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Wasakhowga carradu waa dhibaato weyn oo ay keento hawlaha bani'aadamka. Qaybinta meelaha sunta ah ee suurtagalka ah ee sunta ah (PTEs) waxay ku kala duwan yihiin inta badan magaalooyinka iyo xaafadaha magaalooyinka. Sidaa darteed, way adagtahay in la saadaaliyo waxa ku jira PTE-yada ee carradan oo kale. Wadar ahaan 115 muunado ayaa laga helay Frydek Mistek ee Czech Republic. d Plasma emission spectrometry. Doorsoomayaasha jawaab-celinta waa Ni iyo saadaaliyayaashu waa Ca, Mg, iyo K. Isku-xidhka isku-xidhka u dhexeeya doorsoomiyaha jawaab-celinta iyo doorsoomiyaha saadaasha waxay muujinaysaa isku-xirnaanta ku qanacsanaanta u dhexeeya walxaha. Waxay ka sarreeyaan hababka kale ee lagu dabaqay. Noocyada isku dhafan ee Empirical Bayesian Kriging-Multiple Linear Regression (EBK-MLR) ayaa si liidata u shaqeynaya, sida lagu caddeeyey isku-dhafka go'aaminta wax ka yar 0.1. The Empirical Bayesian Kriging-Support Vector Machine Regression (EBK-SVMR) wuxuu ahaa qaabka ugu hooseeya.7.7 8 mg/kg) qiyamka iyo iskudarka sare ee go'aaminta (R2 = 0.637) .The EBK-SVMR farsamada wax soo saarka qaabaynta waxaa lagu sawiray iyadoo la isticmaalayo khariidad is-abaabulan s gudaha carrada magaalooyinka iyo agagaarkeeda.
Nickel (Ni) waxaa loo tixgeliyaa nafaqeeyayaalka yar yar ee dhirta sababtoo ah waxay gacan ka geysataa hagaajinta nitrogen atmospheric (N) iyo dheef-shiid kiimikaadka urea, labadaba waxaa looga baahan yahay biqilka abuurka. Marka lagu daro waxtarkeeda biqilka abuurka, Ni waxay u dhaqmi kartaa sida fungal iyo bakteeriyada inhibitor waxayna kor u qaaddaa horumarinta dhirta. Bacriminta ku salaysan si kor loogu qaado nitrogen fixation2.Continued Codsiga ee Bacriminta nikkel-ku salaysan si loo kobciyo ciidda iyo in la kordhiyo awoodda digiraha si loo hagaajiyo nitrogen ee ciidda si joogto ah u kordhiyaa fiirsashada nickel ee ciidda.In kasta oo nickel waa nafaqeeyayaalka yar ee dhirta, ay qaadashada xad-dhaaf ah ee ciidda samayn kartaa waxyeello ka badan wanaagsan. Sida laga soo xigtay Liu3, Ni ayaa la ogaaday in ay 17th element muhiim ah looga baahan yahay horumarinta dhirta iyo koritaanka.In waxaa dheer in doorka nickel ee horumarinta dhirta iyo koritaanka, aadanuhu u baahan yahay codsiyada kala duwan.Electroplating, wax soo saarka ee Alloys ku salaysan nikkel, iyo wax soo saarka ee qalabka dabka iyo dhimbiilo in warshadaha baabuurta oo dhan waxay u baahan yihiin isticmaalka kala duwan ee warshadaha nickel. si weyn loogu isticmaalo qalabka jikada, accessories qolka ball, sahayda warshadaha cuntada, koronto, silig iyo fiilada, marawaxadaha jet, implants qalliinka, dunta, iyo shipbuilding5.Ni-heerarka hodanka ah ee carradu (ie, carradu dusha) ayaa loo aaneeyey in ay labada anthropogenic iyo ilaha dabiiciga ah, laakiin ugu horrayn, Ni waa il dabiici ah halkii anthropogenic.si kastaba ha ahaatee, ilaha anthropogenic waxaa ka mid ah baytariyada nikkel / cadmium ee warshadaha birta, electroplating, alxanka arc, naaftada iyo saliidaha shidaalka, iyo hawada hawada ka gubanaya gubasho dhuxusha iyo qashinka iyo gubasho sludge Nickel accumulation7,8.Sida laga soo xigtay Freedman iyo Hutchinson9 iyo Manyiwa et al.10, ilaha ugu muhiimsan ee wasakhowga ciidda sare ee deegaanka dhow iyo kuwa u dhow ayaa ah inta badan nikkel-copper-ku salaysan dhoobada iyo macdanta. iyo al.12, qaddarka nikkel HNO3-soo saari kara ee gobolka ee dhulka sare beerashada (wax soo saarka nikkel ee Russia) u dhexeeyay 6.25 in 136.88 mg / kg, oo u dhiganta celceliska 30.43 mg / kg iyo diiradda aasaasiga ah ee 25 mg / kg. Sida laga soo xigtay kabata 11 dalagga fosfooraska ee xilli-ciyaareedka fosfooraska xilli-ciyaareedka xilliga beeralayda beeralayda ah ee beeralayda xilli-dhaqameed ee xilliga beerista. s waxay ku shubi kartaa ama wasakhayn kartaa ciidda. Saamaynta ka iman karta nikkel ee bini'aadamka waxay u horseedi kartaa kansar iyada oo loo marayo mutagenesis, dhaawaca koromosoomyada, jiilka Z-DNA, hagaajinta DNA-da ee xannibay, ama hababka epigenetic.
Qiimaynta faddaraynta carrada ayaa soo korodhay wakhtiyadii ugu dambeeyay sababo la xidhiidha arrimo badan oo la xidhiidha caafimaadka oo ka dhashay xidhiidhka ciidda-dhirta, xidhiidhka ciidda iyo ciidda, xaalufka deegaanka, iyo qiimaynta saamaynta deegaanka PSM) .Sida laga soo xigtay Minasny iyo McBratney16, khariidaynta ciidda saadaaliya (DSM) ayaa caddeeyey in ay tahay subdiscipline caan ah ee cilmiga ciidda.Lagacherie iyo McBratney, 2006 qeexaa DSM sida "abuurista iyo buuxinta ee nidaamka macluumaadka ciidda bannaan iyada oo la isticmaalayo in goobta iyo shaybaarka observational hababka iyo hababka ciidda iyo alwaaxdii.17 ayaa qeexaya in DSM-ka casriga ah ama PSM ay tahay farsamada ugu waxtarka badan ee saadaalinta ama khariidaynta qaybinta saadaasha ee PTE-yada, noocyada ciidda iyo hantida ciidda.Geostatistics and Machine Learning Algorithms (MLA) waa farsamooyinka qaabaynta DSM ee abuuraya khariidado digitized iyadoo la kaashanayo kombiyuutarada isticmaalaya xogta muhiimka ah iyo kuwa ugu yar.
