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Ukunukubezeka komhlabathi kuyinkinga enkulu ebangelwa imisebenzi yabantu.Ukusatshalaliswa kwendawo kwezinto ezingaba ubuthi (PTEs) kuyahlukahluka ezindaweni eziningi zasemadolobheni nasezindaweni eziseduze namadolobha.Ngakho-ke, kunzima ukubikezela ngokwendawo okuqukethwe kwama-PTEs enhlabathini enjalo.Isamba samasampula angu-115 atholwe ku-Frydek Mistek e-Czech Republic.), i-magnesium nick)Nick) ukugxila kwanqunywa kusetshenziswa i-spectrometry yokukhishwa kwe-plasma ehlanganisiwe.I-variable yempendulo i-Ni futhi izibikezelo ziyi-Ca, Mg, ne-K.I-matrix yokuhlotshaniswa phakathi kokuguquguquka kwempendulo kanye nokuguquguquka kokubikezela kubonisa ukuhlobana okwanelisayo phakathi kwezinto.Imiphumela yokubikezela ibonise ukuthi Ukusekela Umshini Wokuhlela IVector (SVMR) wenze kahle, nakuba impande yayo elinganiselwe ye-9mg kanye nephutha lesikwele esingu-7 mgSE (mg45) isho isikwele se-7 (mgSE). Iphutha eliphelele (MAE) (166.946 mg/kg) lalingaphezulu kunezinye izindlela ezisetshenziswayo.Amamodeli axutshiwe e-Empirical Bayesian Kriging-Multiple Linear Regression (EBK-MLR) asebenza kahle, njengoba kufakazelwa ama-coefficients wokunquma angaphansi kuka-0.1.Imodeli ye-Empirical Bayesian Kriging-Sups, imodeli ye-Empirical Bayesian Kriging-Sup, imodeli engcono kakhulu ye-SVR enamanani aphansi e-RMSE (95.479 mg/kg) kanye ne-MAE (77.368 mg/kg) kanye ne-coefficient ephezulu yokunquma (R2 = 0.637).Ukukhiphayo kwesu lokumodela le-EBK-SVMR kubonakala kusetshenziswa imephu ezihlelayo. Ama-neurons ahlanganisiwe endizeni yemodeli ye-hybrid imodeli ye-hybridK ibikezela amaphethini wombala we-NiEB abikezela i-CakMg yombala eminingi kanye nenhlabathi eseduze nedolobha.Imiphumela ibonisa ukuthi ukuhlanganisa i-EBK ne-SVMR kuyindlela ephumelelayo yokubikezela ukugxila kuka-Ni emhlabathini wasemadolobheni kanye naseduze kwedolobha.
I-Nickel (Ni) ibhekwa njenge-micronutrient yezitshalo ngoba inomthelela ekulungiseni i-nitrogen emkhathini (N) kanye ne-urea metabolism, kokubili okudingekayo ekuhlumeni kwembewu. zidinga ukufakwa kukamanyolo owenziwe nge-nickel ukuze kuthuthukiswe i-nitrogen fixation2.Ukusetshenziswa okuqhubekayo komanyolo owenziwe nge-nickel ukuze kunothisa umhlabathi futhi kwandiswe ikhono le-legumes ukulungisa i-nitrogen enhlabathini ngokuqhubekayo kwandisa ukugcwala kwe-nickel emhlabathini.Nakuba i-nickel iyi-micronutrient yezitshalo, ukungenisa kwayo ngokweqile emhlabathini kungalimaza umhlabathi we-nick futhi kunciphise i-pH ye-hinder. ukumuncwa kwensimbi njengesakhi esibalulekile ekukhuleni kwezitshalo1.Ngokusho kwe-Liu3, i-Ni itholwe iyisici esibalulekile se-17 esidingekayo ekuthuthukisweni nasekukhuleni kwezitshalo.Ngaphezu kwendima ye-nickel ekuthuthukisweni nasekukhuleni kwezitshalo, abantu bayayidinga ukuze benze izinto ezihlukahlukene. I-nickel emikhakheni eyahlukene yezimboni. Ngaphezu kwalokho, ama-alloys asekelwe ku-nickel kanye nezinto ezenziwe nge-electroplated zisetshenziswe kakhulu ku-kitchenware, izesekeli ze-ballroom, izimpahla zembonini yokudla, ugesi, izintambo kanye nekhebula, ama-jet turbines, izifakelo zokuhlinza, izindwangu, nokwakhiwa kwemikhumbi5. kune-anthropogenic4,6.Imithombo yemvelo ye-nickel ihlanganisa ukuqhuma kwentaba-mlilo, uhlaza, imililo yamahlathi, kanye nezinqubo zokuma komhlaba; kodwa-ke, imithombo ye-anthropogenic ihlanganisa amabhethri e-nickel/cadmium embonini yensimbi, i-electroplating, i-arc welding, idizili kanye namafutha kaphethiloli, kanye nesisi esikhipha umoya ophuma ekushisweni kwamalahle nokushiswa kwemfucuza nokushiswa kodaka Ukunqwabelana kwe-Nickel7,8.Ngokuka-Freedman no-Hutchinson9 no-Manyiwa et. I-10, imithombo eyinhloko yokungcoliswa kwenhlabathi engaphezulu endaweni eseduze neseduze ikakhulukazi izincibilikisi nezimayini ezisekelwe ku-nickel-copper.Inhlabathi ephezulu ezungeze indawo yokuhluza i-nickel-copper yase-Sudbury e-Canada yayinezinga eliphakeme kakhulu lokungcoliswa kwe-nickel ku-26,000 mg/kg11. Inhlabathi yaseNorway11.Ngokuvumelana ne-Alms et al. 12, inani le-nickel elikhiphekayo le-HNO3 endaweni ephezulu yokulinywa yesifunda (ukukhiqizwa kwe-nickel eRussia) lalisuka ku-6.25 liye ku-136.88 mg/kg, elihambisana nenani elingu-30.43 mg/kg kanye nokugxilwa kwesisekelo okungu-25 mg/kg. Ngokuvumelana ne-kabata 11, ukusetshenziswa kwenhlabathi yasemadolobheni e-fosforasi inhlabathi yasemadolobheni noma inhlabathi yezolimo izinkathi zezitshalo ezilandelanayo zingafaka noma zingcolise umhlabathi.Imiphumela engaba khona ye-nickel kubantu ingase iholele kumdlavuza ngokusebenzisa i-mutagenesis, umonakalo we-chromosomal, isizukulwane se-Z-DNA, ukulungiswa kwe-DNA excision evinjiwe, noma izinqubo ze-epigenetic13.Ekuhlolweni kwezilwane, i-nickel itholakale inamandla okubangela izinhlobonhlobo zezimila, futhi i-carcinogenic nickel nickel complexes ingase i-epigenetic.
Ukuhlola ukungcoliswa komhlabathi kuye kwachuma ezikhathini zamuva nje ngenxa yohlu olubanzi lwezinkinga eziphathelene nempilo ezivela ebudlelwaneni bezitshalo zomhlabathi, inhlabathi nomhlabathi ubudlelwano bezinto eziphilayo, ukucekelwa phansi kwemvelo, nokuhlola umthelela wendawo. i-predictive soil mapping (PSM) ithuthuke kakhulu.Ngokusho kukaMinasny noMcBratney16, i-predictive soil mapping (DSM) has proven to be a prominent subdiscipline of soil science.Lagacherie and McBratney, 2006 define DSM as “the creation and filling of spatial soil information systems through the use of in sipatial-observatory method amasistimu wokucabanga”.McBratney et al. I-17 iveza ukuthi i-DSM yesimanje noma i-PSM iyindlela ephumelela kakhulu yokubikezela noma yokwenza imephu ukusatshalaliswa kwendawo kwama-PTE, izinhlobo zenhlabathi kanye nezakhiwo zomhlabathi.I-Geostatistics kanye ne-Machine Learning Algorithms (MLA) izindlela zokumodela ze-DSM ezidala amamephu edijithali ngosizo lwamakhompyutha asebenzisa idatha ebalulekile nencane.
