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作 者:张渝 魏强 ZHANG Yu;WEI Qiang(Chongqing University of Technology,Chongqing 401135,China;Chongqing Key Laboratory of Green Energy Materials Technology and Systems,Chongqing 400054,China)
机构地区:[1]重庆理工大学理学院,重庆401135 [2]绿色能源材料技术与系统重庆市重点实验室,重庆400054
出 处:《中国照明电器》2024年第6期9-14,24,共7页China Light & Lighting
基 金:重庆理工大学研究生教育高质量发展行动计划资助成果(gzlcx20243311)。
摘 要:平衡优化器算法自从提出以来就广受国内外学者关注并研究其应用领域,本文提出使用平衡优化器算法作为光谱匹配算法用于匹配低蓝光LED健康产品光谱。选用美国Sorra公司低蓝光LED健康产品光谱作为目标光谱进行拟合,以高斯模型表征单色LED的分布,利用平衡优化器算法得到单色LED的最佳比例系数,进而实现光谱复现。复现得到的模拟光谱与目标光谱相吻合,皮尔逊相关系数达到0.9777。并在此基础上通过与经典的遗传算法和粒子群算法进行对比,选用皮尔逊相关系数和决定系数R^(2)作为评价标准。结果表明与遗传算法和粒子群算法相比较平衡优化器算法在与目标光谱的匹配中具有运行速度快、效率高、拟合误差小等优点。Since its proposal,the Equilibrium Optimizer algorithm has attracted much attention from scholars at home and abroad,and its application areas have been extensively studied.This paper proposes to use the Equilibrium Optimizer algorithm as a spectrum matching algorithm for matching the spectra of low blue light LED health products.The spectrum of low blue light LED health products from the American company Sorra was selected as the target spectrum for fitting.The Gaussian model was used to characterize the distribution of monochromatic LEDs,and the Equilibrium Optimizer algorithm was utilized to obtain the optimal proportion coefficients of the monochromatic LEDs,thereby achieving spectrum reproduction.The simulated spectrum reproduced closely matches the target spectrum,with a Pearson correlation coefficient of 0.9777.Furthermore,a comparison was made with the classical Genetic Algorithm and Particle Swarm Optimization Algorithm,using Pearson correlation coefficient and coefficient of determination R^(2)as evaluation criteria.The results show that compared to Genetic Algorithm and Particle Swarm Optimization Algorithm,the Equilibrium Optimizer algorithm has the advantages of fast operation speed,high efficiency,and small fitting errors in matching with the target spectrum.
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