基于WOA-BP模型的进口和出口玩具的质量和安全风险识别研究
Qiong He1,2, Pengzhao Li3,4
1School of Management Science and Engineering, Beijing Information Science and Technology University, Beijing, 100192, China.
Scientific reports
|August 14, 2025
概括
这项研究通过开发一个新的框架来确定进出口风险,从而提高玩具的安全性. 先进的WOA-BP模型显著提高了检测产品质量和安全问题的准确性,减少了召回.
科学领域:
- 关税风险管理 关税风险管理
- 产品安全工程 产品安全工程
- 数据科学数据科学数据科学
背景情况:
- 进出口玩具的高召回率表明,在识别质量和安全风险方面存在挑战.
- 当前的海关风险管理系统与玩具的高度安全敏感性作斗争.
研究的目的:
- 制定一个综合框架,以便更好地识别进出口玩具的质量和安全风险.
- 提高对高敏感性产品的海关风险管理的准确性和效率.
主要方法:
- 建立了一个"数据收集-风险分类-风险识别"的框架.
- 隐性迪里克莱特分配 (LDA) 用于风险因素聚类.
- 鱼优化算法优化反向传播 (WOA-BP) 模型被开发用于风险识别.
主要成果:
- TF-IDF和网络分析确定了关键的风险词和相关性.
- LDA成功地将风险分为类型,材料和缺陷,并将其分为五种事件类型.
- WOA-BP模型实现了95.71%的准确性,超过了其他优化算法和未优化的BP.
- 该模型表现出与0.997.2的测试集R2的强度适应.
结论:
- 拟议的框架大大提高了玩具质量和安全风险的识别.
- 这种方法为进出口产品安全管理提供了一个新的方法.
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