Multiple regression and group method of data handling-based models for predicting arsenic concentration in sedimentary phosphate rock

Marine sedimentary phosphate rock is the primary source for manufacturing phosphate fertilizers. It is composed mainly of phosphorus and other elements. Some of these elements, including heavy metals, occur as trace elements. Notably, arsenic, classified as a Group I human carcinogen, is among them....

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Published in:	International journal of environmental science and technology (Tehran) Vol. 21; no. 9; pp. 6531 - 6552
Main Authors:	Dassamiour, M., Samai, D., Faghmous, N., Boustila, R.
Format:	Journal Article
Language:	English
Published:	Berlin/Heidelberg Springer Berlin Heidelberg 01.05.2024
Subjects:	algorithms Aquatic Pollution arsenic calcium oxide carcinogens data collection Earth and Environmental Science Ecotoxicology Environment Environmental Chemistry Environmental Science and Engineering equations heavy metals humans neurons Original Paper phosphorus prediction regression analysis rock phosphate Soil Science & Conservation Waste Water Technology Water Management Water Pollution Control Accuracy Sensitivity analysis Neural networks Heavy metals Combinatorial algorithm
ISSN:	1735-1472, 1735-2630
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Abstract	Marine sedimentary phosphate rock is the primary source for manufacturing phosphate fertilizers. It is composed mainly of phosphorus and other elements. Some of these elements, including heavy metals, occur as trace elements. Notably, arsenic, classified as a Group I human carcinogen, is among them. This research aims to develop an explicit model equation for predicting the concentration of arsenic in phosphate rock using backward stepwise multiple regression and two-group method of data handling algorithms: the combinatorial and type neural networks. A database of 277 datasets was compiled from thirteen reputable references for this purpose. The models’ input data are the major oxide contents (P 2 O 5 , CaO, MgO, SiO 2 , Al 2 O 3 , Fe 2 O 3 , K 2 O, and Na 2 O) in the phosphate samples. Three models of multiple regression and twenty-one models were constructed by combining various parameters, like the transformation function of input data and the neuron activation function. The performance of the proposed models was evaluated using metrics such as root mean square error, mean absolute error, and the coefficient of determination. In addition, sensitivity analysis was performed to inspect the impact of input variables on the model output. The results showed that the combinatorial algorithm provides the best model for predicting arsenic concentration with the highest level of accuracy in prediction. The validation results suggest that the combinatorial algorithm can be considered a promising approach for predicting heavy metal concentrations in phosphate rock with improved accuracy, and the model’s explicit form makes its practical application highly feasible.
