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Mmetọ ala bụ nnukwu nsogbu nke ihe ndị mmadụ na-eme. Nkesa oghere nke ihe ndị nwere ike ịkpata nsí (PTEs) dị iche iche n'ọtụtụ ebe obodo ukwu na obodo mepere emepe. Ya mere, ọ na-esiri ike ịkọ amụma gbasara ọdịnaya nke PTEs n'ime ala ndị dị otú ahụ. E nwetara ngụkọta ihe nlele 115 site na Frydek Mistek na Czech Republic. Ejiri usoro inductively coupled plasma emission spectrometry chọpụta njupụta Calcium (Ca), magnesium (Mg), potassium (K) na nickel (Ni). Mgbanwe nzaghachi bụ Ni na ndị na-ebu amụma bụ Ca, Mg, na K. Matrix njikọ dị n'etiti mgbanwe nzaghachi na mgbanwe amụma na-egosi njikọ dị mma n'etiti ihe ndị ahụ. Nsonaazụ amụma gosiri na Nkwado Vector Machine Regression (SVMR) rụrụ ọrụ nke ọma, ọ bụ ezie na atụmatụ ya bụ mgbọrọgwụ nkezi square error (RMSE) (235.974 mg/kg) na nkezi njehie zuru oke (MAE) (166.946 mg/kg) dị elu karịa ụzọ ndị ọzọ etinyere. Ụdị agwakọtara maka Empirical Bayesian Kriging-Multiple Linear Regression (EBK-MLR) na-arụ ọrụ. nke ọma, dịka egosiri site na ihe ndị na-egosi na ọ dịghị ihe karịrị 0.1. Ihe nlereanya Empirical Bayesian Kriging-Support Vector Machine Regression (EBK-SVMR) bụ ihe nlereanya kacha mma, yana obere RMSE (95.479 mg/kg) na MAE (77.368 mg/kg) na nnukwu ọnụọgụ mkpebi (R2 = 0.637). A na-ahụ mmepụta usoro ihe nlereanya EBK-SVMR site na iji maapụ nke na-ahazi onwe ya. Mkpụrụ akwara ndị a na-ejikọta na mbara nke ihe nlereanya ngwakọ CakMg-EBK-SVMR na-egosi ọtụtụ ụkpụrụ agba nke na-ebu amụma mkpokọta Ni na ala obodo ukwu na nke obodo ukwu. Nsonaazụ ya na-egosi na ijikọta EBK na SVMR bụ usoro dị irè maka ịkọ amụma mkpokọta Ni na ala obodo ukwu na nke obodo ukwu.
A na-ewere Nickel (Ni) dị ka ihe na-edozi ahụ maka osisi n'ihi na ọ na-enyere aka na nhazi nitrogen ikuku (N) na metabolism urea, ha abụọ bụ ihe dị mkpa maka mkpụrụ osisi. Na mgbakwunye na ntinye aka ya na mpụta mkpụrụ, Ni nwere ike ịrụ ọrụ dị ka ihe mgbochi fungal na nje bacteria ma kwalite mmepe osisi. Enweghị nickel n'ime ala na-enye osisi ohere ịmịkọrọ ya, na-ebute chlorosis nke akwụkwọ. Dịka ọmụmaatụ, agwa cowpeas na agwa akwụkwọ ndụ akwụkwọ ndụ chọrọ itinye fatịlaịza dabere na nickel iji mee ka nitrogen dịkwuo mma.2. Ịga n'ihu na itinye fatịlaịza dabere na nickel iji mee ka ala baa ọgaranya ma mee ka ikike nke legumes idozi nitrogen dị n'ala na-eme ka mkpokọta nickel dị n'ime ala na-abawanye.Ọ bụ ezie na nickel bụ obere ihe na-edozi ahụ maka osisi, oke oriri ya n'ime ala nwere ike imerụ ahụ karịa uru.Nsí nke nickel n'ime ala na-ebelata pH ala ma na-egbochi nnabata nke ígwè dị ka ihe dị mkpa maka uto osisi1.Dịka Liu3 si kwuo, achọpụtala na Ni bụ ihe nke iri na asaa dị mkpa achọrọ maka mmepe na uto osisi.Na mgbakwunye na ọrụ nickel na mmepe na uto osisi, ụmụ mmadụ chọrọ ya maka ọtụtụ ojiji.Electroplating, mmepụta nke nickel dabere na ihe ndị e ji ígwè rụọ, na imepụta ngwaọrụ ọkụ na ihe ndị e ji ekpo ọkụ na-eme ka ụgbọala rụọ ọrụ niile chọrọ iji nickel n'ọtụtụ ụlọ ọrụ mmepụta ihe. Na mgbakwunye, ejirila ihe ndị e ji nickel mee na ihe ndị e ji electroplated mee ihe n'ihe ndị e ji esi nri, ihe ndị e ji egwuri egwu, ihe ndị e ji egwuri egwu n'ụlọ nri, ihe ndị e ji egwuri egwu, ihe ndị e ji egwuri egwu, ihe ndị e ji egwuri egwu, ihe ndị e ji egwuri egwu, ihe e ji egwuri egwu, ihe e ji egwuri egwu, ihe e ji egwuri egwu, ihe e ji egwuri egwu, ihe e ji egwuri egwu, ihe e ji egwuri egwu, ákwà, na ihe e ji egwuri egwu. 5. A na-ekwu na ọ bụ ihe ndị e ji egwuri egwu n'ala (ya bụ, ala dị n'elu ala) ka ihe ndị e ji egwuri egwu n'ala na ihe ndị e ji egwuri egwu n'ala, mana nke bụ́ isi bụ na Ni bụ ihe e ji egwuri egwu n'ala kama ịbụ ihe e ji egwuri egwu n'ala. 4,6. Isi mmalite nke nickel gụnyere mgbawa ugwu mgbawa, ihe ọkụkụ, ọkụ ọhịa, na usoro ala; agbanyeghị, isi mmalite nke mmadụ gụnyere batrị nickel/cadmium na ụlọ ọrụ ígwè, ihe e ji egwuri egwu, ihe e ji egwuri egwu, mmanụ dizel na mmanụ ọkụ, na ikuku sitere na ọkụ coal na ihe mkpofu na ihe mkpofu na ihe ndị e ji egwuri egwu. Nchịkọta Nickel bụ 7,8. Dịka Freedman na Hutchinson9 na Manyiwa si kwuo. 10, isi ihe na-akpata mmetọ ala n'elu ala n'ebe dị nso na gburugburu bụ ihe ndị na-agbaze ihe na ihe ndị dị n'ime ala nke nwere nickel-copper. Ala dị n'elu gburugburu ụlọ ọrụ mmepụta nickel-copper nke Sudbury na Kanada nwere oke mmetọ nickel kachasị elu na 26,000 mg/kg11. N'ụzọ dị iche, mmetọ sitere na mmepụta nickel na Russia emeela ka mmụba nickel dị elu na ala Norway11. Dịka Alms et al si kwuo. 12, ọnụọgụ nke nickel a na-ewepụta site na HNO3 n'ala kachasị elu nke mpaghara ahụ (mmepụta nickel na Russia) sitere na 6.25 ruo 136.88 mg/kg, nke kwekọrọ na nkezi nke 30.43 mg/kg na mkpokọta ntọala nke 25 mg/kg. Dịka kabata 11 si kwuo, itinye fatịlaịza phosphorus n'ala ugbo n'ala obodo ukwu ma ọ bụ n'akụkụ obodo n'oge oge ihe ubi na-esochi nwere ike itinye ma ọ bụ merụọ ala ahụ. Mmetụta nke nickel nwere ike ime n'ime mmadụ nwere ike ibute ọrịa kansa site na mutagenesis, mmebi chromosomal, mmepụta Z-DNA, ndozi mwepụ DNA, ma ọ bụ usoro epigenetic13. Na nnwale anụmanụ, achọpụtala na nickel nwere ike ibute ọtụtụ etuto ahụ, na mgbagwoju anya nickel nwere ike ime ka etuto ahụ ka njọ.
