Ontology type: schema:ScholarlyArticle
2019-03-01
AUTHORSHoang Nguyen, Carsten Drebenstedt, Xuan-Nam Bui, Dieu Tien Bui
ABSTRACTGround vibration (PPV) is one of the hazard effects induced by blasting operations in open-pit mines, which can affect the surrounding structures, particularly the stability of benches and slopes in open-pit mines, and impact underground water, railway, highway, and puzzling for neighboring communities. Therefore, controlling, accurate prediction, and mitigating blast-induced PPV are necessary. This study contributed a new computational model in predicting blast-induced PPV for the science community and practical engineering with high accuracy level. In this study, a novel hybrid artificial intelligence model based on the hierarchical k-means clustering algorithm (HKM) and artificial neural network (ANN), namely a HKM–ANN model, was considered and proposed for predicting blast-caused PPV in open-pit mines. Accordingly, input data were first clustered by the HKM algorithm, and then, the ANN models were developed based on the obtained clusters. For this aim, 185 blasting events were collected and analyzed. A hybrid model based on fuzzy c-means clustering (FCM) and support vector regression (SVR), i.e., FCM–SVR model, which was proposed by previous authors was also applied for comparison of results with our proposed HKM–ANN model. In addition, an empirical method, several ANN and SVR models (without clustering), FCM–ANN, and HKM–SVR were developed for comparison purposes. For measuring the performance of the improved models, coefficient determination (R2), root-mean-square error, and variance account for were used as the performance indicators. The results show that the HKM algorithm played a significant role in improving the accuracy of the ANN models. The proposed HKM–ANN model was the most superior model in estimating PPV caused by blasting operations in this study. More... »
PAGES1-19
http://scigraph.springernature.com/pub.10.1007/s11053-019-09470-z
DOIhttp://dx.doi.org/10.1007/s11053-019-09470-z
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1112475471
JSON-LD is the canonical representation for SciGraph data.
TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT
[
{
"@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json",
"about": [
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0801",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Artificial Intelligence and Image Processing",
"type": "DefinedTerm"
},
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/08",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Information and Computing Sciences",
"type": "DefinedTerm"
}
],
"author": [
{
"affiliation": {
"alternateName": "Hanoi University of Mining and Geology",
"id": "https://www.grid.ac/institutes/grid.440780.f",
"name": [
"Department of Surface Mining, Mining Faculty, Hanoi University of Mining and Geology, 18 Vien St., Duc Thang Ward, Bac Tu Liem Dist., Hanoi, Vietnam",
"Center for Mining, Electro-Mechanical Research, Hanoi University of Mining and Geology, 18 Vien St., Duc Thang Ward, Bac Tu Liem Dist., Hanoi, Vietnam"
],
"type": "Organization"
},
"familyName": "Nguyen",
"givenName": "Hoang",
"type": "Person"
},
{
"affiliation": {
"alternateName": "Freiberg University Of Mining And Technology",
"id": "https://www.grid.ac/institutes/grid.6862.a",
"name": [
"Institute of Mining and Special Engineering, Freiberg University of Mining and Technology, Gustav-Zeuner Strasse 1A, 09599, Freiberg, Sachsen, Germany"
],
"type": "Organization"
},
"familyName": "Drebenstedt",
"givenName": "Carsten",
"type": "Person"
},
{
"affiliation": {
"alternateName": "Hanoi University of Mining and Geology",
"id": "https://www.grid.ac/institutes/grid.440780.f",
"name": [
"Department of Surface Mining, Mining Faculty, Hanoi University of Mining and Geology, 18 Vien St., Duc Thang Ward, Bac Tu Liem Dist., Hanoi, Vietnam",
"Center for Mining, Electro-Mechanical Research, Hanoi University of Mining and Geology, 18 Vien St., Duc Thang Ward, Bac Tu Liem Dist., Hanoi, Vietnam"
],
"type": "Organization"
},
"familyName": "Bui",
"givenName": "Xuan-Nam",
"type": "Person"
},
{
"affiliation": {
"alternateName": "Duy Tan University",
"id": "https://www.grid.ac/institutes/grid.444918.4",
"name": [
"Institute of Research and Development, Duy Tan University, 550000, Da Nang, Vietnam"
],
"type": "Organization"
},
"familyName": "Bui",
"givenName": "Dieu Tien",
"type": "Person"
}
],
"citation": [
{
"id": "sg:pub.10.1007/s11053-010-9112-2",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1001227708",
"https://doi.org/10.1007/s11053-010-9112-2"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s11053-010-9112-2",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1001227708",
"https://doi.org/10.1007/s11053-010-9112-2"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1076/ijsm.18.1.60.23543",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1002437107"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.soildyn.2007.11.006",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1008398787"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.tust.2010.05.002",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1011724598"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.measurement.2015.07.019",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1013802018"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00366-016-0462-1",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1014257638",
"https://doi.org/10.1007/s00366-016-0462-1"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00366-016-0462-1",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1014257638",
