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Research on Reconstruction Method for Illumination Field based on CMAC Neural Network

机译:基于CMAC神经网络的照明场重建方法研究

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In intelligent building applications, the awareness of built environment illumination filed representatively applies in intelligent lighting systems for providing decision and support. In fact, the dynamic analysis of the built environment can assist in the illumination field of security systems at the same time can also work as a new means of achieving safety precautions. In this paper, a simple interest in the built environment based on discrete data at the point of illumination perception of the built environment illumination field reconstruction method is proposed based on the fast reconstruction method CMAC neural network architecture space illumination field. Experimental results show that with the use of a typical area of interpolation, polynomial interpolation, inverse distance weighting interpolation method reconstructed building space illumination field compared to the use of constructed building space reconstruction method based on CMAC illumination field of architectural space illumination field high precision.
机译:在智能建筑应用中,提交内置环境照明的意识代表性地应用于提供决策和支持的智能照明系统。实际上,建筑环境的动态分析可以帮助在安全系统的照明领域同时可以作为实现安全预防措施的新手段。本文基于快速重建方法CMAC神经网络架构空间照明场提出了基于内置环境照明场重建方法的照明感知的基于离散数据的基于离散数据的简单兴趣。实验结果表明,通过使用基于CMAC照明场高精度的CMAC照明领域的构造建筑空间重建方法的使用与典型的插值,多项式插值,逆距离加权插值方法重建建筑空间照明。

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