Nnyocha mmetọ ala amụbaala n'oge na-adịbeghị anya n'ihi ọtụtụ nsogbu metụtara ahụike sitere na mmekọrịta ala na osisi, mmekọrịta bayọlọji ala na ala, mmebi gburugburu ebe obibi, na nyocha mmetụta gburugburu ebe obibi. Ruo taa, amụma oghere nke ihe ndị nwere ike ịkpata nsí (PTEs) dị ka Ni n'ime ala abụrụla ihe siri ike ma na-ewe oge site na iji usoro ọdịnala. Mbido nke eserese ala dijitalụ (DSM) na ihe ịga nke ọma ya ugbu a15 emeela ka eserese ala amụma (PSM) ka mma nke ukwuu. Dịka Minasny na McBratney16 si kwuo, eserese ala amụma (DSM) egosila na ọ bụ obere ngalaba sayensị ala. Lagacherie na McBratney, 2006 kọwara DSM dị ka "mmepụta na ijupụta usoro ozi ala oghere site na iji usoro nlele in situ na laabu na sistemụ ntinye ala oghere na nke na-abụghị oghere".McBratney et al. 17 na-akọwapụta na DSM ma ọ bụ PSM nke oge a bụ usoro kachasị dị irè maka ịkọ ma ọ bụ ịsepụta nkesa oghere nke PTE, ụdị ala na ihe onwunwe ala. Usoro mmụta geostatistics na igwe (MLA) bụ usoro ihe nlereanya DSM nke na-emepụta maapụ dijitalụ site n'enyemaka nke kọmputa na-eji data dị mkpa na nke pere mpe.
Deutsch18 na Olea19 kọwara geostatistics dị ka "nchịkọta usoro ọnụọgụgụ nke na-emeso nnọchite anya nke njirimara oghere, na-ejikarị ụdị stochastic, dị ka otu nyocha usoro oge si akọwa data oge." N'ụzọ bụ isi, geostatistics gụnyere inyocha variograms, nke na-enye ohere Quantify ma kọwaa ndabere nke uru oghere site na dataset ọ bụla20. Gumiaux et al. 20 na-egosikwa na nyocha nke variograms na geostatistics dabere na ụkpụrụ atọ, gụnyere (a) ịgbakọ nha nke njikọ data, (b) ịchọpụta na ịgbakọ anisotropy na ọdịiche dataset na (c) na mgbakwunye na ịtụle njehie dị n'ime nke data nha nke kewapụrụ na mmetụta mpaghara, a na-atụlekwa mmetụta mpaghara. Dabere na echiche ndị a, a na-eji ọtụtụ usoro interpolation na geostatistics, gụnyere kriging izugbe, co-kriging, kriging nkịtị, empirical Bayesian kriging, usoro kriging dị mfe na usoro interpolation ndị ọzọ a ma ama iji maapụ ma ọ bụ buo amụma PTE, njirimara ala, na ụdị ala.
Usoro mmụta igwe (MLA) bụ usoro ọhụrụ nke na-eji klaasị data ndị na-abụghị ahịrị buru ibu, nke algọridim ndị a na-ejikarị eme ihe maka igwupụta data, ịchọpụta ụkpụrụ dị na data, ma tinye ya ugboro ugboro na nhazi n'ọhịa sayensị dịka sayensị ala na ọrụ nlọghachi. Ọtụtụ akwụkwọ nyocha na-adabere na ụdị MLA iji buru amụma PTE na ala, dịka Tan et al. 22 (oke ọhịa na-enweghị usoro maka atụmatụ ígwè dị arọ na ala ugbo), Sakizadeh et al. 23 (ịme ihe nlereanya site na iji igwe vector nkwado na netwọk akwara artificial) mmetọ ala). Na mgbakwunye, Vega et al. 24 (CART maka ịme ihe nlereanya njide ígwè dị arọ na adsorption na ala) Sun et al. 25 (itinye cubist bụ nkesa nke Cd na ala) na algọridim ndị ọzọ dị ka k-onye agbata obi kacha nso, regression zuru oke, na regression kwalitere Osisi tinyekwara MLA iji buru amụma PTE na ala.
Itinye algọridim DSM n'ọrụ n'amụma ma ọ bụ nhazi ihe na-eche ọtụtụ ihe ịma aka ihu. Ọtụtụ ndị edemede kwenyere na MLA ka mma karịa geostatistics na nke ọzọ. Ọ bụ ezie na otu ka mma karịa nke ọzọ, njikọta nke abụọ ahụ na-eme ka ọkwa izi ezi nke nhazi ihe ma ọ bụ amụma dịkwuo mma na DSM15. Woodcock na Gopal26 Finke27; Pontius na Cheuk28 na Grunwald29 na-ekwu maka adịghị ike na ụfọdụ mmejọ na nhazi ala e buru n'amụma. Ndị ọkà mmụta sayensị ala anwalela ọtụtụ usoro iji melite arụmọrụ, izi ezi, na amụma nke nhazi na amụma DSM. Njikọta nke enweghị ejighị n'aka na nkwenye bụ otu n'ime ọtụtụ akụkụ dị iche iche etinyere na DSM iji melite arụmọrụ ma belata ntụpọ. Agbanyeghị, Agyeman et al. 15 na-akọwa na omume nkwenye na ejighị n'aka nke e kere maapụ na amụma webatara kwesịrị ịbụ nke a kwadoro n'onwe ya iji melite mma map. Mmachi nke DSM bụ n'ihi ịdị mma ala gbasaara na mpaghara, nke gụnyere akụkụ nke ejighị n'aka; Agbanyeghị, enweghị nkwenye na DSM nwere ike isite na ọtụtụ isi mmalite njehie pụta, ya bụ njehie covariate, njehie nlereanya, njehie ebe, na njehie nyocha 31. Mmebi ihe nlereanya na-ezighi ezi nke a na-ebute na MLA na usoro geostatistical jikọtara ya na enweghị nghọta, nke na-eduga na ime ka usoro ahụ dị mfe karịa 32. N'agbanyeghị ụdị ihe nlereanya ahụ, enwere ike ịkọwa na ezighi ezi na paramita ihe nlereanya, amụma ihe nlereanya mgbakọ na mwepụ, ma ọ bụ interpolation33. N'oge na-adịbeghị anya, usoro DSM ọhụrụ apụtala nke na-akwalite njikọta nke geostatistics na MLA na maapụ na amụma. Ọtụtụ ndị ọkà mmụta sayensị na ndị edemede ala, dị ka Sergeev et al. 34; Subbotina et al. 35; Tarasov et al. 36 na Tarasov et al. 37 ejirila ezigbo ịdị mma nke geostatistics na mmụta igwe mee ihe iji mepụta ụdị ngwakọ nke na-eme ka arụmọrụ nke amụma na maapụ dịkwuo mma. àgwà.Ụfọdụ n'ime ụdị algọridim ndị a bụ Artificial Neural Network Kriging (ANN-RK), Multilayer Perceptron Residual Kriging (MLP-RK), Generalized Regression Neural Network Residual Kriging (GR- NNRK)36, Artificial Neural Network Kriging-Multilayer Perceptron (ANN-K-MLP)37 na Co-Kriging na Gaussian Process Regression38.
