ARTIFICIAL NEURAL NETWORK APPLICATION FOR HEAVY EQUIPMENT GAS EMISSION CONTROL ON ROCK BREAKING ACTIVITY

Mulyanto Soerjodibroto, Victor Amrizal, Wishnu Prabowo

Abstract


Applications of artificial intelligence (AI) software in mining activities, both for equipment automation, data analysis and processing, identification of patterns and features data, upto determining solutions have been carried out by several mining companies. This is mainly due to mining activities naturally are always facing uncertainty and natural variability conditions. One of the AI applications is to control fuel consumption aimed at increasing the efficiency of fuel use, while in the same time reducing exhaust gas emissions from internal combustion engines, which are one of the causes of rising greenhouse gases (GHG).

Utilization of AI in aimed to control fuel consumption in Rock Breaking activities in limestone quarry in the Sukabumi area, resulting a deviation rate of 0.17 for  fuel consumption prediction, which is fall in “ the good category”. Increasing the volume and variety of data for “machine learning” would  improve AI performance.

Keywords : Artificial intelligence application,  fuel consumption, ICE gas emission control.


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DOI: https://doi.org/10.15408/jipl.v2i2.29289 Abstract - 0 PDF - 0

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Publisher Mining Engineering Department, Faculty Science and Technology, Syarif Hidayatullah Jakarta State Islamic University,
 
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