利用基于人工神经网络的作业组合方法降低热应激风险

2010 IEEE International Conference on Industrial Engineering and Engineering Management Pub Date : 2010-12-23 DOI:10.1109/IEEM.2010.5674503

S. Srivastava, Y. Anand, V. Soamidas

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引用次数: 9

摘要

我们设计并实施了一个系统，以减少热应激的风险，公认的职业健康危害(OHH)，在两个劳动密集型行业使用工作组合的方法。该系统的一个新特点是采用人工神经网络(ann)作为无模型估计器来评估工作中提出的不同工作组合的感知不适(pd)。

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Reducing the risk of heat stress using artificial neural networks based job-combination approach

We design and implement a system to reduce the risk of heat stress, a recognized occupational health hazard (OHH), in two labor intensive industries using a job-combination approach. A novel feature of the system is employing artificial neural networks (ANNs) as model free estimators to evaluate perceived discomforts (PDs) of workers for different job combinations proposed in the work.

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2010 IEEE International Conference on Industrial Engineering and Engineering Management

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