Dịka Sergeev na ndị otu ya si kwuo, ijikọta usoro nhazi dị iche iche nwere ike iwepụ ntụpọ ma mee ka arụmọrụ nke ụdị nhazi ahụ pụta dịkwuo mma karịa ịmepụta otu ụdị ya. N'ọnọdụ a, akwụkwọ ọhụrụ a na-arụ ụka na ọ dị mkpa itinye algọridim jikọtara ọnụ nke geostatistics na MLA iji mepụta ụdị nhazi kachasị mma iji buo amụma mmụba Ni na mpaghara obodo na nke mepere emepe. Ọmụmụ ihe a ga-adabere na Empirical Bayesian Kriging (EBK) dị ka ụdị ntọala ma gwakọta ya na ụdị Nkwado Vector Machine (SVM) na Multiple Linear Regression (MLR). Amaghị njikọta nke EBK na MLA ọ bụla. Ọtụtụ ụdị ngwakọta a hụrụ bụ ngwakọta nke ihe nkịtị, ihe fọdụrụ, regression kriging, na MLA. EBK bụ usoro njikọta geostatistical nke na-eji usoro stochastic nke dị na mpaghara dị ka ubi na-abụghị nke na-anaghị eguzo/ọdụrụ na paramita mpaghara akọwapụtara n'elu ubi ahụ, na-enye ohere maka mgbanwe oghere39. Ejirila EBK mee ihe n'ọtụtụ ọmụmụ, gụnyere inyocha nkesa nke carbon organic na ala ugbo40, inyocha mmetọ ala41 na eserese ala. ihe onwunwe42.
N'aka nke ọzọ, eserese nhazi onwe onye (SeOM) bụ usoro mmụta nke etinyere n'ọrụ n'ọtụtụ isiokwu dịka Li et al. 43, Wang et al. 44, Hossain Bhuiyan et al. 45 na Kebonye et al. 46 Chọpụta njirimara oghere na nhazi nke ihe.Wang et al. 44 depụtara na SeOM bụ usoro mmụta dị ike a maara maka ikike ya ịhazi ma chee echiche banyere nsogbu ndị na-abụghị ahịrị. N'adịghị ka usoro nnabata ụkpụrụ ndị ọzọ dịka nyocha akụkụ bụ isi, nhazi fuzzy, nhazi ọkwa, na ime mkpebi ọtụtụ ihe, SeOM ka mma n'ịhazi na ịchọpụta ụkpụrụ PTE. Dịka Wang et al. 44 si kwuo, SeOM nwere ike ịchịkọta nkesa nke neurons metụtara ya n'ebe dị iche iche ma nye onyonyo data dị elu. SeOM ga-ahụ data amụma Ni iji nweta ụdị kachasị mma iji kọwaa nsonaazụ maka nkọwa kpọmkwem.
Akwụkwọ a na-achọ imepụta ụdị eserese siri ike nke nwere izi ezi kacha mma maka ịkọ amụma ọdịnaya nickel na ala obodo mepere emepe na nke dị n'ime obodo. Anyị na-eche na ntụkwasị obi nke ụdị agwakọtara dabere na mmetụta nke ụdị ndị ọzọ ejikọtara na ụdị ntọala ahụ. Anyị na-ekweta ihe ịma aka ndị a na-eche ihu DSM, ọ bụ ezie na a na-edozi ihe ịma aka ndị a n'ọtụtụ akụkụ, njikọta nke ọganihu na geostatistics na ụdị MLA yiri ka ọ na-abawanye ụba; ya mere, anyị ga-anwa ịza ajụjụ nyocha nke nwere ike ịpụta ụdị agwakọtara. Agbanyeghị, kedu ka ụdị ahụ si zie ezi n'ịkọ ihe ebumnuche? Ọzọkwa, kedu ọkwa nyocha arụmọrụ dabere na nyocha nkwenye na izi ezi? Ya mere, ebumnuche kpọmkwem nke ọmụmụ a bụ (a) ịmepụta ụdị ngwakọta ejikọtara ọnụ maka SVMR ma ọ bụ MLR site na iji EBK dị ka ụdị ntọala, (b) tụnyere ụdị ndị sitere na ya (c) tụọ aro ụdị ngwakọta kacha mma maka ịkọ amụma mkpokọta Ni na ala obodo mepere emepe ma ọ bụ nke dị n'ime obodo, na (d) itinye SeOM iji mepụta maapụ dị elu nke mgbanwe oghere nickel.
A na-eme nnyocha a na mba Czech Republic, ọkachasị na mpaghara Frydek Mistek dị na mpaghara Moravia-Silesia (lee eserese 1). Ọdịdị ala nke ebe a na-amụ ihe siri ike nke ukwuu ma bụrụ akụkụ nke mpaghara Moravia-Silesian Beskidy, nke bụ akụkụ nke mpụta nke Ugwu Carpathian. Ebe a na-amụ ihe dị n'etiti 49° 41′ 0′ N na 18° 20′ 0′ E, elu ya dịkwa n'etiti 225 na 327 m; Agbanyeghị, a na-enye usoro nhazi Koppen maka ọnọdụ ihu igwe nke mpaghara ahụ ọkwa Cfb = ihu igwe dị mma nke oke osimiri. Enwere ọtụtụ mmiri ozuzo ọbụlagodi n'oge ọkọchị. Okpomọkụ na-adịtụ iche n'afọ niile n'etiti −5 °C na 24 °C, ọ naghị adịkarị ala n'okpuru −14 °C ma ọ bụ karịa 30 °C, ebe nkezi mmiri ozuzo kwa afọ dị n'etiti 685 na 752 mm47. Mpaghara nyocha nke mpaghara ahụ dum bụ 1,208 square kilomita, yana 39.38% nke ala a kụrụ na 49.36% nke mkpuchi ọhịa. N'aka nke ọzọ, mpaghara ejiri mee ihe na nnyocha a dị ihe dị ka 889.8 square kilomita. N'ime na gburugburu Ostrava, ụlọ ọrụ ígwè na ọrụ ígwè na-arụ ọrụ nke ọma. Ụlọ ọrụ ígwè, ụlọ ọrụ ígwè ebe a na-eji nickel eme ihe na ígwè anaghị agba nchara (dịka ọmụmaatụ maka iguzogide corrosion ikuku) na ígwè alloy (nickel na-eme ka ike nke alloy dịkwuo elu ma na-ejigide ezigbo ductility na ike ya), na ọrụ ugbo siri ike dị ka itinye fatịlaịza phosphate na mmepụta anụ ụlọ bụ isi iyi nke nickel nwere ike ịnweta. na mpaghara ahụ (dịka ọmụmaatụ, itinye nickel na atụrụ iji mee ka ọnụego uto nke ụmụ atụrụ na ehi ndị na-azụghị nri dịkwuo elu). Ojiji ndị ọzọ nke nickel n'ụlọ ọrụ mmepụta ihe na mpaghara nyocha gụnyere ojiji ya na electroplating, gụnyere electroplating nickel na electroless nickel plating. A na-amata ihe onwunwe ala ngwa ngwa site na agba ala, nhazi, na ọdịnaya carbonate. Ọdịdị ala ahụ dị ọkara ruo na nke dị mma, sitere na ihe nne na nna. Ha bụ ihe jikọrọ ọnụ, alluvial ma ọ bụ aeolian n'okike. Ụfọdụ ebe ala na-apụta ìhè n'elu na ala dị n'okpuru ala, ọtụtụ mgbe na-enwe simenti na bleach. Agbanyeghị, cambisols na stagnosols bụ ụdị ala kachasị na mpaghara ahụ48. Site na elu dị site na 455.1 ruo 493.5 m, cambisols na-achị Czech Republic49.
Maapụ ebe ọmụmụ ihe [E ji ArcGIS Desktop (ESRI, Inc, ụdị 10.7, URL: https://desktop.arcgis.com) mepụta maapụ ebe ọmụmụ ihe ahụ.]
