Construction in process...
An integrated method to optimize the design of streetscape based on Machine Learning and Evolutionary Multi-objective Optimization Algorithm.
Developed by: Jeff H ([email protected]) This repository is based on my dissertation submitted for Master of Landscape Architecture (MLA) at National University of Singapore (NUS).
一套基于机器学习和演进式多目标优化算法的、用来对街景设计进行优化的框架,包含一系列工具、算法和概念。
本套框架由 Jeff H 开发。它是我在新加坡国立大学 景观硕士的毕业论文中设计的框架。
- Python 3.6+
- Essential library:
- Numpy
- Pandas
- Matplotlib
- Tensorflow
- Deeplab2 (https://github.com/google-research/deeplab2)
- Geatpy (http://geatpy.com | https://github.com/geatpy-dev/geatpy)
- Sci-kit learn
-
Initialization tools of GIS data
-
Initialization tools of GSV data list for obtaining the images
- As a non-CS researcher, I don't have a lot of knowledge about licensing and copyright. I will arrange this part after checking and studying.
- In addition, since some steps in this framework use other open source code libraries, algorithms, tools, etc., I need to follow their licenses. I will complete this part after I have researched and clarified it.
- Python 3.6+
- Essential library:
- Numpy
- Pandas
- Matplotlib
- Tensorflow
- Deeplab2 (https://github.com/google-research/deeplab2)
- Geatpy (http://geatpy.com | https://github.com/geatpy-dev/geatpy)
- Sci-kit learn
-
GIS数据初始化工具(供本研究分析用)
-
GSV数据初始化工具和处理器(供GSV图像获取用)
- 作为非计算机专业的研究人员,我并不太了解许可证、著作权方面的信息。待我调查和学习后再安排这部分内容。
- 此外,由于本框架中的部分步骤使用了其他开源的代码库、算法、工具等,所以我需要遵循它们的许可。待我研究清楚后再完善这部分。