"https://doi.org/10.1007/s00366-016-0462-1"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/s1364-0321(01)00006-5",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1014405502"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00521-016-2577-0",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1019069579",
"https://doi.org/10.1007/s00521-016-2577-0"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00521-016-2577-0",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1019069579",
"https://doi.org/10.1007/s00521-016-2577-0"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.tust.2016.12.009",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1022113557"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1002/(sici)1099-047x(199905)9:3<158::aid-mmce3>3.0.co;2-v",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1023355094"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00366-016-0438-1",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1025181832",
"https://doi.org/10.1007/s00366-016-0438-1"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s10661-010-1470-z",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1027134704",
"https://doi.org/10.1007/s10661-010-1470-z"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.neunet.2005.10.007",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1027340947"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00366-016-0475-9",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1027652714",
"https://doi.org/10.1007/s00366-016-0475-9"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00366-016-0475-9",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1027652714",
"https://doi.org/10.1007/s00366-016-0475-9"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s10706-004-7068-x",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1029378913",
"https://doi.org/10.1007/s10706-004-7068-x"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s12517-015-2057-3",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1029721959",
"https://doi.org/10.1007/s12517-015-2057-3"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s12665-015-4274-1",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1030000705",
"https://doi.org/10.1007/s12665-015-4274-1"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.jrmge.2013.11.001",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1030033154"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1023/a:1025175904545",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1030034358",
"https://doi.org/10.1023/a:1025175904545"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.ijrmms.2015.08.004",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1031219206"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1177/1077546311421052",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1031918352"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1177/1077546311421052",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1031918352"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s10706-016-0126-3",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1032770652",
"https://doi.org/10.1007/s10706-016-0126-3"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s10706-016-0126-3",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1032770652",
"https://doi.org/10.1007/s10706-016-0126-3"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1023/a:1025128021384",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1032950808",
"https://doi.org/10.1023/a:1025128021384"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/0167-9031(91)91642-u",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1033108567"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s13762-016-0979-2",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1033172041",
"https://doi.org/10.1007/s13762-016-0979-2"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s11053-014-9235-y",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1035951000",
"https://doi.org/10.1007/s11053-014-9235-y"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s12517-013-1174-0",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1038954491",
"https://doi.org/10.1007/s12517-013-1174-0"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.jrmge.2015.10.009",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1040292123"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00254-007-1143-6",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1041344277",
"https://doi.org/10.1007/s00254-007-1143-6"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00366-016-0442-5",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1042559958",
"https://doi.org/10.1007/s00366-016-0442-5"
],
"type": "CreativeWork"
},
{
"id": "https://app.dimensions.ai/details/publication/pub.1044216575",
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/978-1-4614-7138-7",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1044216575",
"https://doi.org/10.1007/978-1-4614-7138-7"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/978-1-4614-7138-7",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1044216575",
"https://doi.org/10.1007/978-1-4614-7138-7"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s10346-015-0557-6",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1044681977",