Deutsch18 iyo Olea19 waxay ku qeexaan geostatistics sida "ururinta farsamooyinka tirooyinka ee la tacaalaya matalaadda sifooyinka boosaska, inta badan shaqaalaynta moodooyinka stochastic, sida sida falanqaynta taxanaha wakhtigu u tilmaamto xogta ku meel gaarka ah."Asal ahaan, geostatistics waxay ku lug leedahay qiimeynta variograms, taas oo u oggolaanaysa in la qiyaaso oo qeexo ku tiirsanaanta qiyamka boosaska ee xog kasta20.Gumiaux et al.20 waxay sii muujinaysaa in qiimaynta variograms ee geostatistics ay ku salaysan tahay saddex mabda'a, oo ay ku jiraan (a) xisaabinta miisaanka isku xirka xogta, (b) aqoonsiga iyo xisaabinta anisotropy ee farqiga xogta iyo (c) marka lagu daro tixgelinta qaladka asalka ah ee xogta cabbirka ee ka soocaya saamaynta maxalliga ah, farsamooyinka isdhexgalka ayaa sidoo kale lagu qiyaasaa farsamooyinkan. kriging guud, wada-kriging, kriging caadiga ah, empirical Bayesian kriging, habka kriging fudud iyo farsamooyinka kale ee si fiican loo yaqaan si ay u khariidad ama saadaaliyaan PTE, sifooyinka ciidda, iyo noocyada ciidda.
Algorithms Barashada Machine (MLA) waa farsamo ilaa xad cusub oo ka shaqeeya fasalada xogta aan toos ahayn, shiday by algorithms ugu horrayn loo isticmaalo macdanta xogta, aqoonsado hababka xogta, iyo si joogto ah codsatay in ay kala soocida ee beeraha sayniska sida sayniska ciidda iyo soo celinta hawlaha. Warqado cilmi tiro badan oo ku tiirsan moodooyinka MLA si ay u saadaaliyaan PTE ee carrada, sida Tan et al.22 (kaymaha random ee qiyaasta birta culus ee carrada beeraha), Sakizadeh et al.23 (qaabaynta iyadoo la adeegsanayo mashiinnada vector-ka taageerada iyo shabakadaha neerfaha ee macmalka ah) wasakhowga ciidda) .Intaa waxaa dheer, Vega et al.24 (CART loogu talagalay qaabaynta haynta birta culus iyo adsorption ee ciidda) Sun et al.25 (codsiga cubist waa qaybinta Cd ee ciidda) iyo algorithms kale sida k-dariska ugu dhow, dib u celinta guud ee kor loo qaaday, iyo kor u kaca Geedaha ayaa sidoo kale codsaday MLA si loo saadaaliyo PTE ee ciidda.
Codsiga algorithms DSM ee saadaasha ama khariidadda waxay la kulmaan caqabado dhowr ah. Qorayaal badan ayaa aaminsan in MLA uu ka sarreeyo geostatistics iyo liddi ku ah. Inkasta oo mid ka mid ah uu ka fiican yahay kan kale, isku dhafka labadaba waxay hagaajinayaan heerka saxda ah ee khariidadda ama saadaasha DSM15.Woodcock iyo Gopal26 Finke27;Pontius iyo Cheuk28 iyo Grunwald29 waxay ka faalloodaan cilladaha iyo khaladaadka qaarkood ee khariidaynta carrada ee la saadaaliyay. Saynisyahannada carradu waxay isku dayeen farsamooyin kala duwan si ay u wanaajiyaan waxtarka, saxnaanta, iyo saadaalinta khariidadda DSM iyo saadaalinta. Isku-darka hubin la'aanta iyo xaqiijinta waa mid ka mid ah dhinacyo badan oo kala duwan oo lagu dhex daray DSM si loo hagaajiyo waxtarka iyo si loo yareeyo wax-ku-oolnimada.15 waxay qeexaysaa in habdhaqanka ansaxinta iyo hubin la'aanta ay soo bandhigtay khariidad abuurista iyo saadaasha waa in si madaxbanaan loo ansixiyo si loo hagaajiyo tayada khariidadda. Xaddidaadda DSM waxaa sabab u ah tayada ciidda ee kala firirsan, taas oo ku lug leh qayb ka mid ah hubanti la'aanta;si kastaba ha ahaatee, la'aanta hubinta ee DSM ayaa laga yaabaa inay ka soo baxdo ilo badan oo qalad ah, kuwaas oo ah qalad isku dhafan, qalad model, qaladka goobta, iyo khaladaadka falanqaynta 31. Qaabaynta khaladaadka ku jira MLA iyo hababka geostatistical waxay la xidhiidhaan faham la'aan, ugu dambeyntiina waxay keenaysaa in la fududeeyo habka dhabta ah32. Iyadoo aan loo eegin dabeecadda moodeelka, qiyaasaha naqshadaynta, qiyaasaha isku-dhafka ah ee la qiyaasi karo. 33. Dhawaan, isbeddel cusub oo DSM ah ayaa soo baxay kaas oo kor u qaadaya isdhexgalka geostatistics iyo MLA ee khariidaynta iyo saadaalinta. Dhowr saynisyahano iyo qorayaal ciidda, sida Sergeev et al.34;Subbotina iyo al.35;Tarasov iyo al.36 iyo Tarasov et al.37 waxay ka faa'iidaysteen tayada saxda ah ee geostatistics iyo barashada mashiinka si ay u abuuraan moodooyin isku dhafan oo hagaajiya waxtarka saadaasha iyo khariidaynta.tayada.Qaar ka mid ah moodooyinkaas isku-dhafka ah ama isku-dhafka ah ee algorithm-ka waa Artificial Neural Network Kriging (ANN-RK), Multilayer Perceptron Residual Kriging (MLP-RK), Guud ahaan Dib-u-celinta Neural Network Residual Kriging (GR- NNRK) 36, Shabakadda Neural ee Artificial Kriging-Multiyer Perceptron (ANN-K-K-MLP-3)
Sida laga soo xigtay Sergeev et al., isku darka farsamooyinka moodeelka kala duwan ayaa awood u leh in la baabi'iyo cilladaha iyo kordhinta waxtarka qaabka isku-dhafka ah ee ka dhalanaya halkii ay ka horumarin lahaayeen qaabkeeda hal-abuurka ah Isku qas Mashiinka Taageerada Vector Machine (SVM) iyo Multiple Linear Regression (MLR). Isku-dhafka EBK ee leh MLA lama yaqaan. Noocyada kala duwan ee isku dhafan ee la arkay waa isku-dhafka caadiga ah, haraaga, dib-u-celinta kriging, iyo MLA.EBK waa habka is-dhexgalka juqraafiyeed ee isticmaala habka kaydinta spatially stochastic, oo u oggolaanaya in ka badan nidaam goobeed oo aan kala sooc lahayn. ing for spatial variation39.EBK ayaa loo adeegsaday cilmi-baarisyo kala duwan, oo ay ku jiraan falanqaynta qaybinta kaarboon organic ee carrada beeraha40, qiimaynta ciidda wasakhaysan41 iyo khariidaynta hantida ciidda42.
