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穆拉卡:一种可解释的多式联网深度学习框架,用于识别饮用水中的PMT/vPvM物质

Nguyen Doan Hieu Nguyen1, Nhat Truong Pham1, Hojin Seo1

  • 1Department of Integrative Biotechnology, College of Biotechnology and Bioengineering, Sungkyunkwan University, Suwon, Gyeonggi-do 16419, Republic of Korea.

Journal of hazardous materials
|November 26, 2025
PubMed
概括

一个新的深度学习工具,Mulaqua,有效地识别了饮用水中的持久性,移动性和有毒性 (PMT) 和非常持久和非常移动性 (vPvM) 物质. 这种计算方法有助于早期危险检测和新出现的污染物的监管优先级.

关键词:
数据增强数据增强模型解释模型解释多模式深度学习 (deep learning) 是一种多模式深度学习.有关PMT/vPvM的物质.水的质量 水的质量

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相关概念视频

Multiple Pipe Systems01:21

Multiple Pipe Systems

Multipipe systems consist of complex configurations of interconnected pipes designed to transport fluids efficiently across intricate networks. They are essential in engineering applications requiring precise control over flow distribution, pressure, and head loss. They are categorized into series, parallel, loop, and network configurations, each distinguished by unique flow characteristics and applications.
Series Configuration
In a series configuration, fluid flows sequentially from one pipe...