I-Deuts18 ne-Olea19 zichaza i-geostatistics ngokuthi "iqoqo lamasu ezinombolo abhekana nokumelwa kwezimfanelo zendawo, ikakhulukazi zisebenzisa amamodeli we-stochastic, njengokuthi ukuhlaziywa kochungechunge lwesikhathi kuyichaza kanjani idatha yesikhashana." Ngokuyinhloko, i-geostatistics ihilela ukuhlolwa kwama-variograms, okuvumela Ukulinganisa nokuchaza ukuncika kwamanani wendawo kusuka kudathasethi ngayinye20.Gumiaux et al. 20 iphinde ibonise ukuthi ukuhlolwa kwama-variograms ku-geostatistics kusekelwe ezimisweni ezintathu, okuhlanganisa (a) ukwenza ikhompuyutha isikali sokuhlobana kwedatha, (b) ukuhlonza nokwenza ikhompuyutha i-anisotropy ngokungafani kwedathasethi kanye (c) ngaphezu kokuthi Ngaphezu kokucabangela iphutha elingokwemvelo ledatha yokulinganisa ehlukanisiwe emiphumeleni yokulinganisa yendawo nayo iyimiphumela eminingi yokuhlanganisa. asetshenziswa kuma-geostatistics, okuhlanganisa i-kriging evamile, i-co-kriging, i-kriging evamile, i-empirical Bayesian kriging, indlela ye-kriging elula namanye amasu aziwa kakhulu wokuhumusha ukuze enze imephu noma ukubikezela i-PTE, izici zomhlabathi, nezinhlobo zenhlabathi.
I-Machine Learning Algorithms (MLA) iyindlela entsha uma kuqhathaniswa esebenzisa amakilasi edatha amakhulu angawolayini, akhuthazwa ama-algorithms ngokuyinhloko asetshenziselwa ukumbiwa kwedatha, ukuhlonza amaphethini kudatha, futhi asetshenziswa ngokuphindaphindiwe ekuhlukaniseni emikhakheni yesayensi efana nesayensi yenhlabathi nemisebenzi yokubuyisela. Amaphepha amaningi ocwaningo ancike kumamodeli we-MLA ukuze abikezele i-PTE emhlabathini, njenge-Tan et al. 22 (amahlathi angahleliwe okulinganisa kwensimbi esindayo emhlabathini wezolimo), Sakizadeh et al. 23 (ukumodela kusetshenziswa imishini ye-vector yokusekela kanye namanethiwekhi e-neural okwenziwa) ukungcoliswa komhlabathi).Ngaphezu kwalokho, i-Vega et al. 24 (INQALI yokulinganisa ukugcinwa kwensimbi esindayo kanye ne-adsorption enhlabathini) Sun et al. 25 (ukusetshenziswa kwe-cubist ukusatshalaliswa kwe-Cd enhlabathini) namanye ama-algorithms afana nomakhelwane oseduze kuka-k, ukuhlehla okuthuthukile okujwayelekile, kanye nokuhlehla okuthuthukisiwe Izihlahla nazo zasebenzisa i-MLA ukubikezela i-PTE enhlabathini.
Ukusetshenziswa kwama-algorithms e-DSM ekubikezeleni noma ekudwebeni kubhekana nezinselele ezimbalwa.Ababhali abaningi bakholelwa ukuthi i-MLA iphakeme kune-geostatistics futhi ngokuphambene nalokho.Nakuba eyodwa ingcono kunomunye, ukuhlanganiswa kwakho kokubili kuthuthukisa izinga lokunemba kwemephu noma ukubikezela ku-DSM15.I-Woodcock ne-Gopal26 Finke27; U-Pontius no-Cheuk28 kanye no-Grunwald29 baphawula ngokushiyeka kanye namaphutha athile kumephu yomhlabathi ebikezelwe.Ososayensi bomhlabathi bazamile amasu anhlobonhlobo ukuze bathuthukise ukusebenza kahle, ukunemba, kanye nokubikezela kwemephu ye-DSM kanye nokubikezela.Inhlanganisela yokungaqiniseki nokuqinisekisa ingenye yezici eziningi ezihlukene ezididiyelwe ku-DSM ukuze kuncishiswe ukusebenza kahle. 15 iveza ukuthi ukuziphatha kokuqinisekisa nokungaqiniseki okwethulwa ngokudalwa kwemephu nokubikezela kufanele kuqinisekiswe ngokuzimele ukuze kuthuthukiswe ikhwalithi yemephu.Imikhawulo ye-DSM ibangelwa ikhwalithi yenhlabathi ehlakazekile ngokwendawo, ebandakanya ingxenye yokungaqiniseki; kodwa-ke, ukuntuleka kwesiqiniseko ku-DSM kungase kuvele emithonjeni eminingi yephutha, okuyiphutha le-covariate, iphutha lemodeli, iphutha lendawo, kanye nephutha lokuhlaziya 31.Ukungalungi kwe-Modelling okufakwe ku-MLA kanye nezinqubo ze-geostatistical kuhlotshaniswa nokuntula ukuqonda, ekugcineni okuholela ekweqinisweni kwenqubo yangempela32.Kungakhathaliseki ukuthi imodeli ingaba i-attributed model, imodeli engafaneleki izibikezelo zemodeli yezibalo, noma ukufakwa33.Muva nje, kuvele umkhuba omusha we-DSM okhuthaza ukuhlanganiswa kwe-geostatistics kanye ne-MLA ekudwebeni imephu nokubikezela.Ososayensi abaningi benhlabathi nababhali, njengoSergeev et al. 34; I-Subbotina et al. 35; Tarasov et al. 36 kanye noTarasov et al. Abangu-37 basebenzise ikhwalithi enembile ye-geostatistics nokufunda komshini ukuze bakhiqize amamodeli ayingxube athuthukisa ukusebenza kahle kokubikezela nokubhala imephu. ikhwalithi.Amanye alawa mamodeli ayi-hybrid noma ahlanganisiwe we-algorithm i-Artificial Neural Network Kriging (ANN-RK), i-Multilayer Perceptron Residual Kriging (MLP-RK), Generalized Regression Neural Network Residual Kriging (GR- NNRK)36, Artificial Neural Network Kriging-Multilayer Perceptron-Multilayer Perceptron (ANKsi-3K) kanye ne-ANNriging Perceptron (ANKsi-3K) Ukwehla38.
Ngokuka-Sergeev et al., ukuhlanganisa amasu okumodela ahlukahlukene kunamandla okuqeda amaphutha futhi kwandise ukusebenza kahle kwemodeli eyingxube ewumphumela kunokuba kuthuthukiswe imodeli yayo eyodwa.Kulo mongo, leli phepha elisha liphikisa ngokuthi kuyadingeka ukusebenzisa i-algorithm ehlanganisiwe ye-geostatistics kanye ne-MLA ukuze kudalwe amamodeli ayi-hybrid alungile ukuze abikezele ukucebisa kwe-Ni ezindaweni zasemadolobheni nasezindaweni zasemakhaya. (EBK) njengemodeli eyisisekelo bese uyixuba namamodeli Womshini Wokusekela Vector (SVM) kanye Nawe-Multiple Linear Regression (MLR).I-Hybridization ye-EBK nanoma iyiphi i-MLA akwaziwa.Amamodeli axubile amaningi abonwayo ayinhlanganisela ye-regression kriging evamile, eyinsalela, kanye ne-MLA.EBK iyindlela yokuhlanganisa ye-geostatistical esebenzisa i-spastic process yendawo nge-spa. insimu engamile/emile enemingcele echaziwe yendawo endaweni, evumela ukuhlukahluka kwendawo39.EBK isetshenziswe ezifundweni ezihlukahlukene, okuhlanganisa nokuhlaziya ukusatshalaliswa kwekhabhoni yemvelo enhlabathini yasemapulazini40, ukuhlola ukungcoliswa komhlaba41 kanye nokudwetshwa kwezakhiwo zomhlabathi42.
