FTIR-PAS coupled to partial least squares for prediction of ash content, volatile matter, fixed carbon and calorific value of coal
[Display omitted] •Prective model for properties of coal using FT-IR PAS and PLS are proposed.•Tests and statistical parameters indicate good performance of the models.•An alternative strategy to determine complexity and selection models is presented. Fourier Transform Infrared Photoacoustic Spectro...
Gespeichert in:
| Veröffentlicht in: | Fuel (Guildford) 2018-08, Vol.226, p.536-544 |
|---|---|
| Hauptverfasser: | , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 544 |
|---|---|
| container_issue | |
| container_start_page | 536 |
| container_title | Fuel (Guildford) |
| container_volume | 226 |
| creator | Román Gómez, Yesid Cabanzo Hernández, Rafael Guerrero, Jáder Enrique Mejía-Ospino, Enrique |
| description | [Display omitted]
•Prective model for properties of coal using FT-IR PAS and PLS are proposed.•Tests and statistical parameters indicate good performance of the models.•An alternative strategy to determine complexity and selection models is presented.
Fourier Transform Infrared Photoacoustic Spectroscopy (FT-IR PAS) and multivariate calibration using partial least squares (PLS) has been coupled for the development of predictive models of ash content, volatile matter, fixed carbon and calorific value of coal samples from several mines of Colombia. In the chemometric approach, a novel alternative is proposed to define the complexity and the selection of the models. According to tests and statistical criteria, at a 95% confidence level, the selected models demonstrate their linear character and a true correlation between the reference values and the predicted values. Results provide standard error of cross-validation (SECV) of 1.22 wt%, 0.78 wt%, 1.08 wt% and 0.75 MJ kg−1 predicting ash, volatile matter (VM), fixed carbon (FC) and calorific value, respectively. |
| doi_str_mv | 10.1016/j.fuel.2018.04.040 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2089868225</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S001623611830663X</els_id><sourcerecordid>2089868225</sourcerecordid><originalsourceid>FETCH-LOGICAL-c328t-8a0771e4bdd588bc69c327c09c8a482cc88d177ccb8bb28c1a28168d3f26b7ac3</originalsourceid><addsrcrecordid>eNp9kE9r3DAQxUVpodu0X6AnQa7xRpK91izkEkL-QSChSc5CHo-JFsVyJHlJr_3kldmcAwMzDO-9GX6M_ZZiLYVsT3frYSa_VkLCWjSlxBe2kqDrSstN_ZWtRFFVqm7ld_YjpZ0QQsOmWbF_V0-3f6qH80eOYZ489TwHPtmYnfXck02Zp7fZRkp8CJFPkXqH2YWRh4Hb9FJsY6Yxn_B98DY7T_zV5kzxhA_uvcShjV1R23EZfYhucMj31s-0JGCw_if7Nlif6NdHP2LPV5dPFzfV3f317cX5XYW1glyBFVpLarq-3wB02G7LXqPYItgGFCJAL7VG7KDrFKC0CmQLfT2ottMW6yN2fMidYnibKWWzC3Mcy0mjBGyhBaU2RaUOKowhpUiDmaJ7tfGvkcIsrM3OLKzNwtqIppQoprODicr_e0fRJHQ0YoEVCbPpg_vM_h-N6IkH</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2089868225</pqid></control><display><type>article</type><title>FTIR-PAS coupled to partial least squares for prediction of ash content, volatile matter, fixed carbon and calorific value of coal</title><source>Elsevier ScienceDirect Journals Complete</source><creator>Román Gómez, Yesid ; Cabanzo Hernández, Rafael ; Guerrero, Jáder Enrique ; Mejía-Ospino, Enrique</creator><creatorcontrib>Román Gómez, Yesid ; Cabanzo Hernández, Rafael ; Guerrero, Jáder Enrique ; Mejía-Ospino, Enrique</creatorcontrib><description>[Display omitted]
•Prective model for properties of coal using FT-IR PAS and PLS are proposed.•Tests and statistical parameters indicate good performance of the models.•An alternative strategy to determine complexity and selection models is presented.
