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A review study of predictive model blast vibration attenuation equation by using neural network as an evaluator
Wahyudi S.a, Shimada H.a, Simangunsong G.M.b, Sasaoka T.a, Matsui K.a, Kramadibrata S.b, Sulistianto B.b
a Department of Earth Resources Engineering, Kyushu University, Japan
b Department of Mining Engineering, Institut Teknologi Bandung, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]Over the years, a number of empirical attenuation equations (AEs) have been proposed. However, many established AEs are not accurate enough and sometimes they are confusing to use, particularly when the parameter associated with blasting and geological condition changes. Nowadays an accurate AE is an important requirement for a coal mine such as Kaltim Prima Coal (KPC) whose mining area in the East Kutai regency is located close to a residential area, the Sangatta town. In this study, several important and widely used predictors were used to predict peak particle velocity, while a back propagation artificial neural network is used as a comparator to evaluate the established AEs. Through this study, it is proposed that susceptibility assessment of conventional AEs be employed as tool to evaluate established AEs in a more adaptable way. © 2011 Taylor & Francis.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Artificial Neural Network,Attenuation equation (AE),Blast vibrations,Coal surface mine,Peak particle velocity (PPV)[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Artificial neural network (ANN),Attenuation equation (AE),Blast vibration,Coal surface mine,Peak particle velocity (PPV)[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1080/17480930.2010.509482[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]