Dhinaca kale, Graph Self-Organizing Graph (SeOM) waa algorithm waxbarasho oo lagu dabaqay maqaallo kala duwan sida Li et al.43, Wang iyo al.44, Hossain Bhuyan et al.45 iyo Kebonye et al.46 Go'aami sifooyinkiisa iyo kooxaynta curiyeyaasha.Wang et al.44 waxay qeexaysaa in SeOM ay tahay farsamo waxbarasho oo awood leh oo loo yaqaan awoodda kooxaynta iyo qiyaasida dhibaatooyinka aan tooska ahayn. Si ka duwan farsamooyinka kale ee aqoonsiga qaabka sida falanqaynta qaybta asaasiga ah, koox-fudud-fudud, ururinta kala sareynta, iyo go'aaminta shuruudaha badan, SeOM waxay ku fiican tahay abaabulka iyo aqoonsiga qaababka PTE. Sida laga soo xigtay Wang et al.44, SeOM waxay kooxeyn kartaa qaybinta neurons-ka la xidhiidha waxayna bixin kartaa muuqaal xog heersare ah.
Warqadani waxay ujeedadeedu tahay in ay abuurto qaab khariidad adag oo sax ah oo qumman oo loogu talagalay saadaalinta nuxurka nikkel ee magaalooyinka iyo magaalooyinka hareeraheeda. Waxaan qiyaasaynaa in isku halaynta qaabka isku dhafan ay inta badan ku xiran tahay saameynta moodooyinka kale ee ku xiran qaabka aasaasiga ah. Waxaan aqoonsannahay caqabadaha soo wajaha DSM, iyo iyada oo caqabadahan lagu wajahayo dhinacyo badan, isku darka horumarka laga sameeyay moodooyinka geostatistics iyo MLASidaa darteed, waxaan isku dayi doonaa inaan ka jawaabno su'aalaha cilmi-baarista ee laga yaabo in ay soo saaraan noocyo isku dhafan. Si kastaba ha ahaatee, sida saxda ah ee qaabka loo saadaaliyo curiyaha bartilmaameedka?Sidoo kale, waa maxay heerka qiimeynta waxtarka leh ee ku salaysan ansaxinta iyo qiimeynta saxda ah? Sidaa darteed, ujeedooyinka gaarka ah ee daraasaddan waxay ahaayeen in (a) la abuuro qaab isku dhafan oo isku dhafan oo loogu talagalay SVMR ama MLR iyadoo la adeegsanayo EBK sida qaabka saldhigga ah, (bc) barbardhigga qaabka ugu fiican carrada magaalooyinka , iyo (d) adeegsiga SeOM si loo abuuro khariidad heer sare ah oo kala duwanaansho booseed nikkel ah.
Daraasadda waxaa lagu qabtaa Jamhuuriyadda Czech, gaar ahaan degmada Frydek Mistek ee gobolka Moravia-Silesian (fiiri sawirka 1) Juqraafiga goobta daraasaddu waa mid aad u qallafsan waxayna inta badan ka tirsan tahay gobolka Moravia-Silesian Beskidy, oo ah qayb ka mid ah cirifka bannaanka ee Buuraha Carpathian. Goobta daraasaddu waxay ku taallaa inta u dhaxaysa 49 ° 0 ′ 0 ′ 1 ′ 2 ′ 1 ′ 2 ′ 1 ′ 2 ′ 2 ′ 1 ′ 2 ′ 1 ′ 2 ′ 1 ′ 2 ′ 1 ′ 2 ′ 0 iyo 49 ° 1 ′ 2 ee Altitude inta u dhaxaysa 225 iyo 327 m;Si kastaba ha ahaatee, nidaamka kala soocidda Koppen ee xaaladda cimilada ee gobolka waxaa lagu qiimeeyaa sida Cfb = cimilada cimilada badweynta, Waxaa jira badan oo roobab ah xitaa bilaha qalalan. Heerkulka wax yar ayaa kala duwan sanadka oo dhan inta u dhaxaysa -5 °C iyo 24 °C, dhif hoos hoos -14 °C ama ka sarreeya 30 °C, halka celceliska waa inta u dhaxaysa 7 preci iyo 5. aagga waa 1,208 kiiloomitir oo laba jibbaaran, oo leh 39.38% dhulka la beero iyo 49.36% ee daboolka kaynta. Dhinaca kale, aagga loo isticmaalo daraasaddan waa qiyaastii 889.8 kiiloomitir oo laba jibbaaran. In iyo agagaarka Ostrava, warshadaha birta iyo shaqada birta ayaa aad u firfircoon. waxay kordhisaa xoogga daawaha iyadoo la ilaalinayo ductility wanaagsan iyo adkaanta), iyo beeraha degdega ah sida codsiga bacriminta fosfooraska iyo wax soo saarka xoolaha waa cilmi-baarista ilaha iman kara ee nikkel ee gobolka (tusaale, ku daray in nikkel in baraar si loo kordhiyo heerka koritaanka ee wananka iyo lo'da hooseeyo-quufin). midabka, qaab-dhismeedka, iyo content carbonate.The texture ciidda waa dhexdhexaad ah si ganaax, laga soo qaatay alaabta waalidka.Waxay yihiin colluvial, alluvial ama aeolian in nature.Some meelaha ciidda u muuqataa mottled ee dusha iyo ciidda hoose, inta badan la shubay iyo bleaching. Si kastaba ha ahaatee, cambisols iyo stagnosols yihiin noocyada ciidda ugu caansan ee gobolka, ranging ilaa 4 m. Czech Republic49.
