Matches in SemOpenAlex for { <https://semopenalex.org/work/W4322631005> ?p ?o ?g. }
Showing items 1 to 76 of
76
with 100 items per page.
- W4322631005 endingPage "340" @default.
- W4322631005 startingPage "340" @default.
- W4322631005 abstract "In a multivariate database, the missing data can be obtained through several imputation techniques, which are particularly useful for data that are difficult to obtain, for any reason, or have high uncertainties or scarce variables. A Self-Organizing Maps (SOM) neural network is an effective tool for the analysis of multidimensional data applied for the imputation of data. In this paper, data from drilling were used for training, testing, and validation using the variables: total Au recovery (%), which means gold recovery from a gravity concentration plus hydrometallurgical process, Au (g/t), As (ppm), S (%), Al2O3 (%), CaO (%), K2O (%), and MgO (%). After training, the partial omission of Au content and recovery was carried out, from 10% to 50%, to evaluate the data imputation performance for those variables. The results imputed by the SOM were compared with the original data values and evaluated according to descriptive statistics; the results indicated a determination coefficient of 85% when 50% of the data were omitted and 93% when 10% of the data were omitted. Once demonstrated, the correlation between the original data and SOM imputation analysis can help geologists and metallurgists to obtain results with a high degree of reliability of metallurgical recovery through related chemical variables, making it possible to implement SOM analysis as a powerful tool to input analytical data. One of the practical applications of the proposed model is to produce a pattern of imputed data that can be a good alternative in the construction or generation of a synthetic geometallurgical database with missing data." @default.
- W4322631005 created "2023-03-01" @default.
- W4322631005 creator A5022626196 @default.
- W4322631005 creator A5074863274 @default.
- W4322631005 creator A5081723123 @default.
- W4322631005 date "2023-02-28" @default.
- W4322631005 modified "2023-10-13" @default.
- W4322631005 title "Imputation of Gold Recovery Data from Low Grade Gold Ore Using Artificial Neural Network" @default.
- W4322631005 cites W1978765357 @default.
- W4322631005 cites W1981592992 @default.
- W4322631005 cites W1990517717 @default.
- W4322631005 cites W1992263854 @default.
- W4322631005 cites W2009931963 @default.
- W4322631005 cites W2014774000 @default.
- W4322631005 cites W2026100150 @default.
- W4322631005 cites W2028933374 @default.
- W4322631005 cites W2042387456 @default.
- W4322631005 cites W2069150656 @default.
- W4322631005 cites W2077687543 @default.
- W4322631005 cites W2081176670 @default.
- W4322631005 cites W2110802877 @default.
- W4322631005 cites W2402657413 @default.
- W4322631005 cites W2912365682 @default.
- W4322631005 cites W2944400040 @default.
- W4322631005 cites W2982152486 @default.
- W4322631005 cites W4245176872 @default.
- W4322631005 cites W65738273 @default.
- W4322631005 doi "https://doi.org/10.3390/min13030340" @default.
- W4322631005 hasPublicationYear "2023" @default.
- W4322631005 type Work @default.
- W4322631005 citedByCount "1" @default.
- W4322631005 crossrefType "journal-article" @default.
- W4322631005 hasAuthorship W4322631005A5022626196 @default.
- W4322631005 hasAuthorship W4322631005A5074863274 @default.
- W4322631005 hasAuthorship W4322631005A5081723123 @default.
- W4322631005 hasBestOaLocation W43226310051 @default.
- W4322631005 hasConcept C105795698 @default.
- W4322631005 hasConcept C119857082 @default.
- W4322631005 hasConcept C124101348 @default.
- W4322631005 hasConcept C154945302 @default.
- W4322631005 hasConcept C161584116 @default.
- W4322631005 hasConcept C33923547 @default.
- W4322631005 hasConcept C41008148 @default.
- W4322631005 hasConcept C50644808 @default.
- W4322631005 hasConcept C58041806 @default.
- W4322631005 hasConcept C9357733 @default.
- W4322631005 hasConceptScore W4322631005C105795698 @default.
- W4322631005 hasConceptScore W4322631005C119857082 @default.
- W4322631005 hasConceptScore W4322631005C124101348 @default.
- W4322631005 hasConceptScore W4322631005C154945302 @default.
- W4322631005 hasConceptScore W4322631005C161584116 @default.
- W4322631005 hasConceptScore W4322631005C33923547 @default.
- W4322631005 hasConceptScore W4322631005C41008148 @default.
- W4322631005 hasConceptScore W4322631005C50644808 @default.
- W4322631005 hasConceptScore W4322631005C58041806 @default.
- W4322631005 hasConceptScore W4322631005C9357733 @default.
- W4322631005 hasIssue "3" @default.
- W4322631005 hasLocation W43226310051 @default.
- W4322631005 hasOpenAccess W4322631005 @default.
- W4322631005 hasPrimaryLocation W43226310051 @default.
- W4322631005 hasRelatedWork W2052457798 @default.
- W4322631005 hasRelatedWork W2079738624 @default.
- W4322631005 hasRelatedWork W2168489635 @default.
- W4322631005 hasRelatedWork W2541565311 @default.
- W4322631005 hasRelatedWork W2784019465 @default.
- W4322631005 hasRelatedWork W3004657493 @default.
- W4322631005 hasRelatedWork W3049453136 @default.
- W4322631005 hasRelatedWork W3183875135 @default.
- W4322631005 hasRelatedWork W4294843249 @default.
- W4322631005 hasRelatedWork W4385711159 @default.
- W4322631005 hasVolume "13" @default.
- W4322631005 isParatext "false" @default.
- W4322631005 isRetracted "false" @default.
- W4322631005 workType "article" @default.