Indoor Landscape Design and Environmental Adaptability Analysis Based on Improved Fuzzy Control

Abstract: With the increasing demand for automation and intelligence in indoor landscape design, exploring efficient and precise control strategies has become particularly important. Robot-assisted technology and A* algorithm are utilized for indoor environment localization and mapping. Then, type-2 fuzzy adaptive fuzzy control is applied for indoor landscape automatic design. An improved genetic algorithm is utilized for environmental analysis to enhance the adaptability of indoor landscape design to the environment. In the results, the robot adopting this algorithm was significantly better than ordinary robots in path planning optimization, with a fitting accuracy of over 95%. The type-2 fuzzy control model had a maximum speed of 0.75m/s and an overshoot of only 7.1% for balancing robots, resulting in a faster recovery speed and smaller overshoot. The proposed method performed the best in terms of functionality, aesthetics, technicality, accessibility, and user satisfaction for landscape design effectiveness and environmental adaptability. The research improves indoor landscape design’s automation. Meanwhile, the combination of fuzzy control and genetic algorithms enhances the design accuracy and environmental adaptability. This provides a new technological path for indoor landscape design.

Jinming Liu, Qian Hu and Pichai Sodbhiban. “Indoor Landscape Design and Environmental Adaptability Analysis Based on Improved Fuzzy Control”. International Journal of Advanced Computer Science and Applications (IJACSA) 15.10 (2024). http://dx.doi.org/10.14569/IJACSA.2024.0151080

@article{Liu2024,
title = {Indoor Landscape Design and Environmental Adaptability Analysis Based on Improved Fuzzy Control},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2024.0151080},
url = {http://dx.doi.org/10.14569/IJACSA.2024.0151080},
year = {2024},
publisher = {The Science and Information Organization},
volume = {15},
number = {10},
author = {Jinming Liu and Qian Hu and Pichai Sodbhiban}
}