Application of Landscape Design Optimization Algorithm Based on Big Data in CAD Platform

This article employs a hybrid approach encompassing both theoretical and empirical research. Initially, a comprehensive review of literature and case studies is conducted to map out the current applications and future trends of big data in landscape design. Subsequently, a model for optimizing landscape design algorithms using big data is devised, and its performance is benchmarked against suitable algorithms. Furthermore, the study explores the integration of big data with CAD platforms, enabling the implementation of these optimization algorithms within the CAD environment. The practical utility and efficacy of this research are validated through real-world application examples. The experimental findings underscore the notable impact of the optimization algorithm when applied to CAD platforms. A comparative analysis of design schemes, both pre-and post-optimization, reveals significant enhancements in aesthetic appeal, functionality, and cost-efficiency. Additionally, the algorithm demonstrates robust efficiency and stability, making it well-suited for practical landscape design tasks. Overall, this research successfully introduces a big data-driven landscape design optimization algorithm to CAD platforms, facilitating automated optimizations and intelligent adjustments to design proposals. This innovation represents a substantial advancement in enhancing landscape design productivity, cost reduction, and industry-wide innovation. © 2024 U-turn Press LLC.