Ngakolunye uhlangothi, i-Self-Organising Graph (i-SeOM) i-algorithm yokufunda esetshenziswe ezihlokweni ezihlukahlukene ezifana ne-Li et al. 43, Wang et al. 44, uHossain Bhuiyan et al. 45 kanye no-Kebonye et al.46 Thola izimfanelo zendawo kanye nokuqoqwa kwezinto.Wang et al. 44 iveza ukuthi i-SeOM iyindlela yokufunda enamandla eyaziwa ngekhono layo lokuqoqa nokucabanga izinkinga ezingahlangene nomugqa.Ngokungafani nezinye izindlela zokuqaphela iphethini ezifana nokuhlaziywa kwengxenye eyinhloko, ukuhlanganisa okungaqondakali, ukuhlanganisa okulandelanayo, kanye nokwenza izinqumo ngemibandela eminingi, i-SeOM ingcono ekuhleleni nasekuboneni amaphethini e-PTE.Ngokuvumelana ne-War. I-44, i-SeOM ingakwazi ukuqoqa ngokwendawo ukusatshalaliswa kwama-neurons ahlobene futhi inikeze ukubonwa kwedatha yokulungiswa okuphezulu.I-SeOM izobuka ngeso lengqondo idatha yokubikezela ye-Ni ukuze ithole imodeli engcono kakhulu yokubonisa imiphumela yokuchazwa okuqondile.
Leli phepha lihlose ukukhiqiza imodeli yemephu eqinile enembayo ephelele yokubikezela okuqukethwe kwe-nickel ezindaweni ezisemadolobheni kanye naseduze kwedolobha. Sicabanga ukuthi ukwethembeka kwemodeli exubile kuncike kakhulu ethonyeni lamanye amamodeli axhumene nemodeli yesisekelo. ngakho-ke, sizozama ukuphendula imibuzo yocwaningo engase iveze amamodeli axubile.Nokho, inembe kangakanani imodeli ekubikezeleni isici esiqondiwe?Futhi, liyini izinga lokuhlola ukusebenza kahle okusekelwe ekuqinisekiseni nasekuhloleni ukunemba?Ngakho-ke, imigomo ethile yalolu cwaningo kwakuwu (a) ukudala imodeli ehlanganisiwe ye-SVMR noma i-MLR usebenzisa i-EBK (isibonelo) ukuqhathanisa imodeli yesisekelo esingcono kakhulu Ukugxiliswa kuka-Ni enhlabathini yasemadolobheni noma eseduze nedolobha , kanye (d) nokusetshenziswa kwe-SeOM ukudala imephu enokulungiswa okuphezulu kokuhlukahluka kwendawo ye-nickel.
Ucwaningo lwenziwa e-Czech Republic, ikakhulukazi esifundeni sase-Frydek Mistek esifundeni sase-Moravia-Silesian (bheka Umfanekiso 1).Indawo yocwaningo inzima kakhulu futhi iyingxenye enkulu yesifunda sase-Moravia-Silesian Beskidy, esiyingxenye yonqenqema olungaphandle lwezintaba ze-Carpathian.Indawo yocwaningo iphakathi kuka-N1′19° no-2 ′19° 0′ E, futhi ukuphakama kuphakathi kuka-225 no-327 m; Nokho, uhlelo lwe-Koppen lokuhlukanisa isimo sezulu sesifunda lulinganiselwe njenge-Cfb = isimo sezulu esishisayo solwandle, Kukhona imvula eningi ngisho nasezinyangeni ezomile.Amazinga okushisa ayahluka kancane unyaka wonke phakathi -5 °C no-24 °C, akuvamile ukuba abe ngaphansi -14 °C noma ngaphezulu kuka-30 °C ngonyaka kanye ne-5 ° C kanye nemvula engu-58 mm47. Indawo yokuhlola elinganiselwe yendawo yonke ingamakhilomitha-skwele angu-1,208, kanye no-39.38% womhlaba olinywayo kanye no-49.36% wehlathi eligcwele yonke indawo. Ngakolunye uhlangothi, indawo esetshenziswe kulolu cwaningo ingamakhilomitha-skwele angu-889.8. (isib. ukumelana nokugqwala komkhathi) nezinsimbi ze-alloy (i-nickel ikhulisa amandla engxubevange kuyilapho igcina i-ductility yayo enhle nokuqina), kanye nokulima okujulile njengokufakwa kukamanyolo we-phosphate nokukhiqizwa kwemfuyo kuyimithombo engaba khona ye-nickel yocwaningo esifundeni (isb., ukwengeza i-nickel kumawundlu ukuze kwandiswe izinga lokukhula kwamawundlu amawundlu kanye nokusetshenziswa ezindaweni eziphansi ze-nickel). i-electroplating, kuhlanganise ne-electroplating nickel kanye ne-electroless nickel plating procedures.Izakhiwo zomhlabathi zihlukaniseka kalula kusukela kumbala wenhlabathi, ukwakheka, kanye nokuqukethwe kwe-carbonate.Ukuthungwa kwenhlabathi kuphakathi nendawo ukuya kokucolekile, kususelwa ezintweni eziwumzali.Ziyi-colluvial, alluvial noma i-aeolian ngokwemvelo.Ezinye izindawo zenhlabathi zibonakala zinamabala angaphezulu kanye nomhlabathi ongaphansi, ngokuvamile zinezinhlobo ezivame ukukhonkolo neziqinile. isifunda48.Ngokuphakama okusuka ku-455.1 kuya ku-493.5 m, ama-cambisol abusa i-Czech Republic49.
Imephu yendawo yokufunda [Imephu yendawo yocwaningo yakhiwe kusetshenziswa i-ArcGIS Desktop (ESRI, Inc, inguqulo 10.7, URL: https://desktop.arcgis.com).]
Kutholwe amasampula enhlabathi engaphezulu ayi-115 enhlabathini yasemadolobheni kanye nangaseceleni kwedolobha esifundeni saseFrydek Mistek. Iphethini yesampula esetshenzisiwe kwakuyigridi evamile enamasampula omhlabathi aqhelelene ngamakhilomitha angu-2 × 2, futhi inhlabathi yangaphezulu yayikalwa ngokujula kuka-0 kuya ku-20 cm kusetshenziswa idivayisi ye-GPS ephathwa ngesandla (Leica Zeno 5 bag, iSampuli efakwe i-GPS ifakwe kahle, iSampula ifakwe i-GPS). elabhorethri.Amasampula omisiwe emoyeni ukuze akhiqize amasampula agayiwe, ahlanjululwe ngomshini (Fritsch disc mill), futhi ahlungwa (usayizi wesisefo 2 mm).Faka igremu elingu-1 lamasampula omhlabathi omisiwe, afakwe i-homogenized futhi ahlungiwe emabhodleleni e-teflon abhalwe ngokucacile. Emkhunjini ngamunye we-Teflon, khipha u-3% we-HC we-5% we-HC, ukhiphe u-3% we-HC we-5% we-HC. I-HNO3 (usebenzisa i-automatic dispenser - eyodwa ku-asidi ngayinye), vala kancane futhi uvumele amasampuli ukuthi ame ubusuku bonke ukuze aphendule (uhlelo lwe-aqua regia) .Beka i-supernatant epuleti lensimbi elishisayo (izinga lokushisa: 100 W kanye no-160 °C) amahora angu-2 ukuze kube lula inqubo yokugaya yamasampuli, bese upholisa ivolumu engu-50 ukuze udlulise ivolumu engu-50 ye-flash. ml ngamanzi angcolile.Ngemva kwalokho, hlunga i-supernatant ehlanjululwe ibe yithubhu ye-PVC engu-50 ml ngamanzi angcolile.Ukwengeza, i-1 ml yesisombululo sokuhlanjululwa ihlanjululwe nge-9 ml yamanzi ahlanjululwe futhi ihlungwe ku-12 ml tube elungiselelwe i-PTE pseudo-concentration.I-concentrations ye-PTEs, i-Cynr, i-Cdb, i-Cud, i-Cud, i-PTEs, i-Cdb, i-Cud I-Mg, K) inqunywe yi-ICP-OES (Inductively Coupled Plasma Optical Emission Spectroscopy) (Thermo Fisher Scientific, USA) ngokwezindlela ezijwayelekile kanye nesivumelwano.Qinisekisa Ukuqinisekiswa Kwekhwalithi Nokulawula (QA/QC) izinqubo (SRM NIST 2711a Montana II Soil) .PTEs ekhishiwe kulo mkhawulo wocwaningo wokutholwa. bekungu-0.0004.(wena).Ngaphezu kwalokho, ukulawulwa kwekhwalithi kanye nenqubo yokuqinisekisa ikhwalithi yokuhlaziywa ngakunye kuqinisekiswa ngokuhlaziya izindinganiso zereferensi.Ukuqinisekisa ukuthi amaphutha aye ancishiswa, ukuhlaziya kabili kwenziwa.
