Designing a Renewal Approach of Rejuvenating Historic Districts: Taking Nantong Temple Street as an Example.

In recent years, people's opinions have shifted with the continuous development and growth of cities. The category of historical heritage is increasingly being shifted from the city's star fire to the backdrop color of the entire city. However, some cities are experiencing issues such as aging, regeneration, and stagnation. With the merging of sustainable development ideas with urban renewal techniques, sustainable urban renewal has developed as a new area of research. Data mining and analytics have played a significant role in extracting knowledge and decision-making in the revitalization of historic districts during the last decade. Machine learning, as a computational engine for learning analytics, is a fundamental technique for extracting information, data pattern detection, and prediction. From the perspective of machine learning, this study investigates the historical block update approach, which is utilized in feature space and culture at the same time. Furthermore, it investigates the development of countermeasures for injecting new energy into the historical block by using the functions of space and scale to search for the block transformation and the combination of natural and cultural landscapes. In addition, in order to interact with visitors and residents and realize the renewal of old blocks, in this research work, multifunctional culture is grafted into the historical block and buried underground, so that their life can be awakened. To highlight the efficiency of this work, we have taken the Nantong Temple Street in China as an example which verifies the validity of this study. [ABSTRACT FROM AUTHOR]