possible to increase the accuracy and speed of map production by combining three genetic algorithms, machine learning, and based on relative intuition in machines. Also, another feature of the proposed method is the learning rate of nearly ninety percent in identifying and presenting designs. Of course, the production of plans by computers is in its early stages and it still needs a long process for this step to be completely taken by computers.
 
Article number: 114
     

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