A downloadable comic

bilibili video introduction:

【考虑采光与视线需求的建筑格栅立面智能生成方案 ——基于cnn和mlp算法】 https://www.bilibili.com/video/BV1H24y1S7Se/?share_source=copy_web&vd_source=9fa...

Abstract：

For the shops along the street on the second floor, lighting and view demand are both important factors affecting the quality of interior space. Therefore, when designing the facade of the commercial street, it is necessary to consider the impact of the facade on indoor lighting and view. However, we found that the uniformly added grille facade after the renovation of the old vegetable market block, while ensuring the integrity of the street, did not meet the specific needs of each Second floor shop for lighting and view, and appeared rigid and impractical. This design aims to use convolutional neural network and multi-layer perceptron to help optimize the grille facade of the second-floor shops in the old vegetable market block driven by lighting and view requirements. On the basis of establishing the unified form of grille, three iconic scenes outside the window are extracted through CNN (i) sky; (ii) City walls; (iii) Characteristic values of trees. First, a single shop is selected, and MLP is used to find the connection between the grille style and the sight perception and lighting condition. And try to use this method and MLP backpropagation aid to design grilles in similar blocks. The method is evaluated by calculating the lighting condition and line of sight evaluation of the generated grid. We believe that the method has strong generalization and robustness, and has strong application space in the reconstruction of historical blocks in Xi 'an and other cities.

Notice：

In order to give you a more relaxed reading experience, we have specially produced a condensed version of the report. If you don't like to read long research background and literature review, this edition will spare you those parts and tell you what we did in a concise way.