AbstractList	Marine sedimentary phosphate rock is the primary source for manufacturing phosphate fertilizers. It is composed mainly of phosphorus and other elements. Some of these elements, including heavy metals, occur as trace elements. Notably, arsenic, classified as a Group I human carcinogen, is among them. This research aims to develop an explicit model equation for predicting the concentration of arsenic in phosphate rock using backward stepwise multiple regression and two-group method of data handling algorithms: the combinatorial and type neural networks. A database of 277 datasets was compiled from thirteen reputable references for this purpose. The models’ input data are the major oxide contents (P₂O₅, CaO, MgO, SiO₂, Al₂O₃, Fe₂O₃, K₂O, and Na₂O) in the phosphate samples. Three models of multiple regression and twenty-one models were constructed by combining various parameters, like the transformation function of input data and the neuron activation function. The performance of the proposed models was evaluated using metrics such as root mean square error, mean absolute error, and the coefficient of determination. In addition, sensitivity analysis was performed to inspect the impact of input variables on the model output. The results showed that the combinatorial algorithm provides the best model for predicting arsenic concentration with the highest level of accuracy in prediction. The validation results suggest that the combinatorial algorithm can be considered a promising approach for predicting heavy metal concentrations in phosphate rock with improved accuracy, and the model’s explicit form makes its practical application highly feasible. Marine sedimentary phosphate rock is the primary source for manufacturing phosphate fertilizers. It is composed mainly of phosphorus and other elements. Some of these elements, including heavy metals, occur as trace elements. Notably, arsenic, classified as a Group I human carcinogen, is among them. This research aims to develop an explicit model equation for predicting the concentration of arsenic in phosphate rock using backward stepwise multiple regression and two-group method of data handling algorithms: the combinatorial and type neural networks. A database of 277 datasets was compiled from thirteen reputable references for this purpose. The models’ input data are the major oxide contents (P 2 O 5 , CaO, MgO, SiO 2 , Al 2 O 3 , Fe 2 O 3 , K 2 O, and Na 2 O) in the phosphate samples. Three models of multiple regression and twenty-one models were constructed by combining various parameters, like the transformation function of input data and the neuron activation function. The performance of the proposed models was evaluated using metrics such as root mean square error, mean absolute error, and the coefficient of determination. In addition, sensitivity analysis was performed to inspect the impact of input variables on the model output. The results showed that the combinatorial algorithm provides the best model for predicting arsenic concentration with the highest level of accuracy in prediction. The validation results suggest that the combinatorial algorithm can be considered a promising approach for predicting heavy metal concentrations in phosphate rock with improved accuracy, and the model’s explicit form makes its practical application highly feasible.
Author	Faghmous, N. Dassamiour, M. Samai, D. Boustila, R.