I-Empirical Bayesian Kriging (EBK) ingenye yezindlela eziningi zokuhlanganisa i-geostatistical interpolation ezisetshenziswa ekumodeleni emikhakheni eyahlukene njengesayensi yenhlabathi.Ngokungafani nezinye izindlela zokuhumusha i-kriging, i-EBK ihlukile ezindleleni zendabuko ze-kriging ngokucabangela iphutha elilinganiselwe imodeli ye-semivariogram. I-semivariogram.Izindlela zokuhumusha zenza indlela yokungaqiniseki nohlelo oluhlobene nalokhu kuhlelwa kwe-semivariogram eyenza ingxenye eyinkimbinkimbi kakhulu yendlela eyanele ye-kriging.Inqubo yokuhumusha ye-EBK ilandela imibandela emithathu ehlongozwe u-Krivoruchko50, (a) imodeli ilinganisela i-semivariogram ye-semivariogram yevelu eqageliwe yendawo ngayinye esekelwe kudathasethi entsha yedathasethi ngayinye ebikezelwe. i-semivariogram kanye (c) nemodeli yokugcina engu-A ibalwa kudathasethi elingisiwe.Umthetho wezibalo wase-Bayesia unikezwa njengengemuva
Lapho \(Prob\left(A\right)\) imele okwangaphambili, \(Prob\left(B\right)\) amathuba asemaceleni ashaywa indiva ezikhathini eziningi, \(Prob (B,A)\ ) .Isibalo se-semivariogram sisekelwe emthethweni we-Bayes, obonisa ukuthambekela kokubuka idathasethi ye-semiovari engase idalwe kusukela ku-semivariogram. Umthetho ka-Bayes, othi mangakanani amathuba okudala isethi yedatha yokubuka kusuka ku-semivariogram.
Umshini wokusekelayo uyi-algorithm yokufunda yomshini ekhiqiza i-hyperplane ehlukanisayo efanele ukuze ihlukanise amakilasi afanayo kodwa angazimele ngokulandelana.I-Vapnik51 idale i-algorithm yokuhlukanisa inhloso, kodwa isanda kusetshenziswa ukuxazulula izinkinga ezigxile ekuhlehleni. Ngokuka-Li et al.52, i-SVM ingenye yezindlela ezingcono kakhulu zokuhlukanisa isigaba futhi isetshenziswe i-SVMupport eyodwa. I-Vector Machine Regression – SVMR) isetshenziswe kulokhu kuhlaziya.UCherkassky kanye no-Mulier53 baphayona i-SVMR njengokuhlehla okusekelwe ku-kernel, ukubala kwakho okwenziwe kusetshenziswa imodeli yokuhlehla yomugqa enemisebenzi yezindawo zamazwe amaningi.U-John et al54 babika ukuthi ukumodela kwe-SVMR kusebenzisa imisebenzi ye-hyperplane yomugqa kanye nokuhlehla kwe-spatircco. kuVohland et al. 55, i-epsilon (ε)-SVMR isebenzisa idathasethi eqeqeshiwe ukuze ithole imodeli yokumelela njengomsebenzi ongazweli we-epsilon osetshenziswa ukwenza imephu idatha ngokuzimela ngokukhetha okungcono kakhulu kwe-epsilon kusukela ekuqeqesheni idatha ehlotshaniswayo.Iphutha lebanga elisethiwe alinakwa kusukela enanini langempela, futhi uma iphutha likhulu kuno-ε(ε), idatha yokuqeqeshwa ibuye inciphise imodeli ebanzi yokuqeqeshwa kwedatha. subset of support vectors.I-equation ephakanyiswe yi-Vapnik51 iboniswe ngezansi.
lapho u-b emele umkhawulo wesikala, \(K\left({x}_{,}{ x}_{k}\right)\) imele umsebenzi we-kernel, \(\alpha\) imele isiphindaphindi se-Lagrange, N Imele idathasethi yezinombolo, \({x}_{k}\) imele okokufaka kwedatha, futhi \.i-Onnethi esetshenziswayo ye-SV, ikhiyishini esetshenziswayo \(y\) ewukhiye wedatha iwumsebenzi wesisekelo se-Gaussian radial basis (RBF).I-RBF kernel isetshenziswa ukuze kutholwe imodeli ye-SVMR elungile, ebalulekile ukuze kutholwe inhlawulo ecashile kakhulu yesethi isici C kanye ne-kernel parameter gamma (γ) yedatha yokuqeqeshwa ye-PTE. Okokuqala, sihlole isethi yokuqeqesha sabe sesihlola ukusebenza kwemodeli kusethi yokuqinisekisa esetshenzisiwe.Indlela yokuqondisa i-sidigm ipharamitha ye-sidigsm.
Imodeli yokuhlehla kwemigqa eminingi (MLR) imodeli yokuhlehla emelela ubuhlobo phakathi kokuguquguquka kwempendulo kanye nenani lokuguquguquka kokubikezela ngokusebenzisa amapharamitha ahlanganiswe ngomugqa abalwe kusetshenziswa indlela yesikwele esincane.Ku-MLR, imodeli yesikwele esincane iwumsebenzi wokubikezela wezakhiwo zenhlabathi ngemva kokukhethwa kweziguquguquko ezichazayo.Kudingeka ukusebenzisa impendulo ukuze umise ukuguquguquka okusetshenzisiwe njengomugqa wokuchazayo kwakuwukuchaza okuguquguqukayo kusetshenziswa umugqa wokuchaza.P neziguquguqukayo ezichazayo.Isibalo se-MLR sithi
lapho u-y ewukushintshashintsha kwempendulo, \(a\) i-intercept, n iyinani lezibikezelo, \({b}_{1}\) ukuhlehla okuyingxenye kwama-coefficients, \({x}_{ i}\) imele isibikezelo noma i-variable echazayo, futhi \({\varepsilon }_{i}\) imele iphutha eliphindwe kabili, eyaziwa ngokuthi imodeli.