E nwetara ngụkọta nke ihe nlele ala dị n'elu 115 site na ala obodo ukwu na nke dị n'akụkụ obodo ukwu na mpaghara Frydek Mistek. Ihe nlereanya ejiri mee ihe bụ grid nkịtị nwere ihe nlele ala dị n'agbata 2 × 2 km, a tụkwara ala dị n'elu ya n'ime omimi nke 0 ruo 20 cm site na iji ngwaọrụ GPS ejiri aka jide (Leica Zeno 5 GPS). A na-etinye ihe nlele ndị ahụ n'ime akpa Ziploc, dee akara nke ọma, ma ziga ha na ụlọ nyocha. A kpọrọ ihe nlele ndị ahụ nkụ site na ikuku iji mepụta ihe nlele ndị a pịrị apị, jiri sistemụ igwe (Fritsch diski mill) gwerie ha, ma sie ha (nha sieve 2 mm). Tinye gram 1 nke ihe nlele ala kpọrọ nkụ, nke a mịrị amị ma sie ha n'ime karama teflon a ma ama. N'ime arịa Teflon ọ bụla, tinye 7 ml nke HCl 35% na 3 ml nke 65% HNO3 (jiri ihe na-ekesa akpaka - otu maka acid ọ bụla), kpuchie ha nke ọma ma kwe ka ihe nlele ndị ahụ guzoro n'abalị maka mmeghachi omume (mmemme aqua regia). Tinye ihe mkpuchi ahụ n'elu efere ígwè ọkụ (okpomọkụ: 100 W na 160 °C) ruo awa abụọ iji mee ka usoro mgbaze nke ihe nlele ahụ dị mfe, wee jụọ oyi. Bufee ihe mkpuchi ahụ na karama volumetric 50 ml ma gwakọta ya na mmiri deionized ruo 50 ml. Mgbe nke ahụ gasịrị, sachaa ihe mkpuchi ahụ a gwakọtara agwakọta n'ime tube PVC 50 ml na mmiri deionized. Na mgbakwunye, a gwakọtara 1 ml nke mmiri deionized na 9 ml nke mmiri deionized ma gwakọta ya na tube 12 ml nke akwadoro maka PTE pseudo-concentration. E kpebiri mkpokọta nke PTE (As, Cd, Cr, Cu, Mn, Ni, Pb, Zn, Ca, Mg, K) site na ICP-OES (Inductively Coupled Plasma Optical Emission Spectroscopy) (Thermo Fisher Scientific, USA) dịka usoro na nkwekọrịta ọkọlọtọ si dị. Hụ na usoro Nkwenye na Njikwa Ogo (QA/QC) (SRM NIST 2711a Montana II Soil). E wepụrụ PTE nwere oke nchọpụta n'okpuru ọkara na ọmụmụ ihe a. Oke nchọpụta nke PTE ejiri na nke a ọmụmụ ihe ahụ bụ 0.0004.(gị). Na mgbakwunye, a na-ahụ na njikwa mma na usoro nkwenye mma maka nyocha ọ bụla site na inyocha ụkpụrụ ntụaka. Iji hụ na e belatara mmejọ, e mere nyocha abụọ.
Empirical Bayesian Kriging (EBK) bụ otu n'ime ọtụtụ usoro njikọta geostatistical eji eme ihe nlereanya n'ọtụtụ ebe dịka sayensị ala. N'adịghị ka usoro njikọta kriging ndị ọzọ, EBK dị iche na usoro kriging ọdịnala site n'ịtụle njehie nke ihe nlereanya semivariogram mere atụmatụ. Na njikọta EBK, a na-agbakọ ọtụtụ ụdị semivariogram n'oge njikọta, kama otu semivariogram. Usoro njikọta na-eme ka ohere maka enweghị obi ike na mmemme jikọtara ya na atụmatụ a nke semivariogram nke bụ akụkụ dị mgbagwoju anya nke usoro kriging zuru oke. Usoro njikọta nke EBK na-agbaso usoro atọ nke Krivoruchko50 tụrụ aro, (a) ihe nlereanya ahụ na-eme atụmatụ semivariogram site na dataset ntinye (b) uru ọhụrụ e buru amụma maka ebe dataset ntinye ọ bụla dabere na semivariogram emepụtara na (c) a na-agbakọ ụdị A ikpeazụ site na dataset emere ka ọ dị ka ihe atụ. A na-enye iwu nha Bayesian dị ka ihe dị n'azụ
Ebe \(Prob\left(A\right)\) na-anọchite anya ihe ga-eme n'ọdịnihu, \(Prob\left(B\right)\) a na-eleghara ohere dị n'akụkụ anya n'ọtụtụ oge, \(Prob (B,A)\) .Ngụkọta semivariogram dabere na iwu Bayes, nke na-egosi oke nke data nlele nke enwere ike ịmepụta site na semivariograms. A na-ekpebi uru nke semivariogram site na iji iwu Bayes, nke na-egosi etu o si kwe omume ịmepụta data nke ihe nlele site na semivariogram.
Igwe nkwado vektọ bụ algọridim mmụta igwe nke na-emepụta hyperplane nkewa kachasị mma iji mata klaasị ndị nwere onwe ha n'usoro mana ọ bụghị n'usoro.Vapnik51 kere algọridim nhazi ebumnuche, mana ejirila ya n'oge na-adịbeghị anya iji dozie nsogbu ndị na-elekwasị anya na regression. Dịka Li et al.52 si kwuo, SVM bụ otu n'ime usoro nhazi kacha mma ma ejirila ya mee ihe n'ọtụtụ ubi. Ejiri akụkụ regression nke SVM (Support Vector Machine Regression - SVMR) mee ihe na nyocha a. Cherkassky na Mulier53 buru ụzọ SVMR dị ka regression dabere na kernel, nke ejiri usoro regression linear mee ya na ọrụ oghere dị iche iche. John et al54 kọrọ na SVMR modeling na-eji hyperplane linear regression, nke na-emepụta mmekọrịta na-abụghị ahịrị ma na-enye ohere maka ọrụ oghere. Dịka Vohland et al. si kwuo. 55, epsilon (ε)-SVMR na-eji dataset a zụrụ azụ iji nweta ihe nlereanya nnọchite anya dị ka ọrụ epsilon-enweghị mmetụta nke a na-etinye iji maapụ data ahụ n'adabereghị na ya na ajọ mbunobi epsilon kachasị mma site na ọzụzụ na data jikọtara ọnụ. A na-eleghara njehie anya nke edobere anya site na uru ahụ n'ezie, ọ bụrụkwa na njehie ahụ buru ibu karịa ε(ε), njirimara ala na-akwụghachi ya. Ihe nlereanya ahụ na-ebelatakwa mgbagwoju anya nke data ọzụzụ gaa na obere akụkụ nke vektọ nkwado. E gosipụtara nha nha nke Vapnik51 tụrụ aro n'okpuru.
ebe b na-anọchite anya oke scalar, \(K\left({x}_{,}{ x}_{k}\right)\) na-anọchite anya ọrụ kernel, \(\alpha\) na-anọchite anya ọnụọgụ Lagrange, N Na-anọchite anya dataset ọnụọgụ, \({x}_{k}\) na-anọchite anya ntinye data, na \(y\) bụ mmepụta data. Otu n'ime kernel ndị dị mkpa ejiri bụ ọrụ SVMR, nke bụ ọrụ ntọala radial Gaussian (RBF). A na-etinye kernel RBF iji chọpụta ụdị SVMR kachasị mma, nke dị oke mkpa iji nweta ihe kacha dị nro nke ntaramahụhụ C na gamma kernel paramita (γ) maka data ọzụzụ PTE. Nke mbụ, anyị nyochachara nhazi ọzụzụ wee nwalee arụmọrụ nlereanya na set nkwado. Paramita njikwa ejiri bụ sigma na uru usoro bụ svmRadial.