Author_xml	– sequence: 1 givenname: M. orcidid: 0000-0003-3760-5639 surname: Dassamiour fullname: Dassamiour, M. email: mohamed.dassamiour@umc.edu.dz organization: Department of Geological Sciences, Faculty of Earth Sciences, Geography and Spatial Planning, Frères Mentouri Constantine 1 University. Lab. Géologie et Environnement (L.G.E), Lab. de Recherche de Géologie (L.R.G), Université Badji Mokhtar Annaba – sequence: 2 givenname: D. orcidid: 0000-0002-6198-9620 surname: Samai fullname: Samai, D. organization: Univ Ouargla, Fac. des Nouvelles Technologies de l’information et de la Communication. Lab. de Génie Electrique (LAGE) – sequence: 3 givenname: N. orcidid: 0000-0001-7613-8039 surname: Faghmous fullname: Faghmous, N. organization: Process Engineering Laboratory for Sustainable Development and Health Products, National Polytechnic School of Constantine – sequence: 4 givenname: R. orcidid: 0000-0002-8356-7277 surname: Boustila fullname: Boustila, R. organization: Département des Sciences de la Terre, Institut d’Architecture et des Sciences de la Terre, Université Ferhat Abbas Sétif 1
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Cites_doi	10.1136/fmch-2019-000262 10.1016/j.energy.2012.01.037 10.1016/j.asoc.2019.105524 10.1016/j.jestch.2019.05.013 10.1007/s12517-013-0837-1 10.1007/s00521-022-07382-3 10.1016/0005-1098(70)90092-0 10.1002/2015GC005861 10.1016/j.chemgeo.2015.06.011 10.1016/j.icheatmasstransfer.2022.106006 10.1016/j.petrol.2020.108182 10.1007/s11270-018-4072-y 10.1016/j.jenvman.2020.110797 10.1016/j.jafrearsci.2012.09.009 10.34312/jjom.v4i2.13529 10.1007/s11814-007-0073-z 10.1006/jcis.2002.8646 10.1016/j.arabjc.2014.10.007 10.1016/j.jhazmat.2023.133110 10.1016/j.sedgeo.2010.02.001 10.1016/j.apradiso.2016.05.012 10.1134/S1028334X14120022 10.1080/1064119X.2017.1415400 10.3390/ijerph121215016 10.1016/j.envpol.2016.05.054 10.1016/j.jhazmat.2010.06.020 10.1016/j.ijheatmasstransfer.2018.11.069 10.1016/j.asoc.2017.10.033 10.3390/ma14102570 10.1007/s40747-021-00480-0 10.1016/j.jseaes.2019.103931 10.3390/min6030088 10.1016/j.eti.2021.102041 10.1016/j.jprocont.2017.12.004 10.13031/2013.23153 10.1016/j.micres.2011.05.007 10.1007/s13146-018-0442-1 10.1016/j.seta.2020.100768 10.4103/jpcs.jpcs_18_20 10.1007/s13319-017-0137-8 10.38094/jastt1457 10.1016/j.margeo.2009.03.006 10.5194/gmd-7-1247-2014 10.1007/s00477-018-1588-z 10.1016/j.jhazmat.2021.126544 10.1016/j.mtcomm.2022.105286 10.1016/j.eng.2020.02.016 10.1016/j.chemosphere.2022.136732 10.1007/s11356-018-1648-4 10.1016/j.jafrearsci.2021.104398 10.1016/j.jenvman.2019.109872 10.1016/j.microc.2008.08.009 10.1007/s11042-019-08453-9 10.1155/2021/7819209 10.24191/mjoc.v6i1.8822 10.1016/j.jafrearsci.2020.104022 10.1126/sciadv.abd4049 10.1016/j.sedgeo.2018.08.001 10.2138/rmg.2002.48.2 10.1007/s12303-017-0013-9 10.1016/j.envsoft.2019.06.014 10.1016/j.gexplo.2013.04.001 10.1134/S1028334X17020222 10.1029/1998WR900018 10.1186/s12932-018-0055-6 10.1289/ehp.6964 10.1016/j.jafrearsci.2018.09.023 10.1016/j.envpol.2020.115126 10.1080/19392699.2020.1774563 10.2110/pec.80.29 10.1016/j.jafrearsci.2017.07.021 10.1016/j.chemosphere.2016.02.117 10.1016/j.chemosphere.2020.127138 10.1186/s40537-018-0143-6 10.1002/gj.3692 10.7717/peerj-cs.623 10.5897/JECI.9000004 10.1016/j.chemgeo.2016.12.001 10.1007/978-3-319-57413-4_17 10.1016/j.apgeochem.2021.104910 10.1007/978-3-030-63270-0_30 10.1088/1742-6596/1168/2/022022 10.1109/CSF.2018.00027 10.1007/978-3-319-70581-1_42 10.1088/1757-899X/324/1/012049 10.1016/B978-0-12-823818-9.00013-4 10.1007/9789463510868_011 10.1016/j.jafrearsci.2020.103826 10.1109/TSMC.1971.4308320