Amamodeli axutshiwe atholwe ngokuhlanganisa i-EBK nge-SVMR ne-MLR. Lokhu kwenziwa ngokukhipha amanani abikezelwe kusukela ekuhumusheni kwe-EBK. Amanani abikezelwe atholwe ku-Ca, K, ne-Mg ehlanganisiwe atholakala ngenqubo yokuhlanganisa ukuze kutholwe okuguquguqukayo okusha, okufana ne-CaK, i-CaMg, ne-KMg, i-KMg ne-KMg bese ithola izakhi zesine, bese i-Mg Ca ithola izici zesine. I-CaKMg.Sekukonke, okuguquguqukayo okutholiwe i-Ca, K, Mg, CaK, CaMg, KMg kanye ne-CaKMg.Lokhu okuguquguqukayo kwaba izibikezelo zethu, okusiza ukubikezela ukugxiliswa kwe-nickel enhlabathini yasemadolobheni kanye naseduze kwedolobha.I-algorithm ye-SVMR yenziwa kuzibikezelo ukuze kutholwe imodeli exubile ye-Empirical Bayesian Kriging-Supports Machines_Supports EBmilar). ngokusebenzisa i-algorithm ye-MLR ukuze kutholwe imodeli exubile ye-Empirical Bayesian Kriging-Multiple Linear Regression (EBK_MLR). Ngokuvamile, okuguquguqukayo okuthi Ca, K, Mg, CaK, CaMg, KMg, kanye ne-CaKMg kusetshenziswa njengama-covariate njengezibikezelo zokuqukethwe kwe-Ni endaweni yasemadolobheni naseduze kwedolobha etholakalayo. usebenzisa igrafu ezihlelayo.Ukuhamba komsebenzi kwalolu cwaningo kuboniswe kuMfanekiso 2.
Ukusebenzisa i-SeOM sekuphenduke ithuluzi elidumile lokuhlela, lokuhlola, kanye nokubikezela idatha emkhakheni wezezimali, ukunakekelwa kwezempilo, imboni, izibalo, isayensi yomhlabathi, nokunye.I-SeOM idalwe kusetshenziswa amanethiwekhi okwenziwa e-neural nezindlela zokufunda ezingagadiwe zokuhlela, ukuhlola, nokubikezela.Kulolu cwaningo, i-SeOM yasetshenziselwa ukubona ngeso lengqondo ukugxilwa kwe-Ni ngokususelwa kunqubo ye-Niu ebikezelwe yedatha yedolobha. ekuhlolweni kwe-SeOM kusetshenziswa njengokuguquguquka kwe-vector ye-input-dimensional43,56.Melssen et al. 57 chaza ukuxhunywa kwe-vector yokufaka kunethiwekhi ye-neural ngokusebenzisa isendlalelo esisodwa sokufaka ku-vector ephumayo ene-vector eyodwa enesisindo.Okukhiphayo okukhiqizwa yi-SeOM imephu enezinhlangothi ezimbili ehlanganisa ama-neurons ahlukene noma ama-node alukwe abe amamephu we-hexagonal, ayindilinga, noma ayisikwele we-topological ngokuya ngokusondela kwawo.Ukuqhathanisa osayizi bemephu ngokusekelwe ku-mepographic, imodeli ye-OME) nge-0.086 kanye ne-0.904, ngokulandelanayo, ikhethiwe, okuyiyunithi yemephu engu-55 (5 × 11).Isakhiwo se-neuron sinqunywa ngokwenani lamanodi ku-equation ye-empirical.
Inani ledatha elisetshenziswe kulolu cwaningo amasampula angu-115. Indlela engahleliwe yasetshenziswa ukuze kuhlukaniswe idatha ibe idatha yokuhlola (25% ukuze iqinisekiswe) namasethi edatha yokuqeqesha (75% ukuze kulinganiswe).Idathasethi yokuqeqeshwa isetshenziselwa ukukhiqiza imodeli yokuhlehla (ukulinganisa), futhi idathasethi yokuhlola isetshenziselwa ukuqinisekisa ikhono lokwenza okuvamile58.Lokhu kwenziwa ukuze kuhlolwe ukufaneleka kwawo wonke amamodeli asetshenzisiwe okusebenza komhlabathi. inqubo yokuqinisekisa okuphambanayo ephindwe kashumi, ephindaphindwa kahlanu.Iziguquko ezikhiqizwe i-EBK interpolation zisetshenziswa njengezibikezelo noma iziguquguquko ezichazayo ukuze kubikezelwe ukuguquguquka okuqondiwe (PTE).Ukumodela kusingathwa ku-RStudio kusetshenziswa ilabhulali yamaphakheji(Kohonen), umtapo wezincwadi (caret), umtapo (modelr), umtapo wolwazi("e1071″), umtapo wezincwadi("plyr") umtapo wezincwadi), umtapo wezincwadi("plyr") (“Amamethrikhi”).
Kusetshenziswe imingcele yokuqinisekisa ehlukahlukene ukuze kutholwe imodeli engcono kakhulu efanelekile ukubikezela ukugxila kwe-nickel emhlabathini kanye nokuhlola ukunemba kwemodeli nokuqinisekiswa kwayo.Amamodeli we-Hybridization ahlolwe kusetshenziswa iphutha eliphelele eliphelele (MAE), iphutha le-root mean square (RMSE), kanye ne-R-squared noma i-coefficient yokunqunywa (R2) . imodeli.RMSE kanye nobukhulu bokuhluka ezilinganisweni ezizimele zichaza amandla okubikezela emodeli, kuyilapho i-MAE inquma inani langempela lomthamo.Inani le-R2 kufanele libe phezulu ukuze kuhlolwe imodeli yengxube engcono kakhulu kusetshenziswa imingcele yokuqinisekisa, inani eliseduze lifika ku-1, liphezulu ukunemba.Ngokusho kwe-Li et al. 59, inani lokunquma elingu-R2 elingu-0.75 noma ngaphezulu libhekwa njengesibikezeli esihle; ukusuka ku-0.5 ukuya ku-0.75 kuwukusebenza kwemodeli okwamukelekayo, futhi ngaphansi kuka-0.5 ukusebenza kwemodeli okungamukelekile.Lapho ukhetha imodeli kusetshenziswa izindlela zokuhlola imibandela yokuqinisekisa ye-RMSE kanye ne-MAE, amanani aphansi atholiwe ayenele futhi athathwa njengokukhetha okungcono kakhulu.Isibalo esilandelayo sichaza indlela yokuqinisekisa.
lapho u-n emelela usayizi yenani eliboniwe\({Y}_{i}\) limelela impendulo elinganisiwe, futhi \({\widehat{Y}}_{i}\) imelela inani lokuphendula elibikezelwe, ngakho-ke, ekubonweni kokuqala kuka-i.
