A hydro-power safety management auxiliary decision-making platform design using natural language processing technologies

The safety management construction of the hydro-power units is necessary to prevent the quality failures. However, the traditional hydro-power units lack a unified safety management decision-making platform, making knowledge retrieval and recommendation difficult. To improve the safety management level of the hydro-power units, this work designs an auxiliary decision-making platform using natural language processing technologies. The auxiliary decision-making platform is composed of three parts, deep semantic similarity model, bidirectional long short-term memory network model and neural collaborative filtering algorithm. A case study is conducted to validate the auxiliary decision-making platform, which can provide the user the relevant knowledge guidance to the problem, including dangerous point analysis, defect causes, handling methods and operation preparation, improving the safety management level of the hydro-power units.