应用于粒子群优化的参数
包含PSO算法用于肝肿瘤射频消融PID控制器调优的参数及模拟性能数据。
基本信息
资源简介
应用于粒子群优化的参数
【数据集背景】
本数据集源站标题为《Parameters applied to PSO.》。源站首次发布：2024-06-26。
【数据内容】
源站原始描述：The study investigates the efficacy of a bioinspired Particle Swarm Optimization (PSO) approach for PID controller tuning in Radiofrequency Ablation (RFA) for liver tumors. Ex-vivo experiments were conducted, yielding a 9th order continuous-time transfer function. PSO was applied to optimize PID parameters, achieving outstanding simulation results: 0.605% overshoot, 0.314 seconds rise time, and 2.87 seconds settling time for a unit step input. Statistical analysis of 19 simulations revealed PID…
【数据结构与技术规格】
文件数 1 个，合计 5.63 KB。Table 2.xls：application/vnd.ms-excel，5.63 KB。数据集 DOI：10.1371/journal.pone.0300445.t002。
【主题与分类】
源站学科分类：Biochemistry、Medicine、Neuroscience、Biotechnology、Biological Sciences not elsewhere classified、Cancer。主题标签：unit step input、time transfer function、pid controller tuning、optimize pid parameters、minimized collateral damage、improving clinical outcomes、hepatocellular carcinoma management、incomplete tumor ablation、19 experiments yielded、value ≪ 0。
【适用方向】
结构化表格数据可直接用于统计建模、特征工程与队列分析。
【获取与许可】
源站页面：https://plos.figshare.com/articles/dataset/Parameters_applied_to_PSO_/26108551
使用许可：CC BY 4.0（https://creativecommons.org/licenses/by/4.0/）。
规范引用：Faria, Rafael Mendes; de Siqueira Rodrigues Fleury Rosa, Suélia; de Almeida Nunes, Gustavo Adolfo Marcelino; Santos, Klériston Silva; de Souza, Rafael Pissinati; Benavides, Angie Daniela Ibarra; et al. (2024). Parameters applied to PSO.. PLOS ONE. Dataset
下载信息
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使用方式
数据集获取（Figshare）
- 源站标题：Parameters applied to PSO.
- DOI：10.1371/journal.pone.0300445.t002
- 发布日期：2024-06-26
- 文件数：1 个
- 文件总体积：5.63 KB
- 源站页面：https://plos.figshare.com/articles/dataset/Parameters_applied_to_PSO_/26108551
命令行下载
curl -L -o "Table 2.xls" "https://ndownloader.figshare.com/files/47259514"
文件清单
Table 2.xls（5.63 KB）
文件总体积 5.63 KB（源站 API 实测）。
数据说明
The study investigates the efficacy of a bioinspired Particle Swarm Optimization (PSO) approach for PID controller tuning in Radiofrequency Ablation (RFA) for liver tumors. Ex-vivo experiments were conducted, yielding a 9th order continuous-time transfer function. PSO was applied to optimize PID parameters, achieving outstanding simulation results: 0.605% overshoot, 0.314 seconds rise time, and 2.87 seconds settling time for a unit step input. Statistical analysis of 19 simulations revealed PID gains: Kp (mean: 5.86, variance: 4.22, standard deviation: 2.05), Ki (mean: 9.89, variance: 0.048, standard deviation: 0.22), Kd (mean: 0.57, variance: 0.021, standard deviation: 0.14) and ANOVA analysis for the 19 experiments yielded a p-value ≪ 0.05. The bioinspired PSO-based PID controller demonstrated remarkable potential in mitigating roll-off effects during RFA, reducing the risk of incomplete tumor ablation. These findings have significant implications for improving clinical outcomes in hepatocellular carcinoma management, including reduced recurrence rates and minimized collateral damage. The PSO-based PID tuning strategy offers a practical solution to enhance RFA effectiveness, contributing to the advancement of radiofrequency ablation techniques.
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.1371/journal.pone.0300445.t002（source: https://plos.figshare.com/articles/dataset/Parameters_applied_to_PSO_/26108551）。
数据缺失？
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