Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Analysis of Mine Haul Road Performance Using Artificial Neural Network
In an opencast mine, several hundred tonnes are regularly carried by haul roads. Thus, mine haul road plays an important role for the transportation. Consequently, at every stage of the mining process, prediction of the performance of haul road is utmost essential. The mine haul road performance is analyzed during designing of a road for new mines and extending or maintenance of an existing haul road. Speed of vehicle movement, fuel cost of the truck and dust emission rate are the three attributes that define the performance of a haul road. This paper shows a novel ANN regression model to divine the values of these three attributes. The proposed ANN regression model is designed with eight input variables/attributes. The paper also presents the theoretical and statistical justifications of choosing these eight input variables. Extensive experiments are carried out by collecting the data from two study areas. The proposed regression model is compared with linear and quadratic regression approaches. The tenfold cross-validation results show the superiority of ANN model over competing models.
Analysis of Mine Haul Road Performance Using Artificial Neural Network
In an opencast mine, several hundred tonnes are regularly carried by haul roads. Thus, mine haul road plays an important role for the transportation. Consequently, at every stage of the mining process, prediction of the performance of haul road is utmost essential. The mine haul road performance is analyzed during designing of a road for new mines and extending or maintenance of an existing haul road. Speed of vehicle movement, fuel cost of the truck and dust emission rate are the three attributes that define the performance of a haul road. This paper shows a novel ANN regression model to divine the values of these three attributes. The proposed ANN regression model is designed with eight input variables/attributes. The paper also presents the theoretical and statistical justifications of choosing these eight input variables. Extensive experiments are carried out by collecting the data from two study areas. The proposed regression model is compared with linear and quadratic regression approaches. The tenfold cross-validation results show the superiority of ANN model over competing models.
Analysis of Mine Haul Road Performance Using Artificial Neural Network
J. Inst. Eng. India Ser. D
Chowdhury, Tarun (Autor:in) / Sinha, Suranjan (Autor:in) / Roy, Sudip Kumar (Autor:in)
01.06.2021
12 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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