Khariidadda goobta daraasadda [Khariidadda goobta daraasadda waxaa la sameeyay iyadoo la adeegsanayo ArcGIS Desktop (ESRI, Inc, nooca 10.7, URL: https://desktop.arcgis.com)
Isku darka 115 shaybaarka carrada sare ayaa laga helay carrada magaalooyinka iyo xaafadaha magaalada ee degmada Frydek Mistek. Nashqada muunada la isticmaalay waxay ahayd shabag caadi ah oo leh muunado carro ah oo u dhexeeya 2 × 2 km, iyo ciidda dusheeda waxaa lagu qiyaasay qoto dheer oo ah 0 ilaa 20 cm iyadoo la adeegsanayo qalab gacanta lagu hayo (Leica Zeno 5 GPS, Samples si sax ah baakadka GPS). s ayaa hawo lagu qallajiyey si ay u soo saaraan muunado la jajabiyey, oo lagu dhuftey nidaamka farsamada (Fritsch disc Mill), iyo shaandheyn (xajmiga shaandhada 2 mm) .Meesha 1 garaam oo la qalajiyey, isku-dhafka iyo shaybaarka ciidda ee si cad loo calaamadiyey dhalooyinka teflon. ly oo u ogolow shaybaarada in ay habeenkii u istaagaan falcelinta (barnaamijka aqua regia) Tuubo leh biyo la fuuqsaday.Waxaa intaa dheer, 1 ml oo ah xalinta qasidda waxaa lagu qasi jiray 9 ml oo biyo nadiif ah waxaana lagu sifeeyay tuubo 12 ml ah oo loo diyaariyey PTE-fiirin been abuur ah. rmo Fisher Scientific, USA) sida waafaqsan hababka caadiga ah iyo heshiis. Hubi Hubinta Tayada iyo Xakamaynta (QA/QC) hababka (SRM NIST 2711a Montana II Ciidda) .PTE-yada leh xaddidaadyada ogaanshaha ee ka hooseeya kala badh ayaa laga saaray daraasaddan. Xadka ogaanshaha ee PTE ee loo isticmaalo daraasaddan ayaa ahayd 0.0004. Hubi in khaladaadka la yareeyay, laba falanqayn ayaa la sameeyay.
Empirical Bayesian Kriging (EBK) waa mid ka mid ah farsamooyin badan oo geostatistical interpolation loo isticmaalo in lagu daydo in beeraha kala duwan sida sayniska ciidda.Unlike farsamooyinka interpolation kale kriging, EBK ka duwan hababka kriging dhaqanka iyadoo la tixgelinayo qalad lagu qiyaasay model semivariogram.In interpolation EBK, dhowr semivariogram ka dhigi qaab isku mid ah, halkii farsamada isku dhafan yihiin inta lagu guda jiro hab interpovarioter ah. Hubinta iyo barnaamijyada la xidhiidha sawir-qaadaha semivariogram-ka oo ka kooban qayb aad u adag oo ka mid ah habka kriging ku filan. Habka isdhexgalka ee EBK wuxuu raacayaa saddexda shuruudood ee uu soo jeediyay Krivoruchko50, (a) moodeelku wuxuu qiyaasayaa semivariogram-ka laga soo bilaabo dataset-gelinta (b) qiimaha cusub ee la saadaaliyay ee meel kasta oo wax-soo-galin ah oo ku salaysan xogta la soo saaray ee EBK waa qaab-dhismeedkii la soo saaray. qaanuunka quation-ka waxaa loo bixiyaa sida gadaal
Halka \ (Prob \ left (A \ right) \) ay ka dhigan tahay ka hor, \ ( dhibaatada \ bidix (B \ saxda ah) \) itimaalka marginal waa la iska indhatiray inta badan kiisaska, \ (Prob (B, A) \ ) samee xog-ururin xog-ururin ah oo laga soo qaatay semivariogram-ka.
Mashiinka vector-ka taageerada waa algorithm barashada mashiinka kaas oo soo saara hyperplane kala soocida ugu wanaagsan si loo kala saaro isku mid ah laakiin aan ahayn fasalo madaxbannaan oo toosan.Vapnik51 ayaa abuuray algorithm-ka-soocidda ujeeddada, laakiin dhawaan ayaa loo isticmaalay si loo xalliyo dhibaatooyinka dib-u-celinta. ) ayaa loo adeegsaday falanqayntan.Cherkassky iyo Mulier53 waxay horseedeen SVMR sida dib-u-celinta kernel-ku-salaysan, xisaabinta taas oo lagu sameeyay iyada oo la adeegsanayo qaabka dib-u-celinta tooska ah ee hawlaha gudaha ee dalal badan.55, epsilon (ε)-SVMR waxay isticmaashaa xogta loo tababaray si ay u hesho qaab matalaad ah oo ah shaqada epsilon-dareenka ah ee lagu dabaqo si loo khariideeyo xogta si madaxbanaan iyada oo la eegayo eexda epsilon ee ugu fiican ee tababarka ku saabsan xogta isku xidhan soo jeediyay Vapnik51 ayaa lagu muujiyay hoos.
