A new approach on ai application for grounding resistor prediction in underground mines of vietnam

Purpose. To apply artificial intelligence (AI) technology for predicting the earthing resistor of underground mines with consideration climate change parameters. Methodology. In coal Vietnam, system are everywhere equipped individual rods combined centralized grounding bed; this significantly influences electrical safety and explosion safety. daily operation, must be measured tested regularly to ensure their value lower than allowance limit (2). However, because being affected by parameters (humidity temperature in mines) varies frequently. By applying a new Neural Network 3 hidden layers including variable parameters, paper presents approach on resistor. An algorithm is formed visible easily usable software assisting operator predict The prediction could used onsite management mine field observing testifying mines. Findings. Software developed based AI corresponding change. Originality. network application utilized relying measurements. Practical value. Prediction results case difficulty measurement. It will also help correct or eliminate measurement error from mining technician.