Ụdị mgbanwe dị iche iche (MLR) bụ ụdị mgbanwe dị iche iche nke na-anọchite anya mmekọrịta dị n'etiti mgbanwe nzaghachi na ọtụtụ mgbanwe ndị na-ebu amụma site na iji paramita ndị a gbakọrọ n'ahịrị site na iji usoro obere square. Na MLR, ụdị obere square bụ ọrụ amụma nke ihe onwunwe ala mgbe ahọpụtara mgbanwe nkọwa. Ọ dị mkpa iji nzaghachi guzobe mmekọrịta kwụ ọtọ site na iji mgbanwe nkọwa. Ejiri PTE mee ihe dị ka mgbanwe nzaghachi iji guzobe mmekọrịta kwụ ọtọ na mgbanwe nkọwa. Usoro MLR bụ
ebe y bụ mgbanwe nzaghachi, \(a\) bụ intercept, n bụ ọnụọgụ nke ndị na-ebu amụma, \({b}_{1}\) bụ mgbanwe akụkụ nke ihe ndị mejupụtara ya, \({x}_{ i}\) na-anọchite anya mgbanwe ihe ndị na-ebu amụma ma ọ bụ ihe nkọwa, na \({\varepsilon }_{i}\) na-anọchite anya njehie dị na ihe nlereanya ahụ, nke a makwaara dị ka ihe fọdụrụ.
E nwetara ụdị dị iche iche site na iji SBK na SVMR na MLR. A na-eme nke a site na iwepụta ụkpụrụ ndị e buru n'amụma site na njikọ EBK. A na-enweta ụkpụrụ ndị e buru n'amụma sitere na Ca, K, na Mg nke e tinyere n'ime ya site na usoro njikọta iji nweta mgbanwe ọhụrụ, dị ka CaK, CaMg, na KMg. A na-ejikọta ihe ndị Ca, K na Mg iji nweta mgbanwe nke anọ, CaKMg. N'ozuzu, mgbanwe ndị e nwetara bụ Ca, K, Mg, CaK, CaMg, KMg na CaKMg. Mgbanwe ndị a ghọrọ ndị na-ebu amụma anyị, na-enyere aka ịkọ amụma mkpokọta nickel na ala obodo ukwu na nke dị n'ime obodo. Emere algọridim SVMR na ndị na-ebu amụma iji nweta ụdị dị iche iche Empirical Bayesian Kriging-Support Vector Machine (EBK_SVM). N'otu aka ahụ, a na-etinyekwa mgbanwe site na algọridim MLR iji nweta ụdị dị iche iche Empirical Bayesian Kriging-Multiple Linear Regression (EBK_MLR). N'otu aka ahụ, mgbanwe ndị ahụ Ca, K, A na-eji Mg, CaK, CaMg, KMg, na CaKMg dị ka ihe na-egosi ọdịnaya Ni n'ime ala obodo ukwu na nke dị n'ime obodo ukwu. A ga-eji eserese nhazi onwe onye gosipụta ụdị kachasị anabatara (EBK_SVM ma ọ bụ EBK_MLR). E gosipụtara usoro ọrụ nke ọmụmụ a na Foto nke 2.
Iji SeOM aghọọla ngwa ọrụ a ma ama maka ịhazi, inyocha, na ịkọ amụma data na ngalaba ego, nlekọta ahụike, ụlọ ọrụ, ọnụ ọgụgụ, sayensị ala, na ihe ndị ọzọ. A na-emepụta SeOM site na iji netwọkụ akwara arụrụ arụ na ụzọ mmụta a na-anaghị elekọta maka nhazi, nyocha, na amụma. Na ọmụmụ ihe a, ejiri SeOM hụta njupụta Ni dabere na ụdị kacha mma maka ịkọ amụma Ni na ala obodo na nke dị n'ime obodo. A na-eji data edoziri na nyocha SeOM dị ka mgbanwe vektọ n ntinye-nha43,56.Melssen et al. 57 na-akọwa njikọ nke vektọ ntinye n'ime netwọk akwara site na otu oyi akwa ntinye na vektọ mmepụta nwere otu vektọ ibu. Ihe mmepụta nke SeOM mepụtara bụ maapụ akụkụ abụọ nke nwere neurons ma ọ bụ nodes dị iche iche nke e ji ihe dị n'ime maapụ hexagonal, okirikiri, ma ọ bụ square topological dịka ha si dị nso. Na-atụnyere nha maapụ dabere na metric, quantization error (QE) na topographic error (TE), a na-ahọrọ ụdị SeOM nwere 0.086 na 0.904, n'otu n'otu, nke bụ nkeji maapụ 55 (5 × 11). A na-ekpebi nhazi neuron dịka ọnụọgụgụ nodes dị na nhazi empirical si dị.
Ọnụọgụ data ejiri mee ihe n'ọmụmụ ihe a bụ ihe atụ 115. E jiri usoro enweghị usoro kewaa data ahụ n'ime data nnwale (25% maka nkwenye) na nhazi data ọzụzụ (75% maka nhazi). A na-eji data ọzụzụ emepụta ụdị regression (nhazi), a na-ejikwa data nnwale ahụ iji chọpụta ikike izugbe58. Emere nke a iji chọpụta ma ụdị dị iche iche hà kwesịrị maka ịkọ ọdịnaya nickel n'ala. Ụdị niile ejiri mee ihe gafere usoro nkwenye okpukpu iri, ugboro ugboro ise. A na-eji mgbanwe ndị EBK interpolation mepụtara dị ka ndị na-ebu amụma ma ọ bụ mgbanwe nkọwa iji buru amụma mgbanwe ebumnuche (PTE). A na-ejikwa ihe nlereanya na RStudio site na iji ọbá akwụkwọ ngwugwu (Kohonen), ọbá akwụkwọ (caret), ọbá akwụkwọ (modelr), ọbá akwụkwọ (“e1071″), ọbá akwụkwọ (“plyr”), ọbá akwụkwọ (“caTools”), ọbá akwụkwọ (“prospecter”) na ọbá akwụkwọ (“Metrics”).
E jiri ọtụtụ paramita nkwenye chọpụta ụdị kacha mma dabara adaba maka ịkọ oke nickel n'ala na inyocha izi ezi nke ụdị ahụ na nkwenye ya. E jiri mmejọ nke mean absolute error (MAE), root mean square error (RMSE), na R-squared ma ọ bụ coefficient determination (R2) nyochaa ụdị hybridization. R2 na-akọwa ọdịiche nke nha dị na azịza ahụ, nke nlereanya regression na-anọchite anya. RMSE na oke mgbanwe na nha onwe onye na-akọwa ike amụma nke ụdị ahụ, ebe MAE na-ekpebi uru nha ahụ n'ezie. Uru R2 ga-adị elu iji nyochaa ụdị ngwakọta kacha mma site na iji paramita nkwenye, ka uru ahụ na-eru nso 1, ka izi ezi ahụ ka elu. Dịka Li et al. 59 si kwuo, a na-ewere uru nhazi R2 nke 0.75 ma ọ bụ karịa dị ka ezigbo amụma; site na 0.5 ruo 0.75 bụ arụmọrụ nlereanya a na-anabata, na n'okpuru 0.5 bụ arụmọrụ nlereanya a na-anabataghị. Mgbe ị na-ahọrọ ụdị site na iji usoro nyocha njirisi nkwenye RMSE na MAE, uru dị ala enwetara zuru oke ma bụrụ nhọrọ kacha mma. Nhazi na-esote na-akọwa usoro nkwenye.
ebe n na-anọchite anya nha nke uru a hụrụ\({Y}_{i}\) na-anọchite anya nzaghachi a tụrụ, na \({\widehat{Y}}_{i}\) na-anọchitekwa anya uru nzaghachi a tụrụ anya ya, ya mere, maka ihe ngosi i mbụ.