halka b u taagan tahay marinka scalar, \(K\bidix({x}_{,}{ x}_{k}\right) \) waxay u taagan tahay shaqada kernel, \(\ alpha \) waxay u taagan tahay lagrange multiplikate, N waxay ka dhigan tahay tiro tiro ah, \({x}_{k} \) waxay matalaysaa xogta O, iyo \(y\us) waa xogta la isticmaalo. RBF.Kernel-ka RBF waxaa lagu dabaqaa si loo go'aamiyo qaabka ugu fiican ee SVMR, taas oo muhiim u ah in la helo qodobka ugu habboon ee ciqaabta C iyo kernel parameter gamma (γ) ee xogta tababarka PTE
Qaabka regression multi-linear (MLR) waa model regression oo ka tarjumaya xidhiidhka ka dhexeeya doorsoomiyaha jawaabta iyo tiro doorsoomayaal saadaaliya iyadoo la isticmaalayo doorsoomayaal toosan oo la xisaabiyay iyadoo la isticmaalayo habka ugu yar ee afar geesle ah. doorsoomayaal atory ah. Isla'egta MLR waa
halka y uu yahay doorsoomiyaha jawaabta, \(a \) waa dhexda, n waa tirada saadaaliyayaal, \({b}_{1}\) waa dib u noqoshada qaybeed ee coefficients, \({x}_{ i}
Noocyada isku dhafan waxaa lagu helay sandwiching EBK oo leh SVMR iyo MLR.Tani waxaa lagu sameeyaa iyada oo la soo saarayo qiyamka la saadaaliyay ee ka soo baxa EBK. Ca, K, Mg, CaK, CaMg, KMg iyo CaKMg. Doorsoomayaashani waxay noqdeen saadaashayada, iyagoo ka caawinaya in la saadaaliyo uruurinta nikkel ee magaalooyinka iyo carrada magaalooyinka.SVMR algorithm waxaa lagu sameeyay saadaasha si loo helo moodal isku dhafan Empirical Bayesian Kriging-Support Vector Machine (EBK_SVM) . -Multiple Linear Regression(EBK_MLR)
Isticmaalka SeOM waxa uu noqday qalab caan ah oo loogu talagalay abaabulka, qiimaynta, iyo odoroska xogta ee qaybta maaliyadeed, daryeelka caafimaadka, warshadaha, statistics, sayniska ciidda, iyo more.SeOM waxaa la abuuray iyadoo la isticmaalayo shabakadaha neural artifaalka ah iyo hababka waxbarasho ee aan la kormeerin ee abaabulka, qiimaynta, iyo saadaalin.In daraasaddan, SeOM loo isticmaalay in lagu sawiro Nii uruurinta ku salaysan habka ugu wanaagsan ee magaalada in la saadaaliyo habka ugu wanaagsan ee pelu pelu xogta. waxaa loo isticmaalaa sida n input-cabbir doorsoomayaasha vector43,56.Melssen et al.57 waxay qeexaysaa isku xirka vector-ka gelinta shabakada neerfaha iyada oo loo marayo hal lakab oo wax soo saar leh oo leh halbeeg miisaan leh.Wax soo saarka SeOM waa khariidad laba-geesood ah oo ka kooban neurons ama noodes kala duwan oo lagu dhejiyay khariidado heer-sare ah, wareeg ah, ama labajibbaaran khariidadaha dusha sare iyadoo loo eegayo isu-dhowaanshahooda 6 iyo 0.904, siday u kala horreeyaan, ayaa la doortay, taas oo ah cutubka 55-map (5 × 11) . Qaab dhismeedka neuron waxaa lagu go'aamiyaa iyadoo loo eegayo tirada qanjidhada ee isla'egta empirical
Tirada xogta loo isticmaalo daraasaddan waa shaybaarada 115. Habka random ayaa loo isticmaalay in lagu kala qaybiyo xogta xogta imtixaanka (25% ee ansaxinta) iyo sets xogta tababarka (75% for calibration) .The tababarka dataset waxaa loo isticmaalaa si ay u abuuraan model regression (calibration), iyo dataset imtixaanka waxaa loo isticmaalaa si loo xaqiijiyo awoodda guud58.This waxaa loo sameeyey si loo qiimeeyo ku haboonaanshaha model ah ee noocyada kala duwan ee loo isticmaalo nickel-ka-tallaalida. Hababka ation, soo noqnoqda shan jeer
Noocyada kala duwan ee ansaxinta ayaa loo isticmaalay si loo go'aamiyo qaabka ugu fiican ee ku habboon in la saadaaliyo qiyaasta nikkel ee ciidda iyo in la qiimeeyo saxnaanta qaabka iyo ansaxinta. Noocyada isku-dhafka ayaa lagu qiimeeyay iyada oo la adeegsanayo celceliska khaladka saxda ah (MAE), qaladka xididka celceliska (RMSE), iyo R-squared or coefficient go'aaminta (R2). awoodda moodeelka, halka MAE ay go'aamiso qiimaha dhabta ah ee dhabta ah. Qiimaha R2 waa inuu ahaadaa mid sarreeya si loo qiimeeyo qaabka isku dhafka ugu fiican iyadoo la adeegsanayo qiyaasaha ansaxinta, qiimaha u dhow waa 1, sare u kaca saxda ah. Sida laga soo xigtay Li et al.59, qiimaha R2 ee 0.75 ama ka weyn ayaa loo arkaa saadaaliye wanaagsan;laga bilaabo 0.5 ilaa 0.75 waa waxqabadka moodeelka ee la aqbali karo, ka hooseeya 0.5 waa waxqabadka moodeelka aan la aqbali karin.Marka la dooranayo moodal isticmaalaya hababka qiimeynta shuruudaha ansaxinta RMSE iyo MAE, qiyamka hoose ee la helay ayaa ku filan waxaana loo tixgeliyey doorashada ugu fiican. Isla'egta soo socota ayaa qeexaysa habka xaqiijinta.
halka n ka dhigan tahay cabbirka qiimaha la arkay \({Y}_{i} \) waxay u taagan tahay jawaabta la cabbiray, iyo \({\ widehat{Y}}_{i} \) sidoo kale waxay u taagan tahay qiimaha jawaabta la saadaaliyay, sidaa darteed, indha-indheynta ugu horreysa.
