Conservation Design of Industrial Heritage based on Nonlinear GA Optimization Algorithm and Three-dimensional Reconstructioneconstruction

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Yunan Zhao
Peng Bai

Abstract

In order to understand the industrial heritage protection design of Iterative reconstruction, the author proposes a research on industrial heritage protection design based on GA optimization algorithm and Iterative reconstruction. Firstly, the author establishes the 3D model of industrial heritage through Iterative reconstruction, and optimizes the model parameters through GA algorithm to achieve the purpose of protecting and utilizing industrial heritage. Secondly, the author proposes a method of Iterative reconstruction of industrial heritage based on GA algorithm, uses this method to conduct Iterative reconstruction of industrial heritage, and imports the reconstructed model into the 3D model management system for management. This method solves the problem of high reconstruction cost caused by low model quality in traditional Iterative reconstruction, and makes industrial heritage protection design more practical. Finally, an experimental analysis was conducted using a factory building in a certain city as an example. The results showed that the model optimized using the GA algorithm had significantly better performance than traditional reconstruction methods, and could more accurately reflect the spatial form and structural characteristics of industrial heritage, this provided new ideas and methods for the subsequent protection and utilization of industrial heritage. The GA algorithm optimized 3D model established by the author can effectively evaluate industrial heritage in historical urban areas, not only revealing the value of industrial heritage better, but also providing a certain reference for similar work in the future.


 

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Special Issue - Deep Learning-Based Advanced Research Trends in Scalable Computing