Fourier Transform Infrared Photoacoustic Spectroscopy (FT-IR PAS) and multivariate calibration using partial least squares (PLS) has been coupled for the development of predictive models of ash content, volatile matter, fixed carbon and calorific value of coal samples from several mines of Colombia. In the chemometric approach, a novel alternative is proposed to define the complexity and the selection of the models. According to tests and statistical criteria, at a 95% confidence level, the selected models demonstrate their linear character and a true correlation between the reference values and the predicted values. Results provide standard error of cross-validation (SECV) of 1.22 wt%, 0.78 wt%, 1.08 wt% and 0.75 MJ kg−1 predicting ash, volatile matter (VM), fixed carbon (FC) and calorific value, respectively.</description><identifier>ISSN: 0016-2361</identifier><identifier>EISSN: 1873-7153</identifier><identifier>DOI: 10.1016/j.fuel.2018.04.040</identifier><language>eng</language><publisher>Kidlington: Elsevier Ltd</publisher><subject>Ashes ; Calibration ; Calorific value ; Carbon ; Coal ; Coal mines ; Confidence intervals ; Fourier transforms ; Infrared spectroscopy ; Least squares ; Mathematical models ; Multivariate calibration ; Photoacoustic spectroscopy ; Prediction models ; Proximate analysis ; Spectrum analysis ; Standard error ; Statistical analysis ; Statistical methods ; Studies</subject><ispartof>Fuel (Guildford), 2018-08, Vol.226, p.536-544</ispartof><rights>2018 Elsevier Ltd</rights><rights>Copyright Elsevier BV Aug 15, 2018</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c328t-8a0771e4bdd588bc69c327c09c8a482cc88d177ccb8bb28c1a28168d3f26b7ac3</citedby><cites>FETCH-LOGICAL-c328t-8a0771e4bdd588bc69c327c09c8a482cc88d177ccb8bb28c1a28168d3f26b7ac3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.fuel.2018.04.040$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3548,27923,27924,45994</link.rule.ids></links><search><creatorcontrib>Román Gómez, Yesid</creatorcontrib><creatorcontrib>Cabanzo Hernández, Rafael</creatorcontrib><creatorcontrib>Guerrero, Jáder Enrique</creatorcontrib><creatorcontrib>Mejía-Ospino, Enrique</creatorcontrib><title>FTIR-PAS coupled to partial least squares for prediction of ash content, volatile matter, fixed carbon and calorific value of coal</title><title>Fuel (Guildford)</title><description>[Display omitted]
•Prective model for properties of coal using FT-IR PAS and PLS are proposed.•Tests and statistical parameters indicate good performance of the models.•An alternative strategy to determine complexity and selection models is presented.
Fourier Transform Infrared Photoacoustic Spectroscopy (FT-IR PAS) and multivariate calibration using partial least squares (PLS) has been coupled for the development of predictive models of ash content, volatile matter, fixed carbon and calorific value of coal samples from several mines of Colombia. In the chemometric approach, a novel alternative is proposed to define the complexity and the selection of the models. According to tests and statistical criteria, at a 95% confidence level, the selected models demonstrate their linear character and a true correlation between the reference values and the predicted values. Results provide standard error of cross-validation (SECV) of 1.22 wt%, 0.78 wt%, 1.08 wt% and 0.75 MJ kg−1 predicting ash, volatile matter (VM), fixed carbon (FC) and calorific value, respectively.</description><subject>Ashes</subject><subject>Calibration</subject><subject>Calorific value</subject><subject>Carbon</subject><subject>Coal</subject><subject>Coal mines</subject><subject>Confidence intervals</subject><subject>Fourier transforms</subject><subject>Infrared spectroscopy</subject><subject>Least squares</subject><subject>Mathematical models</subject><subject>Multivariate calibration</subject><subject>Photoacoustic spectroscopy</subject><subject>Prediction models</subject><subject>Proximate analysis</subject><subject>Spectrum analysis</subject><subject>Standard error</subject><subject>Statistical analysis</subject><subject>Statistical methods</subject><subject>Studies</subject><issn>0016-2361</issn><issn>1873-7153</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNp9kE9r3DAQxUVpodu0X6AnQa7xRpK91izkEkL-QSChSc5CHo-JFsVyJHlJr_3kldmcAwMzDO-9GX6M_ZZiLYVsT3frYSa_VkLCWjSlxBe2kqDrSstN_ZWtRFFVqm7ld_YjpZ0QQsOmWbF_V0-3f6qH80eOYZ489TwHPtmYnfXck02Zp7fZRkp8CJFPkXqH2YWRh4Hb9FJsY6Yxn_B98DY7T_zV5kzxhA_uvcShjV1R23EZfYhucMj31s-0JGCw_if7Nlif6NdHP2LPV5dPFzfV3f317cX5XYW1glyBFVpLarq-3wB02G7LXqPYItgGFCJAL7VG7KDrFKC0CmQLfT2ottMW6yN2fMidYnibKWWzC3Mcy0mjBGyhBaU2RaUOKowhpUiDmaJ7tfGvkcIsrM3OLKzNwtqIppQoprODicr_e0fRJHQ0YoEVCbPpg_vM_h-N6IkH</recordid><startdate>20180815</startdate><enddate>20180815</enddate><creator>Román Gómez, Yesid</creator><creator>Cabanzo Hernández, Rafael</creator><creator>Guerrero, Jáder Enrique</creator><creator>Mejía-Ospino, Enrique</creator><general>Elsevier Ltd</general><general>Elsevier BV</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7QF</scope><scope>7QO</scope><scope>7QQ</scope><scope>7SC</scope><scope>7SE</scope><scope>7SP</scope><scope>7SR</scope><scope>7T7</scope><scope>7TA</scope><scope>7TB</scope><scope>7U5</scope><scope>8BQ</scope><scope>8FD</scope><scope>C1K</scope><scope>F28</scope><scope>FR3</scope><scope>H8D</scope><scope>H8G</scope><scope>JG9</scope><scope>JQ2</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>P64</scope></search><sort><creationdate>20180815</creationdate><title>FTIR-PAS