Sharaxaadaha tirakoobka ee saadaaliyayaal iyo doorsoomayaasha jawaabaha ayaa lagu soo bandhigay shaxda 1, oo muujinaysa celceliska, leexashada caadiga ah (SD), coefficient of variation (CV), ugu yaraan, ugu badnaan, kurtosis, iyo qallooca 39 mg/kg Mistek ee carrada magaalooyinka iyo agagaarkeeda ee daraasadda hadda (Ni 16.15 mg/kg) ayaa ka sarraysa xadka la oggol yahay ee 60 (10.2 mg/kg) ee Ni ee carradu magaalooyinka Polish ay soo wariyeen Różański et al. Intaa waxaa dheer, Bretzel iyo Calderisi61 la diiwaan geliyey celcelis ahaan celceliska ciidda hadda ah (1.78 mg/kg) Tusican ayaa sidoo kale laga helay tirada Nii ee hadda jirta. fiirsashada hoose ee nikkel (12.34 mg / kg) ee carradu Hong Kong, taas oo ka hooseysa diiradda nikkel hadda ee daraasaddan.Birke et al63 ayaa sheegay celceliska Nikkel ee 17.6 mg / kg ee macdanta duug ah iyo aagga warshadaha magaalooyinka ee Saxony-Anhalt, Germany, taas oo ahayd 1.45 mg/kg ka sarreeya celceliska Nick. meelaha qaar ee magaalooyinka iyo agagaarkeeda ee aagga daraasadda waxaa inta badan loo aaneynayaa warshadaha birta iyo birta iyo warshadaha birta. Tani waxay la socotaa daraasadda Khodadoust et al.64 in warshadaha birta iyo biraha ay yihiin ilaha ugu muhiimsan ee wasakheynta nikkel ee carrada. Si kastaba ha ahaatee, saadaaliyayaashu waxay sidoo kale u dhexeeyaan 538.70 mg / kg ilaa 69,161.80 mg / kg ee Ca, 497.51 mg / kg ilaa 3535.68 mg / kg ee K, iyo 65 mg / 5kg. kovljevic iyo al.65 ayaa baadhay wadarta guud ee Mg iyo K ee carrada bartamaha Serbia. Waxay ogaadeen in isku-darka guud (410 mg / kg iyo 400 mg / kg, siday u kala horreeyaan) ay ka hooseeyaan Mg iyo K ee daraasadda hadda jirta. Lama garan karo, bariga Poland, Orzechowski iyo Smolczynski66 waxay qiimeeyeen wadarta guud ee Mg0 iyo Cag0 (Mg0) 590 mg/kg) iyo K (810 mg/kg) Waxa ku jira carrada sare waxay ka hoosaysaa qaybta keliya ee daraasaddan. Daraasad dhowaan ay samaysay Pongrac et al.67 waxay muujisay in wadarta guud ee maadada Ca ee lagu falanqeeyay 3 carradood oo kala duwan oo ku yaala Scotland, UK ( Ciidda Mylnefield, Ciid Balruddery iyo Ciida Hartwood) ay muujinayso maadada Ca sare ee daraasaddan.
Iyada oo loo eegayo kala duwanaanshiyaha la cabbiray ee walxaha la soo saaray, qaybinta xogta xogta ee walxaha waxay muujinaysaa qalloocyo kala duwan. Qalfoofka iyo kurtosis ee walxaha waxay u dhexeeyaan 1.53 ilaa 7.24 iyo 2.49 ilaa 54.16. ked.Cv-yada la qiyaasay ee curiyayaasha ayaa sidoo kale muujinaya in K, Mg, iyo Ni ay muujiyaan kala duwanaansho dhexdhexaad ah, halka Ca uu leeyahay kala duwanaansho aad u sarreeya.CV-yada K, Ni iyo Mg waxay sharxayaan qaybintooda lebbiska ah. Intaa waxaa dheer, qaybinta Ca waa mid aan labis ahayn oo ilaha dibadda ayaa laga yaabaa inay saameeyaan heerka kobcinta.
Isku-xidhka doorsoomayaasha saadaasha leh ee jawaabaha jawaab-celinta waxay muujiyeen isku xirnaanta ku qanacsanaanta u dhexeeya walxaha (fiiri Jaantuska 3) Isku-xidhka ayaa tilmaamaya in CaK ay muujisay isku-xirnaansho dhexdhexaad ah oo leh r qiimaha = 0.53, sida CaNi. Inkasta oo Ca iyo K ay muujiyaan ururo dhexdhexaad ah oo midba midka kale ah, cilmi-baarayaasha sida Kingston et al.68 iyo Santo69 waxay soo jeedinayaan in heerarkooda carrada ay yihiin kuwo aan micno lahayn. NITITITER, MENSITIENIMITE, iyo potassium-ka waxaa lagu dabaqayaa carrada si loo kordhiyo heerarkoodii ... iyo MGESE, iyo 0.52, Magnesium waxay carqaladeysaa nuugida kaalshiyamka, kaalshiyamka waxay yareysaa saameynta magnesium-ka xad dhaafka ah , iyo Magnesium labadaba waxay yareeyaan saameynta sunta ah ee nikkel ee ciidda.
Matrix iskuxiran ee walxaha muujinaya xidhiidhka ka dhexeeya saadaasha iyo jawaabaha (Fiiro gaar ah: jaantuskan waxaa ku jira kala firdhiso u dhexeeya walxaha, heerarka muhiimka ah waxay ku saleysan yihiin p <0,001).
Jaantuska 4 wuxuu muujinayaa qaybinta qaybaha qaybaha. Sida laga soo xigtay Burgos et al70, codsiga qaybinta dhulku waa farsamo loo isticmaalo in lagu qiyaaso laguna muujiyo meelaha kulul ee meelaha wasakhaysan. Heerarka kobcinta Ca ee Jaantuska 4 waxaa laga arki karaa qaybta waqooyi-galbeed ee khariidadda qaybinta. cium oxide) si loo yareeyo aysidhka ciidda iyo isticmaalka birta birta sida oxygen alkaline ee habka steelmaking. Dhinaca kale, beeralayda kale door bidaan in ay isticmaalaan calcium hydroxide in carradu acidic si ay u baabi'iyaan pH, taas oo sidoo kale kordhisaa content calcium ee ciidda71.Potassium sidoo kale muujinaysaa dhibco kulul ee waqooyi-galbeed iyo bari ee map-The Waqooyi-galbeed waa a design sare ee bulshada beeraleyda Kto, iyo Potassium ee dhexdhexaadka ah, sababtoo ah waa beeralayda beeraleyda. waafaqsan daraasado kale, sida Madaras iyo Lipavský72, Madaras et al.73, Pulkrabova et al.74, Asare et al.75, kuwaas oo arkay in xasilinta ciidda iyo daaweynta KCl iyo NPK ay keentay in sare u kaca K ee ciidda.Kobcinta Potassium Spatial ee waqooyi-galbeed ee khariidadda qaybinta waxaa laga yaabaa in ay sabab u tahay isticmaalka Bacriminta potassium-ku salaysan sida chloride potassium, potassium sulfate, nitrate potassium, potash, iyo potash si loo kordhiyo content potassium ee carrada saboolka ah.Zádorová et al.76 iyo Tlustoš et al.77 ayaa qeexay in codsiga bacriminta K-ku salaysan ay kordhisay maadada K ee ciidda waxayna si weyn u kordhin doontaa nuxurka nafaqada ciidda mustaqbalka fog, gaar ahaan K iyo Mg oo muujinaya meel kulul ee ciidda sida potassium magnesium sulfate, magnesium sulfate, iyo Kieserite, daaweeya cilladaha (dhirta waxay u muuqdaan guduud, casaan, ama bunni, oo tilmaamaya yaraanta magnesium) ee carrada leh qiyaasta pH ee caadiga ah6. Isku-ururinta nikkel ee dusha sare ee magaalooyinka iyo hareeraha magaalada waxaa laga yaabaa inay sabab u tahay hawlaha anthropogenic sida beeraha iyo muhiimada wax soo saarka birta ee nikkel78.