Izincazelo zezibalo zokuhlukahluka kwezibikezelo nezimpendulo zethulwe kuThebula 1, okubonisa incazelo, ukuchezuka okujwayelekile (SD), i-coefficient of variation (CV), ubuncane, ubukhulu, i-kurtosis, kanye nokutsheka.Amanani aphansi nomkhawulo wezinto ahlelwe ngendlela enciphayo ye-Mg < Ca < K < Ni kanye ne- Ca < Mg < K < Ni, ngokulandelanayo. Impendulo esuka endaweni yocwaningo ehlukanisiwe ukusuka ku-Nix endaweni yocwaningo) ngokulandelana. 4.86 kuya ku-42.39 mg/kg.Ukuqhathaniswa kwe-Ni nesilinganiso somhlaba (29 mg/kg) kanye nesilinganiso saseYurophu (37 mg/kg) sibonise ukuthi incazelo yejiyomethri ebaliwe iyonke yendawo yocwaningo yayingaphakathi kwebanga elibekezeleleka.Nonatheless, njengoba kuboniswa i-Kabata-Pendias11, ukuqhathaniswa kwesilinganiso esimaphakathi se-nickel kucwaningo lwe-Nick yamanje kukhombisa ukugxilisa kwe-nickel enhlabathini ye-nick yamanje ngaphezulu.Ngokunjalo, ingqikithi yenhlabathi ye-Frydek Mistek enhlabathini yasemadolobheni kanye naseduze kwedolobha ocwaningweni lwamanje (Ni 16.15 mg/kg) ibiphezulu kunomkhawulo ovumelekile wama-60 (10.2 mg/kg) we-Ni enhlabathini yasemadolobheni yase-Polish ebikwe ngu-Różański et al.Ngaphezu kwalokho, i-Ni 16.15 mg/kg isho ukuthi i-Calderisitzel engu-7 mg irekhodi eliphansi kakhulu enhlabathini yasemadolobheni e-Tuscany uma kuqhathaniswa nocwaningo lwamanje.UJim62 uphinde wathola ukuhlushwa kwe-nickel ephansi (12.34 mg/kg) enhlabathini yasemadolobheni e-Hong Kong, ephansi kunokugxilwa kwe-nickel yamanje kulolu cwaningo.U-Birke et al63 ubike isilinganiso se-Nickel esimaphakathi esingu-17.6 mg/kg endaweni endala yezimayini nasezimbonini zasemadolobheni e-Saxony 145-A endaweni (16.15 mg/kg).Ucwaningo lwamanje.Okuqukethwe kwe-nickel ngokweqile enhlabathini kwezinye izindawo zasemadolobheni nasezindaweni ezingaphansi kwedolobha yendawo yocwaningo kungase kubangelwe ikakhulukazi imboni yensimbi nensimbi kanye nemboni yensimbi.Lokhu kuhambisana nocwaningo olwenziwa nguKhodadust et al. 64 ukuthi imboni yensimbi nokusebenza kwensimbi kuyimithombo eyinhloko yokungcoliswa kwe-nickel enhlabathini.Nokho, izibikezelo nazo zazisukela ku-538.70 mg/kg kuya ku-69,161.80 mg/kg ku-Ca, 497.51 mg/kg kuya ku-3535.68 mg/kg ku-K, kanye no-6kg/5 mg/5 Mg.Jakovljevic et al. Abangu-65 baphenye ingqikithi ye-Mg ne-K yenhlabathi emaphakathi ne-Serbia.Bathole ukuthi ukugxilwa okuphelele (410 mg/kg kanye no-400 mg/kg, ngokulandelana) kwakungaphansi kokugxilisa kwe-Mg no-K ocwaningweni lwamanje.Akubonakali, empumalanga ye-Poland, i-Orzechowski ne-Smolczynski66 ibonise, i-avareji ye-M1 yokuqukethwe kwe-Cas kanye ne-Cass 0 K. mg/kg), Mg (590 mg/kg) kanye no-K (810 mg/kg) Okuqukethwe enhlabathini engaphezulu kuphansi kunento eyodwa kulolu cwaningo.Ucwaningo lwakamuva olwenziwa ngu-Pongrac et al. I-67 ibonise ukuthi ingqikithi ye-Ca ehlaziywe enhlabathini engu-3 ehlukene e-Scotland, UK (inhlabathi yaseMylnefield, inhlabathi yaseBalruddery kanye nomhlabathi waseHartwood) ibonise okuqukethwe kwe-Ca okuphezulu kulolu cwaningo.
Ngenxa yokugxilisa okulinganiselwe okulinganiselwe kwama-elementi ayisampula, ukusatshalaliswa kwesethi yedatha yezinto kubonisa ukutsheka okuhlukile.Ukutsheka nokurtosis kwezinto kusukela ku-1.53 ​​kuye ku-7.24 kanye no-2.49 kuya ku-54.16, ngokulandelana.Zonke izici ezibaliwe zinamaleveli okugwedla kanye ne-kurtosis ngaphezu kuka-+1, okubonisa ukuthi ukusabalalisa kwedatha okulungile kubonisa ukuthi isiqondiso sedatha inani eliphakeme.Ama-CV alinganiselwe wezakhi aphinde abonise ukuthi i-K, Mg, kanye ne-Ni ibonisa ukuhlukahluka okumaphakathi, kuyilapho i-Ca inokuhlukahluka okuphezulu kakhulu.Ama-CV ka-K, Ni kanye ne-Mg achaza ukusatshalaliswa kwawo okufanayo.Ngaphezu kwalokho, ukusatshalaliswa kwe-Ca akufani futhi imithombo yangaphandle ingase ithinte izinga layo lokunothisa.
Ukuhlotshaniswa kwezinto eziguquguqukayo zokubikezela nezinto zokuphendula kubonise ukuhlobana okwanelisayo phakathi kwezakhi (bheka Umfanekiso 3) .Ukuhlobana kubonise ukuthi i-CaK ibonise ukuhlobana okusesilinganisweni nenani le-r = 0.53, njengoba kwenza i-CaNi. Nakuba u-Ca no-K bebonisa ukuhlangana okuthobekile komunye nomunye, abacwaningi abafana no-Kingston et al. 68 kanye ne-Santo69 basikisela ukuthi amazinga abo enhlabathini ahambisana ngokuphambene.Nokho, i-Ca ne-Mg iphikisana no-K, kodwa i-CaK ihlobana kahle.Lokhu kungase kube ngenxa yokusetshenziswa komanyolo onjenge-potassium carbonate, ephakeme ngo-56% ku-potassium.I-Potassium yayihlotshaniswa ngokusesilinganisweni ne-magnesium (KM 63 eduze, i-potassium correlates yizici ezimbili ezihlobene). i-magnesium sulfate, i-potassium magnesium nitrate, ne-potash isetshenziswa enhlabathini ukuze kwandiswe amazinga okuntula. I-Nickel ihlotshaniswa ngokusesilinganisweni ne-Ca, K kanye ne-Mg ngamavelu angu-r = 0.52, 0.63 kanye no-0.55, ngokulandelana. kunciphisa imiphumela ye-magnesium eyeqile, futhi kokubili i-magnesium ne-calcium kunciphisa imiphumela enobuthi ye-nickel emhlabathini.
I-matrix yokuhlobana yezakhi ezibonisa ubudlelwano phakathi kwezibikezelo nezimpendulo (Qaphela: lesi sibalo sihlanganisa i-scatterplot phakathi kwama-elementi, amaleveli okubaluleka asekelwe ku-p <0,001).
