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Generative adversarial network-based gorgeous null space planning design generation method and system

A technology for planning, designing and generating systems, applied in biological neural network models, design optimization/simulation, special data processing applications, etc., can solve problems such as irregular spatial structures, difficulty in finding designers, and lack of scholars, etc., reaching an economical level Improve, save labor costs, reduce the effect of environmental damage

Pending Publication Date: 2021-02-05
恩亿科(北京)数据科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, for the deformed null space, on the one hand, the demand is relatively small, and on the other hand, the space structure is irregular, so no scholars are engaged in related research.
However, it is time-consuming and labor-intensive to plan and design the deformed space by manual means, and at the same time, the income is small, so it is difficult to find a suitable designer

Method used

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  • Generative adversarial network-based gorgeous null space planning design generation method and system
  • Generative adversarial network-based gorgeous null space planning design generation method and system
  • Generative adversarial network-based gorgeous null space planning design generation method and system

Examples

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Embodiment 1

[0055] refer to Figure 1 to Figure 3 As shown, this example discloses a specific implementation of a generation method for distorted space planning and design based on generative confrontation network (hereinafter referred to as "method").

[0056] Specifically, as figure 1 As shown, the method disclosed in this embodiment mainly includes the following steps:

[0057] Step S1: Establish a real data set of spatial planning and design schemes of the distorted space, and label each design scheme in the data set with an expected label.

[0058] Specifically, a number of design schemes are generated for the leftover space, and a data set of the design schemes is formed, and each design scheme is marked with an expected label. Among them, the leftover space of the city / leftover space is a collection of scattered Conceptual descriptions of unorganized and unorganized spaces, including intermediary spaces between buildings, corner spaces between roads and bridges, abandoned spaces ...

Embodiment 2

[0087] Combining with the generation method of distorted null space planning and design based on generative confrontation network disclosed in the first embodiment, this embodiment discloses a specific implementation example of a distorted null space planning and design generation system based on generative confrontation network (hereinafter referred to as "system") .

[0088] refer to Figure 4 As shown, the system includes:

[0089] Data set generating module 11: set up a real data set of spatial planning and design schemes of abnormal zero, and label each design scheme in the data set with an expected label;

[0090] Network construction module 12: Construct generation network and discriminant network based on deep convolution generation confrontation network;

[0091] The first result generation module 13: according to the data set and the expected label, based on the generation network and the discrimination network, generate a true or false judgment result of the first...

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Abstract

The invention discloses a generative adversarial network-based gorgeous null space planning design generation method and system, and the method comprises the steps: building a data set of a real gorgeous null space planning design scheme, and marking an expected label for each design scheme in the data set; constructing a generative network and a discrimination network based on the deep convolution generative adversarial network; generating a true and false judgment result of the first design scheme based on the generation network and the judgment network according to the data set and the expected label; according to the data set and the expected label, generating a true and false judgment result of the random design scheme based on a judgment network; alternately iteratively training a discrimination network and a generation network; and receiving an expected label form submitted by the user, and generating a second design scheme corresponding to the expected label form by utilizing the trained generation network.

Description

technical field [0001] The invention relates to the technical field of architectural generative design, in particular to a method and system for generating a malformed space planning and design based on a generative confrontation network. Background technique [0002] In recent years, with the acceleration of the urbanization process and the improvement of the level of economic development, the scale of urban land use has continued to expand, and the problem of scarcity of land resources has become increasingly prominent. Distorted space refers to the unreasonable phenomenon in the planning and use of some land during the development of urban buildings. Therefore, due to the different needs between buildings or between communities, there will inevitably be some inevitable waste of space. The reasons why these spaces are not fully utilized may be caused by the following reasons: (1) The irregular plots formed between buildings are relatively narrow; (2) The land is polluted ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F30/13G06F30/27G06N3/04
CPCG06F30/13G06F30/27G06F2111/08G06N3/045
Inventor 李金运
Owner 恩亿科(北京)数据科技有限公司
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