Qaybinta qaybaha qaybaha [khariidad qaybinta boosaska waxaa la sameeyay iyadoo la adeegsanayo ArcGIS Desktop (ESRI, Inc, Version 10.7, URL: https://desktop.arcgis.com)]
Natiijooyinka tusmada waxqabadka moodeelka ee walxaha loo isticmaalo daraasaddan ayaa lagu muujiyay shaxda 2. Dhanka kale, RMSE iyo MAE ee Ni labaduba waxay ku dhow yihiin eber (0.86 RMSE, -0.08 MAE) . Dhanka kale, labadaba RMSE iyo MAE qiyamka K waa la aqbali karo iyadoo la adeegsanayo EBK si loo saadaaliyo Ni ayaa la ogaaday inay ka wanaagsan tahay natiijooyinka John et al.54 iyadoo la adeegsanayo kriging isku dhafan si loo saadaaliyo uruurinta S ee ciidda iyadoo la adeegsanayo isla xogta la ururiyay. Wax soo saarka EBK ee aan baranay waxay la mid yihiin kuwa Fabijaczyk et al.41, Yan iyo al.79, Beguin iyo al.80, Adhikary iyo al.81 iyo John et al.82, gaar ahaan K iyo Ni.
Waxqabadka hababka shakhsi ahaaneed ee saadaalinta nuxurka nikkel ee magaalooyinka iyo magaalooyinka hareeraheeda ayaa la qiimeeyay iyadoo la adeegsanayo waxqabadka moodooyinka (Shaxda 3) . Xaqiijinta qaabka iyo qiimeynta saxda ah waxay xaqiijisay in saadaalinta Ca_Mg_K oo ay weheliso qaabka EBK SVMR uu keenay waxqabadka ugu fiican. Qaabka Calibration Ca_Mg_K-EBK_SVMR model ab ), 95.479 mg/kg (RMSE) iyo 77.368 mg/kg (MAE) Ca_Mg_K-SVMR ahaa 0.663 (R2), 235.974 mg/kg (RMSE) iyo 166.946 mg/kg (MAE) .Si kastaba ha ahaatee, R2-qiimaha iyo Ca_Mg-EBK_SVMR (0.643 = R2);Natiijooyinkooda RMSE iyo MAE waxay ka sarreeyaan kuwa Ca_Mg_K-EBK_SVMR (R2 0.637) (fiiri shaxda 3) EBK_SVMR.Si la mid ah, RMSE iyo MAE ee Ca_Mg-K SVMR (RMSE = 235.974 iyo MAE = 166.946) moodelku waa 2.5 iyo 2.2 ka weyn kuwa Ca_Mg_K-EBK_SVMR RMSE iyo MAE, siday u kala horreeyaan natiijadii la xisaabiyey ee xariiqda ugu fiican. ME iyo MAE ayaa la arkay. Sida laga soo xigtay Kebonye et al.46 iyo john et al.54, marka la eego RMSE iyo MAE waa eber, natiijada ka sii wanaagsan SVMR iyo EBK_SVMR waxay leeyihiin qiime sare oo RSME iyo MAE ah. Waxaa la arkay in qiyaasaha RSME ay si joogta ah uga sarreeyaan qiimaha MAE, taas oo muujinaysa joogitaanka dibadda. Sida laga soo xigtay Legates iyo McCabe83, celceliska SE waa in uu dhaafo qiyaasta joogitaanka Tani waxay ka dhigan tahay in inta badan xog-ururinta, ay sare u kacdo qiimaha MAE iyo RMSE. Saxnaanta qiimaynta iskutallaabta ee Ca_Mg_K-EBK_SVMR ee qaabka isku dhafan ee saadaalinta nuxurka Ni ee magaalooyinka iyo carradu waxay ahayd 63.70% sida uu qabo Li et al.59, heerkan saxda ah waa heerka waxqabadka moodeelka la aqbali karo. Natiijooyinka hadda jira ayaa la barbardhigay daraasad hore oo Tarasov et al.36 kuwaas oo model hybrid abuuray MLPRK (Multiyer Perceptron Residual Kriging), oo la xidhiidha EBK_SVMR index qiimaynta saxda ah ee lagu soo warramey daraasadda hadda, RMSE (210) iyo MAE (167.5) ayaa ka sarreeyey natiijooyinkayaga daraasadda hadda (RMSE 95.479, MAE 77.368) hadda. Tarasov iyo al.36 (0.544), way caddahay in iskudarka go'aaminta (R2) uu ka sarreeyo qaabkan isku dhafan.Xirafka qaladka (RMSE iyo MAE) (EBK SVMR) ee qaabka isku dhafan waa laba jeer ka hooseeya. Sidoo kale, Sergeev et al.34 waxay diiwaan geliyeen 0.28 (R2) oo loogu talagalay qaabka isku-dhafka ah ee la sameeyay (R2) ee la duubay ee hadda jira (Multilayer Percept) . Heerka saxnaanta saadaasha moodelkan (EBK SVMR) waa 63.7%, halka saxnaanta saadaasha ay heleen Sergeev et al.34 waa 28% Khariidadda kama dambaysta ah (Jaantus 5) ee la sameeyay iyadoo la adeegsanayo qaabka EBK_SVMR iyo Ca_Mg_K oo ah saadaaliyayaal waxay muujinayaan saadaasha dhibco kulul iyo dhexdhexaad ilaa nikkel oo dhan aagga daraasadda. Tani waxay ka dhigan tahay in diiradda nikkel ee goobta daraasaddu ay inta badan dhexdhexaad tahay, oo leh meelo badan oo gaar ah.
