{"id":"https://openalex.org/W2069879869","doi":"https://doi.org/10.1179/174328607x228875","title":"General regression neural network residual estimation for ore grade prediction of limestone deposit","display_name":"General regression neural network residual estimation for ore grade prediction of limestone deposit","publication_year":2007,"publication_date":"2007-09-01","ids":{"openalex":"https://openalex.org/W2069879869","doi":"https://doi.org/10.1179/174328607x228875","mag":"2069879869"},"language":"en","primary_location":{"id":"doi:10.1179/174328607x228875","doi":"https://doi.org/10.1179/174328607x228875","is_oa":false,"landing_page_url":"https://doi.org/10.1179/174328607x228875","pdf_url":null,"source":{"id":"https://openalex.org/S72171858","display_name":"Mining Technology Transactions of the Institutions of Mining and Metallurgy","issn_l":"0371-7844","issn":["0371-7844","1474-9009","1743-2863","2572-6668","2572-6676"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-c","jufo-1","poland-20","russia-white-list-2"],"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547","https://openalex.org/P4310320449"],"host_organization_lineage_names":["Taylor & Francis","Informa"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Mining Technology: Transactions of the Institutions of Mining and Metallurgy: Section A","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"S. Chatterjee","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"S. Chatterjee","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109183845","display_name":"Sukumar Bandopadhyay","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"S. Bandopadhyay","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003587205","display_name":"Rajive Ganguli","orcid":"https://orcid.org/0000-0003-0614-9626","observed_orcids":["https://orcid.org/0000-0003-0614-9626"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"R. Ganguli","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057816026","display_name":"Ashis Bhattacherjee","orcid":"https://orcid.org/0000-0002-2615-1929","observed_orcids":["https://orcid.org/0000-0002-2615-1929"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"A. Bhattacherjee","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089043863","display_name":"B. Samanta","orcid":"https://orcid.org/0000-0002-2120-1106","observed_orcids":["https://orcid.org/0000-0002-2120-1106","https://orcid.org/0000-0003-3820-0924"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"B. Samanta","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5068724120","display_name":"Samir Kumar Pal","orcid":"https://orcid.org/0000-0002-3140-6826","observed_orcids":["https://orcid.org/0000-0002-3140-6826"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"S. K. Pal","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":4150,"currency":"USD","value_usd":4150},"apc_paid":null,"fwci":0.5466,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.70713073,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":97},"biblio":{"volume":"116","issue":"3","first_page":"89","last_page":"99"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13067","display_name":"Geological Modeling and Analysis","score":0.5928000211715698,"subfield":{"id":"https://openalex.org/subfields/1906","display_name":"Geochemistry and Petrology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13067","display_name":"Geological Modeling and Analysis","score":0.5928000211715698,"subfield":{"id":"https://openalex.org/subfields/1906","display_name":"Geochemistry and Petrology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10770","display_name":"Soil Geostatistics and Mapping","score":0.09759999811649323,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.0925000011920929,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/generalized-regression-neural-network","display_name":"generalized regression neural network","score":0.8659999966621399},{"id":"https://openalex.org/keywords/residual-kriging","display_name":"residual kriging","score":0.8090000152587891},{"id":"https://openalex.org/keywords/ore-grade-prediction","display_name":"ore grade prediction","score":0.8529999852180481},{"id":"https://openalex.org/keywords/limestone-deposits","display_name":"limestone deposits","score":0.9779999852180481},{"id":"https://openalex.org/keywords/spatial-variability","display_name":"spatial variability","score":0.7490000128746033},{"id":"https://openalex.org/keywords/ordinary-kriging","display_name":"ordinary