"https://doi.org/10.1007/s10346-015-0557-6"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.soildyn.2010.05.005",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1049071650"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/s1352-2310(97)00447-0",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1050703347"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/bf02289263",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1052823670",
"https://doi.org/10.1007/bf02289263"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00366-017-0501-6",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1083762550",
"https://doi.org/10.1007/s00366-017-0501-6"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00366-017-0501-6",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1083762550",
"https://doi.org/10.1007/s00366-017-0501-6"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.jafrearsci.2017.04.029",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1085399248"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s11053-017-9344-5",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1085573136",
"https://doi.org/10.1007/s11053-017-9344-5"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s11053-017-9344-5",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1085573136",
"https://doi.org/10.1007/s11053-017-9344-5"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s11053-017-9348-1",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1085756191",
"https://doi.org/10.1007/s11053-017-9348-1"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s11053-017-9348-1",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1085756191",
"https://doi.org/10.1007/s11053-017-9348-1"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s13762-017-1395-y",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1090744847",
"https://doi.org/10.1007/s13762-017-1395-y"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s13762-017-1395-y",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1090744847",
"https://doi.org/10.1007/s13762-017-1395-y"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s12665-017-6864-6",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1090952199",
"https://doi.org/10.1007/s12665-017-6864-6"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s12665-017-6864-6",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1090952199",
"https://doi.org/10.1007/s12665-017-6864-6"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s41062-017-0104-5",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1092261504",
"https://doi.org/10.1007/s41062-017-0104-5"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.sjbs.2017.11.022",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1092696805"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00366-017-0546-6",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1092708113",
"https://doi.org/10.1007/s00366-017-0546-6"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/fuzzy.2004.1375706",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1093801218"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/ijcnn.2002.1007487",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1094283672"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.arabjc.2017.12.024",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1100091486"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00366-018-0578-6",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1100288337",
"https://doi.org/10.1007/s00366-018-0578-6"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.ijrmms.2018.01.038",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1101080925"
],
"type": "CreativeWork"
},
{
"id": "https://app.dimensions.ai/details/publication/pub.1101215860",
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/978-3-319-75049-1",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1101215860",
"https://doi.org/10.1007/978-3-319-75049-1"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s41062-018-0137-4",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1103603254",
"https://doi.org/10.1007/s41062-018-0137-4"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s11053-018-9383-6",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1104238613",
"https://doi.org/10.1007/s11053-018-9383-6"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s11053-018-9385-4",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1105050357",
"https://doi.org/10.1007/s11053-018-9385-4"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s11053-018-9385-4",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1105050357",
"https://doi.org/10.1007/s11053-018-9385-4"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s11053-018-9385-4",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1105050357",
"https://doi.org/10.1007/s11053-018-9385-4"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s11053-018-9385-4",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1105050357",
"https://doi.org/10.1007/s11053-018-9385-4"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s11053-018-9385-4",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1105050357",
"https://doi.org/10.1007/s11053-018-9385-4"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1177/0957456518781858",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1105368440"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1177/0957456518781858",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1105368440"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1108/ec-08-2017-0290",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1105536866"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.ins.2018.07.049",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1105857522"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00521-018-3717-5",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1107055053",
