Abstract
Taking a fuel gas company in Guizhou as an example to understand the dangerous and harmful factors in fuel gas production, storage, transportation and operation through on-the-spot investigation, and to deeply analyze the causes of accident. Then constructing the fuel gas accident risk assessment index system. Adopting the expert evaluation method and actual survey samples, and introducing the BP neural network mathematical model algorithm to conduct risk assessment on the sample gas company. And the risk value and risk level were obtained according to the sample comparison analysis.
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Wang, Q., Cheng, C., Zhang, C., Zhang, J., Ning, K. (2020). Fuel Gas Enterprise Accident Risk Assessment Based on BP Neural Network. In: Long, S., Dhillon, B. (eds) Man–Machine–Environment System Engineering . MMESE 2019. Lecture Notes in Electrical Engineering, vol 576. Springer, Singapore. https://doi.org/10.1007/978-981-13-8779-1_86
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DOI: https://doi.org/10.1007/978-981-13-8779-1_86
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