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Selective and Collaborative Optimization Methods for Plasmonics: A Comparison

机译:等离子的选择性和协同优化方法:比较

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In this paper, we optimize the size parameters of hollow nanospheres and nanoshells used in cancer photothermal therapy and we focus on two practical therapy cases: the visible range for shallow cancer and the near infrared for deep cancer. For this, we consider analytical models: the Mie theory for coated spheres. The investigated optimization methods are the Evolutionary Method (EM) and the Particle Swarm Optimization (PSO) which are based on competitiveness and collaborative algorithms, respectively. A comparative study is achieved by checking the efficiency of the optimization methods, to improve the nanoparticles efficiency.
机译:在本文中,我们优化了用于癌症光热疗法的中空纳米球和纳米壳的尺寸参数,并重点研究了两个实际的治疗案例:浅层癌症的可见范围和深层癌症的近红外范围。为此,我们考虑分析模型:涂层球的米氏理论。研究的优化方法分别是基于竞争力和协同算法的进化方法(EM)和粒子群优化(PSO)。通过检查优化方法的效率来提高纳米颗粒的效率,从而进行了比较研究。

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