A na-egosi nkọwa ọnụọgụgụ nke mgbanwe amụma na nzaghachi na Tebụl 1, na-egosi nkezi, ọdịiche ọkọlọtọ (SD), ọnụọgụgụ mgbanwe (CV), nke kacha nta, nke kacha, kurtosis, na skewness. Ọnụọgụ kacha nta na nke kachasị nke ihe ndị ahụ dị n'usoro Mg na-ebelata < Ca < K < Ni na Ca < Mg < K < Ni, n'otu n'otu. Ngụkọta nke mgbanwe nzaghachi (Ni) nke a nwalere site na mpaghara ọmụmụ sitere na 4.86 ruo 42.39 mg/kg. Ntụnyere nke Ni na nkezi ụwa (29 mg/kg) na nkezi nke Europe (37 mg/kg) gosiri na nkezi geometric agbakọrọ maka mpaghara ọmụmụ dị n'ime oke a na-anabata. Agbanyeghị, dịka Kabata-Pendias11 gosiri, ntụnyere nke nkezi nke mkpokọta nickel (Ni) na ọmụmụ ihe ugbu a na ala ugbo na Sweden na-egosi na nkezi nke mkpokọta nickel dị ugbu a dị elu. N'otu aka ahụ, nkezi nke mkpokọta Frydek Mistek na ala obodo ukwu na nke dị n'ime obodo ukwu na ọmụmụ ihe ugbu a (Ni 16.15 mg/kg) dị elu karịa nke a kwere. Oke nke 60 (10.2 mg/kg) maka Ni na ala obodo Poland nke Różański na ndị otu ya kọrọ. Ọzọkwa, Bretzel na Calderisi61 dekọrọ obere nkezi nke Ni (1.78 mg/kg) na ala obodo na Tuscany ma e jiri ya tụnyere ọmụmụ ihe a. Jim62 chọpụtakwara obere nke nickel (12.34 mg/kg) na ala obodo Hong Kong, nke dị ala karịa nke nickel dị ugbu a na ọmụmụ ihe a. Birke na ndị otu ya kọrọ na nkezi nke Ni nke 17.6 mg/kg na mpaghara ochie nke ebe a na-egwupụta ihe na ụlọ ọrụ mmepụta ihe na obodo na Saxony-Anhalt, Germany, nke dị 1.45 mg/kg karịa nkezi nke Ni na mpaghara ahụ (16.15 mg/kg). Nnyocha ugbu a. Oke oke nickel dị na ala na ụfọdụ mpaghara obodo na obodo nta nke mpaghara ọmụmụ ihe nwere ike ịbụ ihe kpatara ụlọ ọrụ ígwè na ígwè na ụlọ ọrụ ígwè. Nke a kwekọrọ na nnyocha nke Khodoust na ndị otu ya mere. 64 na ụlọ ọrụ ígwè na ọrụ ígwè bụ isi ihe na-akpata mmetọ nickel n'ala. Agbanyeghị, ndị na-ebu amụma ahụ malitekwara site na 538.70 mg/kg ruo 69,161.80 mg/kg maka Ca, 497.51 mg/kg ruo 3535.68 mg/kg maka K, na 685.68 mg/kg ruo 5970.05 mg/kg maka Mg.Jakovljevic et al. 65 nyochachara mkpokọta ọdịnaya Mg na K nke ala dị na etiti Serbia. Ha chọpụtara na mkpokọta mkpokọta (410 mg/kg na 400 mg/kg, n'otu n'otu) dị ala karịa mkpokọta Mg na K nke ọmụmụ ihe a. A naghị amata nke ọma, na ọwụwa anyanwụ Poland, Orzechowski na Smolczynski66 nyochachara mkpokọta ọdịnaya Ca, Mg na K ma gosipụta nkezi mkpokọta nke Ca (1100 mg/kg), Mg (590 mg/kg) na K (810 mg/kg). Ọdịnaya dị n'elu ala dị ala karịa otu ihe dị na ọmụmụ ihe a. Nnyocha e mere n'oge na-adịbeghị anya site n'aka Pongrac et al. 67 gosiri na mkpokọta ọdịnaya Ca nke a nyochachara na ala atọ dị iche iche na Scotland, UK (ala Mylnefield, ala Balruddery na ala Hartwood) gosiri ọdịnaya Ca dị elu na ọmụmụ ihe a.
N'ihi nha dị iche iche nke ihe ndị a tụrụ atụ, nkesa data nke ihe ndị ahụ na-egosi mgbanwe dị iche iche. Ngbanwe na kurtosis nke ihe ndị ahụ dị site na 1.53 ruo 7.24 na 2.49 ruo 54.16, n'otu n'otu. Ihe niile agbakọrọ nwere ọkwa skewness na kurtosis karịa +1, si otú a na-egosi na nkesa data adịghị agbanwe agbanwe, gbagọrọ agbagọ n'ụzọ ziri ezi ma ruo n'ọkwa kachasị elu. CV atụmatụ nke ihe ndị ahụ na-egosikwa na K, Mg, na Ni na-egosipụta mgbanwe dị mma, ebe Ca nwere nnukwu mgbanwe. CV nke K, Ni na Mg na-akọwa nkesa ha otu. Ọzọkwa, nkesa Ca abụghị otu na isi mmalite mpụga nwere ike imetụta ọkwa mmụba ya.
Njikọta nke ihe ndị na-eme amụma na ihe ndị na-aza gosiri njikọ dị mma n'etiti ihe ndị ahụ (lee eserese 3). Njikọta ahụ gosiri na CaK gosipụtara njikọ dị n'etiti ya na uru r = 0.53, dịka CaNi mere. Ọ bụ ezie na Ca na K na-egosi njikọ dị ala n'etiti onwe ha, ndị nchọpụta dịka Kingston et al. 68 na Santo69 na-atụ aro na ọkwa ha n'ala dị n'otu nhata. Agbanyeghị, Ca na Mg na-emegide K, mana CaK na-akpakọrịta nke ọma. Nke a nwere ike ịbụ n'ihi itinye fatịlaịza dịka potassium carbonate, nke dị 56% elu na potassium. Potassium nwere njikọ nke ọma na magnesium (KM r = 0.63). N'ime ụlọ ọrụ fatịlaịza, ihe abụọ a nwere njikọ chiri anya n'ihi na a na-etinye potassium magnesium sulfate, potassium magnesium nitrate, na potash na ala iji mee ka ọkwa enweghị ha dịkwuo elu. Nickel na-ejikọta nke ọma na Ca, K na Mg yana uru r = 0.52, 0.63 na 0.55, n'otu n'otu. Mmekọrịta metụtara calcium, magnesium, na PTE dị ka nickel dị mgbagwoju anya, mana agbanyeghị, magnesium na-egbochi nnabata calcium, calcium na-ebelata mmetụta nke oke magnesium, ma magnesium na calcium na-ebelata mmetụta nsí nke nickel na ala.
Matrix njikọ maka ihe ndị na-egosi mmekọrịta dị n'etiti ndị na-ebu amụma na nzaghachi (Rịba ama: ọnụọgụ a gụnyere eserese mgbasa ozi n'etiti ihe, ọkwa dị mkpa dabere na p < 0,001).
