| 陈敏鑫,刘 石,孙单勋,刘兆宇.随机森林算法在温度分布重建中的应用[J].电子测量与仪器学报,2020,34(11):173-180 |
| 随机森林算法在温度分布重建中的应用 |
| Application of random forest algorithm in temperature distribution reconstruction |
| |
| DOI： |
| 中文关键词: 随机森林 温度分布重建 特征重要性 测点优化布置 |
| 英文关键词:random forest temperature field reconstruction feature importance optimal sensor placement |
| 基金项目:中央高校基本科研业务费专项资金(2019QN013)资助项目 |
|
|
|
|
| 摘要点击次数: 274 |
| 全文下载次数: 6387 |
| 中文摘要: |
| 为提高温度分布重建精度,提出了使用随机森林算法对温度测点进行优化布置的新方法。 将测点位置作为样本特征,
以不同的测点布置方式及其对应的重建误差作为样本数据集。 使用样本数据集构建随机森林模型,评估样本特征重要性,根据
特征重要性排序实现温度测点的优化布置。 设定仿真实验与燃烧实验验证优化布置算法的可行性与有效性。 分析实验数据,
所提出的优化布置算法相对于原有算法,重建精度提升了 20%以上。 研究结果表明,随机森林算法在温度分布重建中具有良好
的应用价值,并为解决工业实际问题提供了新思路。 |
| 英文摘要: |
| In order to improve reconstruction accuracy to resolve temperature distribution reconstruction problems, a method for optimal
sensor placement based on random forest algorithm is proposed. Denoting different measurement sites as different sample features, a
series of different sensor placements and the reconstruction errors which are calculated by these placements constitute a sample dataset.
A random forest model is setting up by the sample dataset, feature importance is also evaluated, then the optimal sensor placement is
determined by feature importance. Simulation test and combustion test are set up to verify the feasibility and practicability of the proposed
method. Testing data shows that comparing the original method, the proposed method can improve the reconstruction accuracy by at least
20%. Research results indicate that the proposed method has a good practical value, it also provides a new probe of using random forest
algorithm to solve industrial problems. |
| 查看全文 查看/发表评论 下载PDF阅读器 |
|
|
|
