相关实验视频

Updated: Jun 29, 2025

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

通过Taguchi方法,机器学习和遗传算法优化PCF-SPR传感器设计

Sameh Kaziz¹, Fraj Echouchene², Mohamed Hichem Gazzah³

¹NANOMISENE Laboratory, LR16CRMN01, Centre for Research on Microelectronics and Nanotechnology (CRMN) of Sousse Technopole, Sahloul, B.P.334, 4054, Sousse, Tunisia. kaziz_sameh@yahoo.fr.

Scientific reports

|April 3, 2024

概括

这项研究引入了一种高度敏感的光子晶体纤维表面等离子体共振传感器,用于检测低折射率变化. 优化的设计实现了显著的光谱和振幅灵敏度,展示了制药检查的潜力.

科学领域:

光子学是指光子学的使用方法.
塑制剂是一种塑制剂.
光学传感传感器是什么?

背景情况:

采用表面等离子共振 (SPR) 的光子晶纤 (PCF) 提供了先进的传感能力.
低折射率 (RI) 检测对于制药检查和环境监测等应用至关重要.
现有的PCF-SPR传感器需要优化,以提高灵敏度和稳定性.

研究的目的:

设计和优化一种新型的双核PCF-SPR传感器,用于高灵敏度检测低折射率.
调查设计参数对传感器性能的影响.
利用人工神经网络 (ANN) 来预测传感器特性和优化设计.

主要方法:

一个双核PCF结构的制造,外层沉积的银 (Ag) 塑层,由二氧化 (TiO2) 保护.
优化五个关键设计参数 (距离,空气孔直径,银厚) 使用Taguchi L8(2 ^ 5) 直角阵列.
应用人工神经网络 (ANN) 优化技术,包括多层感知器 (MLP) 和粒子集群优化 (PSO),以预测限制损失 (αloss).
使用遗传算法 (GA) 来优化传感器设计,以最大限度地减少限制损失.

主要成果:

实现了显著的10,000nm/RIU的光谱灵敏度和235,882 RIU-1的振幅灵敏度,用于低RI检测.
证明了PSO-ANN在准确预测未知几何维度的传感器性能方面的有效性.
确定了最佳设计参数,从而产生出色的传感器响应.

结论:

拟议的双核PCF-SPR传感器在低RI检测方面表现出极高的灵敏度.
ANN优化技术,特别是PSO,提供了光学属性的高效和准确的预测,促进了快速传感器设计.
传感器设计对制药检查和检测低RI分析物的实时监控具有重大前景.

关键词:

遗传算法遗传算法遗传算法多层的感知电子是多层的.粒子群集优化优化粒子群集优化这是光子晶体纤维.表面等离子体共振是什么?塔古奇的方法是Taguchi的方法.

更多相关视频

Design and Analysis for Fall Detection System Simplification

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

相关概念视频

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...

PD Controller: Design

PD Controller: Design

In automotive engineering, car suspension systems often employ Proportional Derivative (PD) controllers to enhance performance. PD controllers are utilized to adjust the damping force in response to road conditions. A controller, acting as an amplifier with a constant gain, demonstrates proportional control, with output directly mirroring input.
Designing a continuous-data controller requires selecting and linking components like adders and integrators, which are fundamental in Proportional,...