Umfanekiso wesi-4 ubonisa ukusatshalaliswa kwendawo kwezinto.Ngokusho kukaBurgos et al70, ukusetshenziswa kokusatshalaliswa kwendawo kuyindlela esetshenziselwa ukulinganisa nokugqamisa izindawo ezishisayo ezindaweni ezingcolile.Amazinga okunothisa we-Ca kuFig. 4 angabonakala engxenyeni esenyakatho-ntshonalanga yemephu yokusatshalaliswa kwendawo.Isibalo sibonisa ukunothisa kwe-calcium okusesilinganisweni kwe-Capots ephezulu kakhulu ye-Cap. kungenzeka ngenxa yokusetshenziswa kwe-quicklime (i-calcium oxide) ukunciphisa ubumuncu bomhlaba kanye nokusetshenziswa kwayo ezigayweni zensimbi njengomoya-mpilo we-alkaline enqubweni yokwenza insimbi.Ngakolunye uhlangothi, abanye abalimi bakhetha ukusebenzisa i-calcium hydroxide enhlabathini ene-asidi ukwenza i-pH ingathathi hlangothi, ephinde yandise okuqukethwe kwe-calcium enhlabathini71.I-Potassium iphinde ibonise izindawo ezishisayo enyakatho-ntshonalanga naseNyakatho-ntshonalanga ye-potassium esezingeni eliphezulu umphakathi wezolimo. kungase kube ngenxa ye-NPK kanye nezicelo ze-potash.Lokhu kuhambisana nezinye izifundo, ezifana ne-Madaras ne-Lipavský72, i-Madaras et al.73, i-Pulkrabová et al.74, i-Asare et al.75, eyaqaphela ukuthi ukuqiniswa kwenhlabathi nokwelashwa nge-KCl ne-NPK kubangele okuqukethwe okuphezulu kwe-K emhlabathini. Ukucebisa kwe-Spatial Potassium enyakatho-ntshonalanga yemephu yokusabalalisa kungase kube ngenxa yokusetshenziswa komanyolo owenziwe nge-potassium njenge-potassium chloride, i-potassium sulfate, i-potassium nitrate, i-potash, ne-potash ukwandisa okuqukethwe kwe-potassium emhlabathini ompofu.Zádorová et al. 76 kanye noTlustoš et al. 77 iveze ukuthi ukusetshenziswa komanyolo osuselwe ku-K kwenyusa okuqukethwe kwe-K emhlabathini futhi kuzokwandisa kakhulu izakhi zomhlabathi ngokuhamba kwesikhathi, ikakhulukazi i-K ne-Mg ebonisa indawo eshisayo emhlabathini.Izindawo ezishisayo ezimaphakathi enyakatho-ntshonalanga yemephu naseningizimu-mpumalanga yemephu.Ukulungiswa kwe-colloidal enhlabathini kunciphisa ukugcwala kwe-magnesium emhlabathini ophuzi kubangela ukuntuleka kwezitshalo emhlabathini ophuzi. I-chlorosis.Umanyolo osekelwe ku-Magnesium, njenge-potassium magnesium sulfate, i-magnesium sulfate, ne-Kieserite, welapha ukushoda (izitshalo zibonakala zinsomi, zibomvu, noma zinsundu, okubonisa ukuntuleka kwe-magnesium) enhlabathini ene-pH evamile6. ukukhiqizwa78.
Ukusatshalaliswa kwendawo kwezinto [imephu yokusabalalisa yendawo idalwe kusetshenziswa i-ArcGIS Desktop (ESRI, Inc, Version 10.7, URL: https://desktop.arcgis.com).]
Imiphumela yenkomba yokusebenza yemodeli yezakhi ezisetshenziswe kulolu cwaningo iboniswa kuThebula 2. Ngakolunye uhlangothi, i-RMSE kanye ne-MAE ye-Ni zombili zisondele ku-zero (0.86 RMSE, -0.08 MAE). Ngakolunye uhlangothi, kokubili amanani e-RMSE kanye ne-MAE ka-K ayamukeleka.Imiphumela ye-RMSE ne-MAE ibe mikhulu nge-calcium ne-magnesium ehlukene yimiphumela ehlukene ye-MAE kanye nedatha ye-K. I-RMSE kanye ne-MAE yalolu cwaningo isebenzisa i-EBK ukubikezela i-Ni itholakale ingcono kunemiphumela kaJohn et al. 54 sisebenzisa i-synergistic kriging ukubikezela ukugxila kuka-S enhlabathini kusetshenziswa idatha efanayo eqoqiwe. Imiphumela ye-EBK esiyifundile ihlobana naleyo ka-Fabijaczyk et al. 41, Yan et al. 79, Beguin et al. 80, Adhikary et al. 81 kanye noJohane et al. 82, ikakhulukazi u-K no-Ni.
Ukusebenza kwezindlela ezingazodwana zokubikezela okuqukethwe kwe-nickel enhlabathini yasemadolobheni naseduze kwedolobha kwahlaziywa kusetshenziswa ukusebenza kwamamodeli (Ithebula 3).Ukuqinisekiswa kwemodeli nokuhlola ukunemba kuqinisekisile ukuthi isibikezelo se-Ca_Mg_K esihlanganiswe nemodeli ye-EBK SVMR sinikeze ukusebenza okungcono kakhulu.Imodeli ye-Calibration kanye ne-square model Ca_Mg_K-EBK2 imodeli ye-square ye-SVM_EBK-EBK Iphutha eliphelele (MAE) lalingu-0.637 (R2), 95.479 mg/kg (RMSE) kanye no-77.368 mg/kg (MAE) Ca_Mg_K-SVMR bekungu-0.663 (R2), 235.974 mg/kg (RMSE) kanye no-166.946 amavelu atholwe ngo-R2. I-Ca_Mg_K-SVMR (0.663 mg/kg R2) kanye ne-Ca_Mg-EBK_SVMR (0.643 = R2); imiphumela yabo ye-RMSE ne-MAE ibiphezulu kunaleyo ye-Ca_Mg_K-EBK_SVMR (R2 0.637) (bona Ithebula 3). Ngaphezu kwalokho, i-RMSE kanye ne-MAE ye-Ca_Mg-EBK_SVMR (RMSE = 1664.64 kanye ne-MAE = 1031.49) imodeli kanye ne-17.5 enkulu kunaleyo engu-17.5. I-Ca_Mg_K-EBK_SVMR. Ngokufanayo, imodeli ye-RMSE ne-MAE ye-Ca_Mg-K SVMR (RMSE = 235.974 ne-MAE = 166.946) imodeli ingu-2.5 no-2.2 mikhulu kunaleyo ye-Ca_Mg_K-EBK_SVMR ibonisa ukuthi idatha ihlelwe kanjani ngokuqhathanisa ne-MASE. inomugqa ofaneleka kakhulu.I-RSME ephezulu ne-MAE yabonwa.Ngokuka-Kebonye et al. 46 kanye noJohane et al. 54, uma i-RMSE ne-MAE isondela kuqanda, kuba ngcono imiphumela.I-SVMR kanye ne-EBK_SVMR banamanani aphezulu e-RSME kanye ne-MAE. Kwaqashelwa ukuthi izilinganiso ze-RSME zaziphezulu ngokuqhubekayo kunamanani e-MAE, okubonisa ukuba khona kwabangaphandle.Ngokusho kwe-Leates, i-McCabes isho ukuthi i-McCabe idlula u-8 izinga le-McCabe3 (I-MAE) iyatuswa njengenkomba yokuba khona kwabangaphandle.Lokhu kusho ukuthi uma idathasethi ihluka kakhulu, amanani e-MAE nawe-RMSE aphezulu.Ukunemba kokuhlolwa kokuqinisekisa okuphambene kwemodeli exubile ye-Ca_Mg_K-EBK_SVMR yokubikezela okuqukethwe kwe-Ni emhlabathini wasemadolobheni kanye ne-Suburban kwaba ngu-63.70% we-alcco. 59, leli zinga lokunemba liyimodeli yezinga lokusebenza elamukelekayo.Imiphumela yamanje iqhathaniswa nocwaningo lwangaphambili lukaTarasov et al. 36 imodeli yayo eyingxube idale i-MLPRK (Multilayer Perceptron Residual Kriging), ehlobene nenkomba yokuhlola ukunemba kwe-EBK_SVMR ebikwe ocwaningweni lwamanje, i-RMSE (210) kanye ne-The MAE (167.5) yayiphezulu kunemiphumela yethu ocwaningweni lwamanje (RMSE 95.479, MAE6 yamanje ye-R2,3 kanjani i-R2). (0.637) naleyo kaTarasov et al. 36 (0.544), kusobala ukuthi i-coefficient of determination (R2) iphezulu kule modeli exubile.Imajini yephutha (RMSE kanye ne-MAE) (EBK SVMR) yemodeli exubile iphansi ngokuphindwe kabili.Ngokufanayo, u-Sergeev et al.34 barekhode u-0.28 (R2) kumodeli ye-hybrid ethuthukisiwe (i-Multilarecord yocwaningo lwamanje) ngenkathi i-Record Recording yamanje 0.637 (R2).Izinga lokunemba lokubikezela lale modeli (EBK SVMR) lingu-63.7%, kuyilapho ukunemba kokubikezela okutholwe u-Sergeev et al. I-34 ingu-28%.Imephu yokugcina (Fig. 5) idalwe kusetshenziswa imodeli ye-EBK_SVMR kanye ne-Ca_Mg_K njengesibikezelo sezindawo ezishisayo kanye ne-nickel emaphakathi ukuya kweye-nickel kuyo yonke indawo yocwaningo.Lokhu kusho ukuthi ukugxiliswa kwe-nickel endaweni yocwaningo ngokuyinhloko kumaphakathi, nokugxila okuphezulu kwezinye izindawo ezithile.