coupled to partial least squares for prediction of ash content, volatile matter, fixed carbon and calorific value of coal</title><author>Román Gómez, Yesid ; Cabanzo Hernández, Rafael ; Guerrero, Jáder Enrique ; Mejía-Ospino, Enrique</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c328t-8a0771e4bdd588bc69c327c09c8a482cc88d177ccb8bb28c1a28168d3f26b7ac3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Ashes</topic><topic>Calibration</topic><topic>Calorific value</topic><topic>Carbon</topic><topic>Coal</topic><topic>Coal mines</topic><topic>Confidence intervals</topic><topic>Fourier transforms</topic><topic>Infrared spectroscopy</topic><topic>Least squares</topic><topic>Mathematical models</topic><topic>Multivariate calibration</topic><topic>Photoacoustic spectroscopy</topic><topic>Prediction models</topic><topic>Proximate analysis</topic><topic>Spectrum analysis</topic><topic>Standard error</topic><topic>Statistical analysis</topic><topic>Statistical methods</topic><topic>Studies</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Román Gómez, Yesid</creatorcontrib><creatorcontrib>Cabanzo Hernández, Rafael</creatorcontrib><creatorcontrib>Guerrero, Jáder Enrique</creatorcontrib><creatorcontrib>Mejía-Ospino, Enrique</creatorcontrib><collection>CrossRef</collection><collection>Aluminium Industry Abstracts</collection><collection>Biotechnology Research Abstracts</collection><collection>Ceramic Abstracts</collection><collection>Computer and Information Systems Abstracts</collection><collection>Corrosion Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Materials Business File</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Copper Technical Reference Library</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Biotechnology and BioEngineering Abstracts</collection><jtitle>Fuel (Guildford)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Román Gómez, Yesid</au><au>Cabanzo Hernández, Rafael</au><au>Guerrero, Jáder Enrique</au><au>Mejía-Ospino, Enrique</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>FTIR-PAS coupled to partial least squares for prediction of ash content, volatile matter, fixed carbon and calorific value of coal</atitle><jtitle>Fuel (Guildford)</jtitle><date>2018-08-15</date><risdate>2018</risdate><volume>226</volume><spage>536</spage><epage>544</epage><pages>536-544</pages><issn>0016-2361</issn><eissn>1873-7153</eissn><abstract>[Display omitted]
•Prective model for properties of coal using FT-IR PAS and PLS are proposed.•Tests and statistical parameters indicate good performance of the models.•An alternative strategy to determine complexity and selection models is presented.
Fourier Transform Infrared Photoacoustic Spectroscopy (FT-IR PAS) and multivariate calibration using partial least squares (PLS) has been coupled for the development of predictive models of ash content, volatile matter, fixed carbon and calorific value of coal samples from several mines of Colombia. In the chemometric approach, a novel alternative is proposed to define the complexity and the selection of the models. According to tests and statistical criteria, at a 95% confidence level, the selected models demonstrate their linear character and a true correlation between the reference values and the predicted values. Results provide standard error of cross-validation (SECV) of 1.22 wt%, 0.78 wt%, 1.08 wt% and 0.75 MJ kg−1 predicting ash, volatile matter (VM), fixed carbon (FC) and calorific value, respectively.</abstract><cop>Kidlington</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.fuel.2018.04.040</doi><tpages>9</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0016-2361 |
| ispartof | Fuel (Guildford), 2018-08, Vol.226, p.536-544 |
| issn | 0016-2361 1873-7153 |
| language | eng |
| recordid | cdi_proquest_journals_2089868225 |
| source | Elsevier ScienceDirect Journals Complete |
| subjects | Ashes Calibration Calorific value Carbon Coal Coal mines Confidence intervals Fourier transforms Infrared spectroscopy Least squares Mathematical models Multivariate calibration Photoacoustic spectroscopy Prediction models Proximate analysis Spectrum analysis Standard error Statistical analysis Statistical methods Studies |
| title | FTIR-PAS coupled to partial least squares for prediction of ash content, volatile matter, fixed carbon and calorific value of coal |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-10T19%3A45%3A32IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=FTIR-PAS%20coupled%20to%20partial%20least%20squares%20for%20prediction%20of%20ash%20content,%20volatile%20matter,%20fixed%20carbon%20and%20calorific%20value%20of%20coal&rft.jtitle=Fuel%20(Guildford)&rft.au=Rom%C3%A1n%20G%C3%B3mez,%20Yesid&rft.date=2018-08-15&rft.volume=226&rft.spage=536&rft.epage=544&rft.pages=536-544&rft.issn=0016-2361&rft.eissn=1873-7153&rft_id=info:doi/10.1016/j.fuel.2018.04.040&rft_dat=%3Cproquest_cross%3E2089868225%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2089868225&rft_id=info:pmid/&rft_els_id=S001623611830663X&rfr_iscdi=true |