Foto nke 4 na-egosi nkesa oghere nke ihe ndị dị na ya. Dịka Burgos et al70 si kwuo, itinye nkesa oghere bụ usoro eji atụle ma gosipụta ebe ọkụ na-ekpo ọkụ n'ebe ndị ruru unyi. Enwere ike ịhụ ọkwa mmụba nke Ca na Foto nke 4 n'akụkụ ugwu ọdịda anyanwụ nke map nkesa oghere. Foto a na-egosi ebe ọkụ na-ekpo ọkụ nke Ca dị n'etiti ruo na elu. Ọ ga-abụ na mmụba nke calcium na ugwu ọdịda anyanwụ nke map ahụ bụ n'ihi ojiji nke quicklime (calcium oxide) iji belata acidity ala na ojiji ya na igwe ígwè dị ka oxygen alkaline na usoro nhazi ígwè. N'aka nke ọzọ, ndị ọrụ ugbo ndị ọzọ na-ahọrọ iji calcium hydroxide na ala acidic iji mee ka pH ghara ịdị irè, nke na-emekwa ka ọdịnaya calcium nke ala dịkwuo elu71. Potassium na-egosikwa ebe ọkụ na-ekpo ọkụ na ugwu ọdịda anyanwụ na ọwụwa anyanwụ nke map ahụ. Ugwu ọdịda anyanwụ bụ obodo ọrụ ugbo buru ibu, ụkpụrụ potassium dị n'etiti ruo na elu nwere ike ịbụ n'ihi NPK na ngwa potash. Nke a kwekọrọ na ọmụmụ ihe ndị ọzọ, dị ka Madaras na Lipavský72, Madaras et al.73, Pulkrabová et al.74, Asare et al.75, bụ ndị hụrụ na Nkwụsi ike na ọgwụgwọ nke KCl na NPK mere ka e nwee oke K n'ime ala. Mmeju Potassium n'ebe ugwu ọdịda anyanwụ nke map nkesa nwere ike ịbụ n'ihi ojiji nke fatịlaịza ndị dabeere na potassium dịka potassium chloride, potassium sulfate, potassium nitrate, potash, na potash iji mee ka ọdịnaya potassium dị n'ime ala na-adịghị mma dịkwuo elu. Zádorová et al. 76 na Tlustoš et al. 77 kọwara na itinye fatịlaịza dabere na K mụbara ọdịnaya K n'ime ala ma ga-eme ka ọdịnaya nri ala dịkwuo elu n'ikpeazụ, ọkachasị K na Mg na-egosi ebe ọkụ n'ime ala. Ebe ndị dị ntakịrị na-ekpo ọkụ n'ebe ugwu ọdịda anyanwụ nke map na ndịda ọwụwa anyanwụ nke map ahụ. Ndozi colloidal n'ime ala na-ebelata mkpokọta magnesium n'ime ala. Enweghị ala ya na-eme ka osisi gosipụta chlorosis intervein na-acha odo odo. Fatịlaịza dabere na Magnesium, dị ka potassium magnesium sulfate, magnesium sulfate, na Kieserite, na-agwọ ụkọ (osisi na-acha odo odo, ọbara ọbara, ma ọ bụ aja aja, na-egosi enweghị magnesium) n'ala nwere oke pH nkịtị6. Nchikọta nickel n'elu ala obodo ukwu na nke dị n'akụkụ obodo nwere ike ịbụ n'ihi ọrụ mmadụ dịka ọrụ ugbo na mkpa nickel na mmepụta ígwè anaghị agba nchara78.
Nkesa oghere nke ihe [ejiri ArcGIS Desktop (ESRI, Inc, Version 10.7, URL: https://desktop.arcgis.com) mepụta maapụ nkesa oghere [ebe a na-ekesa oghere).]
A na-egosi nsonaazụ ihe atụ nke ihe eji eme ihe n'ọmụmụ ihe a na Tebụl 2. N'aka nke ọzọ, RMSE na MAE nke Ni dị nso na efu (0.86 RMSE, -0.08 MAE). N'aka nke ọzọ, ma uru RMSE na MAE nke K bụ ihe a na-anabata. Nsonaazụ RMSE na MAE dị ukwuu maka calcium na magnesium. Nsonaazụ Ca na K MAE na RMSE buru ibu n'ihi data dị iche iche. Achọpụtara na RMSE na MAE nke ọmụmụ a na-eji EBK ebu amụma Ni ka mma karịa nsonaazụ nke John et al. 54 site na iji synergistic kriging buru amụma mkpokọta S n'ala site na iji otu data anakọtara. Nsonaazụ EBK anyị mụrụ na-ejikọta na nke Fabijaczyk et al. 41, Yan et al. 79, Beguin et al. 80, Adhikary et al. 81 na John et al. 82, karịsịa K na Ni.
A tụlere arụmọrụ nke usoro dị iche iche maka ịkọ amụma ọdịnaya nickel n'ime ala obodo ukwu na nke dị n'ime obodo ukwu site na iji arụmọrụ nke ụdị ndị ahụ (Tebụl 3). Nyocha nkwenye na izi ezi nke ụdị ahụ gosiri na amụma Ca_Mg_K jikọtara ya na ụdị EBK SVMR nyere arụmọrụ kacha mma. Ụdị nhazi Ca_Mg_K-EBK_SVMR nlereanya R2, njehie mgbọrọgwụ nkezi square (RMSE) na nkezi njehie zuru oke (MAE) bụ 0.637 (R2), 95.479 mg/kg (RMSE) na 77.368 mg/kg (MAE). Ca_Mg_K-SVMR bụ 0.663 (R2), 235.974 mg/kg (RMSE) na 166.946 mg/kg (MAE). Agbanyeghị, enwetara ezigbo uru R2 maka Ca_Mg_K-SVMR (0.663 mg/kg R2) na Ca_Mg-EBK_SVMR (0.643 = R2); nsonaazụ RMSE na MAE ha dị elu karịa nke Ca_Mg_K-EBK_SVMR (R2 0.637) (lee Tebụl 3). Na mgbakwunye, RMSE na MAE nke ụdị Ca_Mg-EBK_SVMR (RMSE = 1664.64 na MAE = 1031.49) bụ 17.5 na 13.4, n'otu n'otu, nke buru ibu karịa nke Ca_Mg_K-EBK_SVMR. N'otu aka ahụ, RMSE na MAE nke ụdị Ca_Mg-K SVMR (RMSE = 235.974 na MAE = 166.946) buru ibu karịa nke Ca_Mg_K-EBK_SVMR RMSE na MAE, n'otu n'otu. Nsonaazụ RMSE agbakọrọ na-egosi etu ntọala data siri dị na ahịrị nke dabara adaba kacha mma. A hụrụ RSME na MAE dị elu. Dịka Kebonye na ndị otu ya 46 na John na ndị otu ya 54, ka RMSE na MAE na-eru nso na efu, otú ahụ ka nsonaazụ ya ka mma.SVMR na EBK_SVMR nwere ụkpụrụ RSME na MAE dị elu. A hụrụ na atụmatụ RSME dị elu karịa ụkpụrụ MAE, na-egosi ọnụnọ nke ndị na-abụghị. Dịka Legates na McCabe83 si kwuo, a na-atụ aro oke RMSE gafere nkezi njehie zuru oke (MAE) dị ka ihe na-egosi ọnụnọ nke ndị na-abụghị. Nke a pụtara na ka dataset dị iche iche, otú ahụ ka ụkpụrụ MAE na RMSE si dị elu. Izi ezi nke nyocha nkwenye cross-validation nke ụdị Ca_Mg_K-EBK_SVMR agwakọtara maka ịkọ amụma ọdịnaya Ni na ala obodo ukwu na nke dị n'ime obodo bụ 63.70%. Dịka Li na ndị otu ya 59 si kwuo, ọkwa izi ezi a bụ ọnụego arụmọrụ nlereanya a na-anabata. A na-atụnyere nsonaazụ ugbu a na nnyocha gara aga nke Tarasov na ndị otu ya mere. 36 nke ụdị ngwakọ ya mepụtara MLPRK (Multilayer Perceptron Residual Kriging), metụtara ntụaka nyocha ziri ezi nke EBK_SVMR akọwara na ọmụmụ ihe a, RMSE (210) na The MAE (167.5) dị elu karịa nsonaazụ anyị na ọmụmụ ihe a (RMSE 95.479, MAE 77.368). Agbanyeghị, mgbe a na-atụnyere R2 nke ọmụmụ ihe ugbu a (0.637) na nke Tarasov et al. 36 (0.544), o doro anya na ihe mejupụtara mkpebi (R2) dị elu karịa na ihe nlereanya a agwakọta. Oke njehie (RMSE na MAE) (EBK SVMR) maka ihe nlereanya a gwakọtara agwakọta dị okpukpu abụọ ala. N'otu aka ahụ, Sergeev et al.34 dekọrọ 0.28 (R2) maka ihe nlereanya a kpụrụ akpụ (Multilayer Perceptron Residual Kriging), ebe Ni na ọmụmụ ihe a dekọrọ 0.637 (R2). Ọkwa izi ezi nke ihe nlereanya a (EBK SVMR) bụ 63.7%, ebe izi ezi nke amụma nke Sergeev et al. 34 nwetara bụ 28%. Maapụ ikpeazụ (Foto 5) e kere site na iji ihe nlereanya EBK_SVMR na Ca_Mg_K dị ka ihe amụma na-egosi amụma nke ebe ọkụ na oke ruo nickel n'elu mpaghara ọmụmụ ihe niile. Nke a pụtara na ntinye nke nickel na mpaghara ọmụmụ ihe bụkarị obere, yana ntinye dị elu na ụfọdụ mpaghara kpọmkwem.
