城市固体废物网络:用于城市固体废物的自动化分类的层次堆叠模型.
Vaishnavi Jayaraman1, Arun Raj Lakshminarayanan1
1Computer Science and Engineering, B.S. Abdur Rahman Crescent Institute of Science and Technology, Chennai, India.
Journal of the Air & Waste Management Association (1995)
|June 20, 2024
概括
本研究介绍了MSW-Net,这是一个自动化城市固体废物 (MSW) 分类模型. MSW-Net实现了高精度,改善了废物管理,并保护废物收集者免受手动分类的危险.
科学领域:
- 环境科学 环境科学
- 计算机科学 计算机科学
- 人工智能的人工智能
背景情况:
- 高效的固体废物管理对于快速工业化的城市健康至关重要.
- 手动垃圾分类对垃圾收集者造成健康风险,原因是缺乏来源分离.
研究的目的:
- 开发城市固体废物 (MSW) 分类的自动化系统.
- 提高废物管理过程的效率和安全性.
主要方法:
- 开发了MSW-Net,这是一个用于自动MSW分类的层次堆叠模型.
- 使用自定义的卷积神经网络 (CNN) 和贝叶斯优化移动网络作为基础模型.
- 采用渐变增强作为元分类器.
主要成果:
- MSW-Net实现了99%的培训,95%的验证和96.43%的测试准确度.
- 在测试中表现出高性能,精度,回忆和F1得分约为96.42%.
- 在废物分类准确度方面表现优于现有模型.
结论:
- 城市固体废物网络 (MSW-Net) 模型为城市固体废物的自动化分类提供了一个高度准确的解决方案.
- 这项技术可以帮助市政当局在废物管理中以最小的人为干预.
- 提高废物管理效率,提高废物采集人员的安全.
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