Khariidadda saadaasha kama dambaysta ah waxaa lagu soo bandhigay iyadoo la adeegsanayo qaabka isku-dhafka ah ee EBK_SVMR iyo iyadoo la adeegsanayo Ca_Mg_K sida saadaalinta.
Waxaa lagu soo bandhigay Jaantuska 6 waa PTE-xoojinta sida diyaarad ka kooban oo ka kooban neurons shakhsi ah. Mid ka mid ah diyaaradaha qayb ka mid ah ma soo bandhigin qaabka midabka isku midka ah sida lagu muujiyay. Si kastaba ha ahaatee, tirada ku habboon ee neurons ee khariidadda la sawiray waa 55. SeOM waxaa la soo saaraa iyadoo la adeegsanayo midabyo kala duwan, iyo in ka badan oo la mid ah qaababka midabka, inta badan isbarbardhigga sifooyinka shaybaarada, midabka midabka M, midabka midabka midabka, midabka midabka midabka, midabka midabka midabka, midabka midabka midabka, midabka midabka midabka, midabka midabka, iyo midabka midabka. Neurons sare iyo inta badan neurons.Sidaas darteed, CaK iyo CaMg wadaagaan qaar ka mid ah la mid ah oo leh neurons aad u sarreeya iyo qaababka midabka hooseeya-ilaa-dhexdhexaad ah.Labada moodooyinka waxay saadaaliyaan xoojinta Ni ee ciidda iyagoo soo bandhigaya midabyo dhexdhexaad ah ilaa midabyo sare sida casaan, oranji iyo jaalle. Habka KMg wuxuu soo bandhigayaa qaabab badan oo midab leh oo ku salaysan cabbirka saxda ah ee cabbirka midabka iyo midabka hoose ilaa midabka hoose ee midabka midabka hoose. moodelku wuxuu muujiyay qaab midabkiisu sarreeyo oo tilmaamaya xoojinta awoodda nikkel ee ciidda (eeg Jaantuska 4) . Diyaaradda qaybta qaybta CakMg waxay muujinaysaa qaabka midabka kala duwan ee hoose ilaa sare marka loo eego cabbirka midabka saxda ah. Intaa waxaa dheer, saadaasha moodeelka ee nuxurka nikkel (CakMg) waxay la mid tahay qaybinta booska ee nikkel ee lagu muujiyay sawirka 5., labadaba garaafyada hoose ee hoose iyo hoose waxay muujinayaan heerka sare ee carrada. ure 7 waxa ay muujinaysaa habka contour ee k-macneheedu waa kooxaynta khariidada, oo loo qaybiyay saddex rucubood oo ku salaysan qiimaha la saadaaliyay ee model kasta. Habka konturku waxa uu ka dhigan yahay tirada ugu fiicnayd ee clusters. si loo ogolaado fasiraad sax ah oo kutlada
Wax soo saarka diyaaradda qayb kasta oo Empirical Bayesian Kriging Support Vector Machine (EBK_SVM_SeOM) doorsoome.
Qaybaha kala soocidda kooxeed ee kala duwan [maab SeOM waxa la abuuray iyadoo la isticmaalayo RStudio (nooca 1.4.1717: https://www.rstudio.com/)]
Daraasadda hadda jirta waxay si cad u muujineysaa farsamooyinka qaabaynta nikkel ee magaalooyinka iyo dhulka magaalooyinka. Daraasaddu waxay tijaabisay farsamooyinka moodeelka kala duwan, isku-darka walxaha leh farsamooyinka moodeelka, si aad u hesho habka ugu wanaagsan ee lagu saadaaliyo fiirsashada nikkel ee ciidda. qaybinta tial ee qaybaha soo bandhigay by EBK_SVMR (eeg sawirka 5) .Natiijooyinka waxay muujinayaan in taageerada mashiinka regression model (Ca Mg K-SVMR) saadaaliyay fiirsashada Ni ee ciidda sida hal model ah, laakiin ansixinta iyo xuduudaha qiimaynta saxda ah ayaa muujinaya khaladaad aad u sarreeya marka la eego RMSE iyo MAE.On dhinaca kale, farsamada qaabaynta ayaa sidoo kale la go'aamiyay qiimaha EBK ee EBK ee qiimaha hooseeyo ee EBK ah. (R2) .Natiijooyin wanaagsan ayaa la helay iyadoo la adeegsanayo EBK SVMR iyo walxaha isku dhafan (CaKMg) oo leh khaladaadka RMSE iyo MAE hooseeya ee saxda ah ee 63.7%.Waxay soo baxday in isku darka EBK algorithm ee mashiinka barashada algorithm uu dhalin karo algorithm hybrid kaas oo saadaalin kara xoojinta PTEs ee ciidda. Natiijooyinka waxay muujinayaan isticmaalka Ca Mg K sida saadaaliyayaal si loo saadaaliyo fiirsashada codsiga Ni. Bacriminta ku salaysan iyo wasakhaynta warshadaha ee carrada by warshadaha birta ayaa u janjeera in ay kordhiyaan diirada ee nikkel ee ciidda. Daraasaddan ayaa shaaca ka qaaday in model EBK hoos u dhigi karaa heerka qaladka iyo hagaajinta saxnaanta model ah ee qaybinta bannaan ee ciidda ee magaalooyinka ama agagaarka carradu.In guud ahaan, waxaan soo jeedinayaa in lagu dabaqo model EBK-SVMR si loo qiimeeyo oo loo saadaaliyo PTE ee ciidda;Intaa waxaa dheer, waxaan soo jeedinaynaa in la isticmaalo EBK si hybridize la algorithms barashada mashiinka kala duwan.Ni la saadaaliyay iyadoo la isticmaalayo xubno sida covariates;si kastaba ha ahaatee, isticmaalka covariates badan ayaa si weyn u wanaajin doona waxqabadka qaabka, taas oo loo tixgelin karo xaddidaadda shaqada hadda jirta. Xaddidaadda kale ee daraasaddan ayaa ah in tirada xogta ay tahay 115. Sidaa darteed, haddii xog dheeraad ah la bixiyo, waxqabadka habka isku-dhafka ah ee la soo jeediyay waa la hagaajin karaa.
PlantProbs.net.Nickel ee Dhirta iyo Ciidda
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