A na-egosi maapụ amụma ikpeazụ site na iji ụdị ngwakọ EBK_SVMR ma jiri Ca_Mg_K mee ihe dị ka ihe na-ebu amụma.[E ji RStudio (ụdị 1.4.1717: https://www.rstudio.com/) mepụta maapụ nkesa oghere.]
E gosipụtara na Foto nke 6 na PTE dị ka ihe mejupụtara nke nwere neurons nke ọ bụla. Ọ dịghị nke ọ bụla n'ime ihe mejupụtara ya gosipụtara otu agba ahụ dịka egosiri. Agbanyeghị, ọnụọgụgụ neurons kwesịrị ekwesị maka maapụ eserese bụ 55. A na-emepụta SeOM site na iji agba dị iche iche, ka ụkpụrụ agba ha yikwara, otú ahụ ka njirimara nke ihe atụ ndị ahụ si yie. Dịka nha agba ha si dị, ihe ndị dị iche iche (Ca, K, na Mg) gosiri ụkpụrụ agba yiri nke ahụ na neurons dị elu na ọtụtụ neurons dị ala. Ya mere, CaK na CaMg nwere ụfọdụ myirịta na neurons dị elu na ụkpụrụ agba dị ala ruo nke na-adịghị oke. Ụdị abụọ ahụ na-ebu amụma mkpokọta Ni n'ime ala site na igosi agba agba dị n'etiti ruo na nke dị elu dịka ọbara ọbara, oroma na odo. Ụdị KMg na-egosipụta ọtụtụ ụkpụrụ agba dị elu dabere na nha ziri ezi na agba dị ala ruo nke ọkara. Na nha agba ziri ezi site na ala ruo na nke dị elu, ụkpụrụ nkesa planar nke ihe mejupụtara ihe nlereanya ahụ gosipụtara ụkpụrụ agba dị elu nke na-egosi ike itinye nickel n'ime ala (lee Foto 4). Ụdị ihe nlereanya CakMg na-egosi ụkpụrụ agba dị iche iche site na ala ruo na nke dị elu dịka agba ziri ezi si dị. nha. Ọzọkwa, amụma ihe nlereanya ahụ gbasara ọdịnaya nickel (CakMg) yiri nkesa oghere nke nickel egosiri na Foto 5. Grafụ abụọ ahụ na-egosi oke dị elu, ọkara na ala nke oke nickel na ala obodo ukwu na peri-obodo ukwu. Foto 7 na-egosi usoro nhazi na nchịkọta k-means na map, kewara n'ime otu atọ dabere na uru e buru n'amụma na ụdị ọ bụla. Usoro nhazi na-anọchite anya ọnụọgụ kachasị mma nke otu. N'ime ihe nlele ala 115 anakọtara, otu 1 nwetara ọtụtụ ihe nlele ala, 74. Klọsta 2 natara ihe nlele 33, ebe otu 3 natara ihe nlele 8. Ngwakọta amụma planar nke akụkụ asaa dị mfe iji nye ohere maka nkọwa klọsta ziri ezi. N'ihi ọtụtụ usoro mmadụ na okike na-emetụta nhazi ala, ọ siri ike inwe ụkpụrụ klọsta dị iche iche nke ọma na map SeOM kesara78.
Mmepụta nke akụkụ site na mgbanwe ọ bụla nke Empirical Bayesian Kriging Support Vector Machine (EBK_SVM_SeOM). [E jiri RStudio (ụdị 1.4.1717: https://www.rstudio.com/) mepụta maapụ SeOM.]
Akụkụ nhazi nkewa dị iche iche [E jiri RStudio mepụta maapụ SeOM (ụdị 1.4.1717: https://www.rstudio.com/).]
Ọmụmụ ihe a na-egosi nke ọma usoro nhazi maka mkpokọta nickel na ala obodo ukwu na nke mepere emepe. Ọmụmụ ihe a nwalere usoro nhazi dị iche iche, na-ejikọta ihe ndị dị na usoro nhazi, iji nweta ụzọ kachasị mma isi buru amụma mkpokọta nickel na ala. Atụmatụ oghere nhazi SeOM nke usoro nhazi gosipụtara ụkpụrụ agba dị elu site na obere ruo elu na nha agba ziri ezi, na-egosi mkpokọta Ni na ala. Agbanyeghị, maapụ nkesa oghere na-akwado nkesa oghere planar nke ihe ndị EBK_SVMR gosipụtara (lee Foto 5). Nsonaazụ ya na-egosi na ụdị nhazi igwe nkwado vector (Ca Mg K-SVMR) na-ebu amụma mkpokọta Ni na ala dị ka otu ụdị, mana paramita nyocha nkwenye na izi ezi na-egosi njehie dị elu n'ihe gbasara RMSE na MAE. N'aka nke ọzọ, usoro nhazi ejiri na ụdị EBK_MLR nwekwara ntụpọ n'ihi obere uru nke coefficient nke mkpebi (R2). E nwetara ezigbo nsonaazụ site na iji EBK SVMR na ihe ndị ejikọtara ọnụ (CaKMg) yana obere njehie RMSE na MAE yana izi ezi nke 63.7%. Ọ na-apụta na ijikọ EBK algọridim nwere algọridim mmụta igwe nwere ike ịmepụta algọridim ngwakọ nke nwere ike ibu amụma mkpokọta PTE n'ime ala. Nsonaazụ ya na-egosi na iji Ca Mg K dị ka ndị na-ebu amụma ibu amụma mkpokọta Ni n'ime mpaghara ọmụmụ ihe nwere ike ime ka amụma nke Ni ka mma n'ime ala. Nke a pụtara na itinye fatịlaịza dabere na nickel na mmetọ ụlọ ọrụ nke ala site na ụlọ ọrụ ígwè nwere ike ịbawanye mkpokọta nickel n'ime ala. Ọmụmụ ihe a kpughere na ụdị EBK nwere ike ibelata ọkwa njehie ma melite izi ezi nke ụdị nkesa oghere ala n'ime ala obodo ma ọ bụ n'ime obodo. N'ozuzu, anyị na-atụ aro itinye ụdị EBK-SVMR iji nyochaa ma buo amụma PTE n'ime ala; na mgbakwunye, anyị na-atụ aro iji EBK jikọta ya na algọridim mmụta igwe dị iche iche. E buru amụma mkpokọta Ni site na iji ihe dị ka covariates; agbanyeghị, iji ọtụtụ covariates ga-eme ka arụmọrụ nke ihe nlereanya ahụ ka mma nke ukwuu, nke a pụrụ iwere dị ka mmachi nke ọrụ dị ugbu a. Mmachi ọzọ nke ọmụmụ a bụ na ọnụọgụ nke datasets bụ 115. Ya mere, ọ bụrụ na enyere data karịa, enwere ike imeziwanye arụmọrụ nke usoro njikọta kachasị mma akwadoro.
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