Research on Visual Environment Evaluation System of Subway Station Space

Abstract

Based on the energy crisis, LED with its energy-saving and environmental friendly is gradually used to the subway station space lighting. But now, there are little materials about the visual environment evaluation for semiconductor lighting, so that the use of LED lighting lacks theoretical basis and data support. So, in order to promote the LED lighting in subway station space, it’s very important to evaluate the visual environment. Therefore, the core of this paper was to build a theoretical model to evaluate the visual environment of subway station space using Particle Swarm Optimization. Firstly, chose 16 evaluation indexes which were fit for the subway station visual environment evaluation and got the initial judgment matrix through pair wise comparison, after that, established the non-linear consistency correction model. Finally, used Particle Swarm Optimization to calculate the judgment matrix with better consistency and the corresponding index weight, and constructed the theoretical model.