Imephu yokuqagela yokugcina imelelwa kusetshenziswa imodeli ye-hybrid engu-EBK_SVMR futhi kusetshenziswa i-Ca_Mg_K njengesibikezelo.[Imephu yokusabalalisa yendawo idalwe kusetshenziswa i-RStudio (inguqulo 1.4.1717: https://www.rstudio.com/).]
Kwethulwa kuMfanekiso 6 ukugxiliswa kwe-PTE njengendiza yokuqamba ehlanganisa ama-neurons angawodwana.Ayikho indiza yengxenye ebonise iphethini yombala efanayo njengoba kukhonjisiwe.Nokho, inani elifanele lama-neurons kumephu edwetshiwe ngu-55.I-SeOM ikhiqizwa kusetshenziswa imibala eyahlukene, futhi uma amaphethini ombala afana kakhulu, kulapho kuqhathaniswa khona nakakhulu izici zamasampuli, izakhi zombala, i-KCang, kanye nezakhi zombala ezibonisa i-KCang ngayinye. amaphethini ombala afanayo kuma-neurons aphezulu kanye nama-neuron amaningi aphansi.Ngakho, i-CaK ne-CaMg babelana ngokufana okuthile nama-neurons e-oda eliphezulu kakhulu kanye namaphethini ombala ophansi ukuya komaphakathi.Womabili amamodeli abikezela ukugcwala kwe-Ni enhlabathini ngokubonisa imibala ephakathi nendawo ukuya phezulu yemibala efana nobomvu, osawolintshi kanye nophuzi.Imodeli ye-KMg ibonisa amaphethini amaningi ombala ophakeme asekelwe ekulinganisweni okunembile kombala ukuya esikalini esiphansi nokusabalalisa umbala wepulani eliphansi. iphethini yezingxenye zemodeli ibonise iphethini yombala ophezulu ebonisa ukuthi kungenzeka yini ukugxiliswa kwe-nickel enhlabathini (bona Umfanekiso 4). Imodeli yengxenye yendiza ye-CakMg ibonisa iphethini yombala ohlukahlukene ukusuka kophansi ukuya phezulu ngokwesilinganiso sombala esinembile. Ngaphezu kwalokho, ukubikezela kwemodeli kokuqukethwe kwe-nickel (i-CakMg) kufana nokusatshalaliswa kwendawo kwe-nickel ephakathi nendawo ekuboniseni i-nickel ephansi ekhonjisiwe ku-Proport5 ye-nickel. ukugxiliswa kwe-nickel enhlabathini yasemadolobheni naseduze kwedolobha.Umfanekiso 7 ubonisa indlela ye-contour ekuqoqweni kwezindlela ze-k kumephu, ihlukaniswe yaba amaqoqo amathathu ngokusekelwe enanini elibikezelwe kumodeli ngayinye.Indlela ye-contour imelela inani eliphelele lamaqoqo.Kumasampuli angu-115 aqoqiwe, isigaba 1 sathola amasampuli amaningi angu-4, amasampula enhlabathi angu-3luster athola amasampula amaningi angu-2. Abangu-3 bathole amasampula angu-8. Inhlanganisela yezingxenye eziyisikhombisa ze-planar predictor yenziwe lula ukuze kuvunyelwe ukutolikwa okulungile kweqoqo.Ngenxa yezinqubo eziningi ze-anthropogenic nezemvelo ezithinta ukwakheka kwenhlabathi, kunzima ukuba namaphethini eqoqo ahluke ngokufanele kumephu ye-SeOM esabalalisiwe78.
Okukhipha ingxenye yendiza ngokuhlukahluka ngakunye kwe-Empirical Bayesian Kriging Support Vector Machine (EBK_SVM_SeOM).[Amamephu we-SeOM adalwe kusetshenziswa i-RStudio (inguqulo 1.4.1717: https://www.rstudio.com/).]
Izingxenye ezihlukene zokuhlukanisa iqoqo [amamephu we-SeOM adalwe kusetshenziswa i-RStudio (inguqulo 1.4.1717: https://www.rstudio.com/).]
Ucwaningo lwamanje lubonisa ngokusobala amasu okumodela okugxilwa kwe-nickel enhlabathini yasemadolobheni naseduze kwedolobha. Ucwaningo luhlole amasu okumodela ahlukene, ahlanganisa izakhi nezindlela zokumodela, ukuze kutholwe indlela engcono kakhulu yokubikezela ukugxiliswa kwe-nickel enhlabathini.Izici ze-SeOM zokwakheka kwepulani yendawo yendlela yokumodela ibonise iphethini yombala ophezulu ukusuka kokuphansi ukuya phezulu esikalini sombala we-Nickel esinembile, imephu ye-spatidic esikalini sokusabalalisa umhlabathi. iqinisekisa ukusatshalaliswa kwendawo okuhleliwe kwezingxenye ezikhonjiswe yi-EBK_SVMR (bona Umfanekiso 5). Imiphumela ibonisa ukuthi imodeli yokuhlehlisa umshini we-vector (Ca Mg K-SVMR) ibikezela ukugxiliswa kwe-Ni enhlabathini njengemodeli eyodwa, kodwa imingcele yokuhlola yokuqinisekisa nokunemba ibonisa amaphutha aphezulu kakhulu ngokuya nge-RMSE imodeli ye-employe nesinye isandla se-employe. Imodeli ye-EBK_MLR nayo inephutha ngenxa yenani eliphansi le-coefficient of determination (R2). Imiphumela emihle itholwe kusetshenziswa i-EBK SVMR nezici ezihlanganisiwe (CaKMg) enamaphutha aphansi e-RMSE kanye ne-MAE ngokunemba okungu-63.7%.Kuvela ukuthi ukuhlanganisa i-algorithm ye-EBK ne-algorithm ye-hybrid ku-algorithm ye-Phrit ukusebenzisa i-Ca Mg K njengezibikezelo zokubikezela ukugxila kwe-Ni endaweni yocwaningo kungathuthukisa ukubikezela kwe-Ni emhlabathini.Lokhu kusho ukuthi ukusetshenziswa okuqhubekayo komanyolo owenziwe nge-nickel kanye nokungcoliswa komhlabathi kwezimboni yimboni yensimbi kunomkhuba wokwandisa ukugcwala kwe-nickel enhlabathini.Lolu cwaningo lwembula ukuthi imodeli ye-EBK inganciphisa izinga lephutha futhi ithuthukise ukunemba kwenhlabathi yendawo yasemadolobheni. ngokuvamile, siphakamisa ukusebenzisa imodeli ye-EBK-SVMR ukuhlola nokubikezela i-PTE enhlabathini; ngaphezu kwalokho, siphakamisa ukusebenzisa i-EBK ukuze sihlanganise ngama-algorithms okufunda omshini ahlukahlukene.Ukugxila kwe-Ni kwabikezelwa kusetshenziswa izakhi njengama-covariate; kodwa-ke, ukusebenzisa ama-covariate amaningi kungathuthukisa kakhulu ukusebenza kwemodeli, okungabhekwa njengomkhawulo womsebenzi wamanje.Omunye umkhawulo walolu cwaningo ukuthi inani lamasethi edatha liyi-115.Ngakho-ke, uma idatha eyengeziwe inikezwa, ukusebenza kwendlela ehlongozwayo yokwenza inhlanganisela elungiselelwe kahle ingathuthukiswa.
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