kriging","score":0.8669999837875366}],"concepts":[{"id":"https://openalex.org/C81692654","wikidata":"https://www.wikidata.org/wiki/Q225926","display_name":"Kriging","level":2,"score":0.9277161359786987},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.8033336997032166},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.696243405342102},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.6593700051307678},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.5804423689842224},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5303336381912231},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.401542067527771},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.36911675333976746},{"id":"https://openalex.org/C159390177","wikidata":"https://www.wikidata.org/wiki/Q9161265","display_name":"Soil science","level":1,"score":0.3556603789329529},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.3359922766685486},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3071562647819519},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.24812710285186768},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.23663267493247986},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1179/174328607x228875","doi":"https://doi.org/10.1179/174328607x228875","is_oa":false,"landing_page_url":"https://doi.org/10.1179/174328607x228875","pdf_url":null,"source":{"id":"https://openalex.org/S72171858","display_name":"Mining Technology Transactions of the Institutions of Mining and Metallurgy","issn_l":"0371-7844","issn":["0371-7844","1474-9009","1743-2863","2572-6668","2572-6676"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-c","jufo-1","poland-20","russia-white-list-2"],"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547","https://openalex.org/P4310320449"],"host_organization_lineage_names":["Taylor & Francis","Informa"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Mining Technology: Transactions of the Institutions of Mining and Metallurgy: Section A","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W415261","https://openalex.org/W285676759","https://openalex.org/W624587259","https://openalex.org/W651238688","https://openalex.org/W1533618852","https://openalex.org/W2026284034","https://openalex.org/W2029516643","https://openalex.org/W2143022286","https://openalex.org/W2149723649","https://openalex.org/W2891163915","https://openalex.org/W3138949179","https://openalex.org/W4238717354","https://openalex.org/W4247422722","https://openalex.org/W4388284198"],"related_works":["https://openalex.org/W7128629267","https://openalex.org/W2587932242","https://openalex.org/W4291145168","https://openalex.org/W4281294180","https://openalex.org/W7124596047","https://openalex.org/W4406933756","https://openalex.org/W4412659234","https://openalex.org/W2014215739","https://openalex.org/W2057163195","https://openalex.org/W7172520507"],"abstract_inverted_index":{"The":[0,75,102,141,175],"aim":[1],"of":[2,17,30,46,54,143,159,167],"the":[3,13,28,36,43,47,55,86,91,99,108,116,120,138,144,157,165,168,172,180,189,200],"present":[4],"paper":[5],"is":[6,57],"to":[7,41,59,84,97],"provide":[8],"an":[9],"improved":[10],"estimator":[11],"for":[12],"ore":[14],"grade":[15,121],"prediction":[16],"a":[18,152,196],"limestone":[19],"deposit":[20,56],"in":[21],"India.":[22],"A":[23],"generalised":[24],"modelling":[25],"framework":[26],"with":[27,164],"help":[29],"general":[31,76],"regression":[32,77],"neural":[33,78],"network":[34,79],"and":[35,71,90,113,119,133,156,171],"ordinary":[37,92,173,190],"kriging":[38,93,147,183],"was":[39,82,95,105,149],"formulated":[40],"capture":[42,85,98],"spatial":[44,52,66,87,109],"variability":[45,53],"deposit.":[48],"In":[49],"this":[50,160],"platform,":[51],"assumed":[58],"be":[60],"characterised":[61],"by":[62],"three":[63],"major":[64],"components:":[65],"trend":[67,88],"component,":[68,70,89],"regionalised":[69,100],"purely":[72],"random":[73],"component.":[74,101],"(GRNN)":[80],"model":[81,104,148,161,184],"used":[83],"technique":[94],"implemented":[96],"GRNN":[103,145,169,181,201],"developed":[106],"using":[107,151],"coordinates":[110],"(Northing,":[111],"Easting":[112],"Elevation)":[114],"as":[115,137],"input":[117],"parameters":[118],"attributes":[122],"(CaO,":[123],"Al":[124],"2":[125,130,135],"O":[126,131],"3":[127,132],",":[128],"Fe":[129],"SiO":[134],")":[136],"output":[139],"parameters.":[140],"performance":[142],"residual":[146,182],"tested":[150],"testing":[153],"data":[154],"set,":[155],"outputs":[158,166],"were":[162],"compared":[163],"model,":[170],"kriging.":[174],"comparative":[176],"results":[177],"show":[178],"that":[179],"provided":[185],"significant":[186],"improvement":[187,198],"over":[188,199],"kriging,":[191],"however,":[192],"it":[193],"only":[194],"shows":[195],"marginal":[197],"model.":[202]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2013,"cited_by_count":1}],"updated_date":"2026-10-01T08:54:57.152042","created_date":"2016-06-24T00:00:00"}