"https://doi.org/10.1007/s00521-018-3717-5"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s11053-018-9424-1",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1109759308",
"https://doi.org/10.1007/s11053-018-9424-1"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.3934/dcdss.2019045",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1110243226"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.3934/dcdss.2019045",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1110243226"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.3934/dcdss.2019058",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1110243240"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.3934/dcdss.2019058",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1110243240"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.asoc.2019.01.042",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1111827631"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.asoc.2019.01.042",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1111827631"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s11053-019-09461-0",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1111840485",
"https://doi.org/10.1007/s11053-019-09461-0"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s11600-019-00268-4",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1112378322",
"https://doi.org/10.1007/s11600-019-00268-4"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s11600-019-00268-4",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1112378322",
"https://doi.org/10.1007/s11600-019-00268-4"
],
"type": "CreativeWork"
}
],
"datePublished": "2019-03-01",
"datePublishedReg": "2019-03-01",
"description": "Ground vibration (PPV) is one of the hazard effects induced by blasting operations in open-pit mines, which can affect the surrounding structures, particularly the stability of benches and slopes in open-pit mines, and impact underground water, railway, highway, and puzzling for neighboring communities. Therefore, controlling, accurate prediction, and mitigating blast-induced PPV are necessary. This study contributed a new computational model in predicting blast-induced PPV for the science community and practical engineering with high accuracy level. In this study, a novel hybrid artificial intelligence model based on the hierarchical k-means clustering algorithm (HKM) and artificial neural network (ANN), namely a HKM\u2013ANN model, was considered and proposed for predicting blast-caused PPV in open-pit mines. Accordingly, input data were first clustered by the HKM algorithm, and then, the ANN models were developed based on the obtained clusters. For this aim, 185 blasting events were collected and analyzed. A hybrid model based on fuzzy c-means clustering (FCM) and support vector regression (SVR), i.e., FCM\u2013SVR model, which was proposed by previous authors was also applied for comparison of results with our proposed HKM\u2013ANN model. In addition, an empirical method, several ANN and SVR models (without clustering), FCM\u2013ANN, and HKM\u2013SVR were developed for comparison purposes. For measuring the performance of the improved models, coefficient determination (R2), root-mean-square error, and variance account for were used as the performance indicators. The results show that the HKM algorithm played a significant role in improving the accuracy of the ANN models. The proposed HKM\u2013ANN model was the most superior model in estimating PPV caused by blasting operations in this study.",
"genre": "research_article",
"id": "sg:pub.10.1007/s11053-019-09470-z",
"inLanguage": [
"en"
],
"isAccessibleForFree": false,
"isPartOf": [
{
"id": "sg:journal.1136218",
"issn": [
"0961-1444",
"1520-7439"
],
"name": "Natural Resources Research",
"type": "Periodical"
}
],
"name": "Prediction of Blast-Induced Ground Vibration in an Open-Pit Mine by a Novel Hybrid Model Based on Clustering and Artificial Neural Network",
"pagination": "1-19",
"productId": [
{
"name": "readcube_id",
"type": "PropertyValue",
"value": [
"f2243d802318d39a1fb2846d543cd845c4b59b4372ca5e58f583fbbbe3a8f6b1"
]
},
{
"name": "doi",
"type": "PropertyValue",
"value": [
"10.1007/s11053-019-09470-z"
]
},
{
"name": "dimensions_id",
"type": "PropertyValue",
"value": [
"pub.1112475471"
]
}
],
"sameAs": [
"https://doi.org/10.1007/s11053-019-09470-z",
"https://app.dimensions.ai/details/publication/pub.1112475471"
],
"sdDataset": "articles",
"sdDatePublished": "2019-04-11T10:37",
"sdLicense": "https://scigraph.springernature.com/explorer/license/",
"sdPublisher": {
"name": "Springer Nature - SN SciGraph project",
"type": "Organization"
},
"sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000349_0000000349/records_113673_00000005.jsonl",
"type": "ScholarlyArticle",
"url": "https://link.springer.com/10.1007%2Fs11053-019-09470-z"
}
]Download the RDF metadata as: json-ld nt turtle xml License info
JSON-LD is a popular format for linked data which is fully compatible with JSON.
curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s11053-019-09470-z'
N-Triples is a line-based linked data format ideal for batch operations.
curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s11053-019-09470-z'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s11053-019-09470-z'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s11053-019-09470-z'
This table displays all metadata directly associated to this object as RDF triples.
308 TRIPLES
21 PREDICATES
89 URIs
16 LITERALS
5 BLANK NODES