Abstract
The fuel tank autocalibration problem is an important issue in managing the amount of fuel stored in the tank. Current values are calculated basing on fuel sold (going out through nozzles - dispensing) and fuel pumped into the tank by a tanker (delivered). The difference in these values may point to different reasons - leakage, theft, or other errors. To pinpoint the cause it is important to rule out the case of wrong tank calibration, hence the tank autocalibration method is required. In this paper we present autocalibration method based on a neural networks algorithm, along with method’s drawbacks and an alternative calibration method proposition.
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The project is founded by the Polish Council of the National Centre for Research and Development within the DEMONSTRATOR+ program.
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Gorawski, M., Skrzewski, M., Gorawski, M., Gorawska, A. (2015). Neural Networks in Petrol Station Objects Calibration. In: Wang, G., Zomaya, A., Martinez, G., Li, K. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2015. Lecture Notes in Computer Science(), vol 9532. Springer, Cham. https://doi.org/10.1007/978-3-319-27161-3_65
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DOI: https://doi.org/10.1007/978-3-319-27161-3_65
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