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References	Borboudakis, Tsamardinos (CR16) 2019; 20 Abed, Saffarini, Sadaqah (CR2) 2014; 7 Naderpour, Rezazadeh Eidgahee, Fakharian (CR57) 2020; 23 Abed, Sadaqah (CR1) 2013; 77 Chai, Draxler (CR20) 2014; 7 Sun, Quicksall, Chillrud (CR80) 2016; 153 Ivakhnenko (CR40) 1970; 6 Renard, Putnis, Montes-Hernandez, King (CR64) 2017; 449 Anandan, Manikandan (CR9) 2023; 34 Baturin (CR13) 2017; 472 Khurana, Singh (CR45) 2017; 8 CR71 Smith (CR77) 2018; 5 Maulud, Abdulazeez (CR49) 2020; 1 Otchere, Ganat, Gholami, Ridha (CR59) 2020 Wang, Xiong, He (CR85) 2020; 255 Mehmood, Chaudhry, Tufail, Irfan (CR50) 2009; 91 Moayedi, Osouli, Nguyen, Rashid (CR52) 2021; 37 Lütke, Oliveira, Silva (CR48) 2020; 256 Garnit, Bouhlel, Jarvis (CR33) 2017; 134 Khikmah, Indahwati, Fitrianto (CR44) 2022; 4 Faridullah, Umar, Alam (CR29) 2017; 21 Hendryx, Luo (CR39) 2020; 265 Salama, Khirekesh, Amini, Bafti (CR69) 2018; 376 Zhuang, Mu, Fu (CR92) 2020; 269 Ivakhnenko (CR41) 1976; 9 CR6 Amireh, Amaireh, Taha, Abed (CR7) 2019; 150 Ghasemian, Öztürk, Cansu (CR34) 2022; 185 Trzepieciński, Szpunar, Kaščák, uboš (CR82) 2021; 14 Pao, Fu, Tseng (CR61) 2012; 40 Pusat, Akkaya (CR62) 2020 Mola-Abasi, Eslami (CR54) 2019; 37 Nelson, Pufahl, Hiatt (CR58) 2010; 226 Chen, Zhu, Cai (CR21) 2021; 24 Rao, Sun, Tian (CR63) 2018; 32 Boumaza, Kechiched, Chekushina (CR17) 2021 CR89 CR42 Mo, Xie, Jiang (CR51) 2018; 62 Garbin, Zhu, Marques (CR32) 2020; 79 Strawn (CR79) 2018; 19 CR83 Zjavka (CR93) 2011; 2 Bentor (CR15) 1980 Pan, Fleet (CR60) 2002; 48 Amiri, Soleimani (CR8) 2021; 7 Saud, Jamil, Upadhyay, Irshad (CR70) 2020; 40 Boumaza, Kechiched, Chekushina (CR18) 2023 Rezazadeh Eidgahee, Jahangir, Solatifar (CR65) 2022; 34 Lenoble, Bouras, Deluchat (CR47) 2002; 255 Wasserman, Liu, Parvez (CR86) 2004; 112 Jia, Di, Feng (CR43) 2018; 62 Yang, Xiao, Xia (CR88) 2019; 182 Es-saidi, Oulguidoum, El Bekkali (CR28) 2021; 173 Güzelel, Olmuş, Çerçi, Büyükalaca (CR36) 2022; 134 Haque, Hossain (CR37) 2021; 2021 Mohapatra, Mishra, Chaudhury, Das (CR53) 2007; 24 CR56 Ruengvirayudh, Brooks (CR68) 2016; 42 Fashoto, Mbunge, Ogunleye, den Burg (CR30) 2021; 6 Wu, Nethery, Sabath (CR87) 2020; 6 Legates, McCabe (CR46) 1999; 35 Elbaz, Shen, Zhou (CR26) 2021; 7 Chicco, Warrens, Jurman (CR22) 2021; 7 Galai, Sliman (CR31) 2019; 12 Souza, Freitas, Mohallem, Ciminelli (CR78) 2021; 420 CR91 CR90 Baturin, Zhegallo, Shkolnik (CR14) 2014; 459 Al-Hobaib, Baioumy, Al-Ateeq (CR5) 2013; 132 Skiera, Reiner, Albers, Homburg, Klarmann, Vomberg (CR75) 2022 González, Somoza, Hein (CR35) 2016; 17 Slaughter, Macur, Inskeep (CR76) 2012; 167 El Zrelli, Rabaoui, Daghbouj (CR25) 2018; 25 Ahmad, Baioumy, Farouk (CR4) 2020; 55 El-Taher, Khater (CR27) 2016; 114 Chowdhury, Turin (CR23) 2020; 8 Moriasi, Arnold, Van Liew (CR55) 2007; 50 Antelo, Arce, Fiol (CR10) 2015; 410 Arning, Lückge, Breuer (CR12) 2009; 262 Cabaneros, Calautit, Hughes (CR19) 2019; 119 Shahsavar, Khanmohammadi, Karimipour, Goodarzi (CR73) 2019; 131 Abou El-Anwar (CR3) 2019; 34 CR67 Arco-Lázaro, Agudo, Clemente, Bernal (CR11) 2016; 216 Sureiman, Mangera (CR81) 2020; 6 Sekulić, Antanasijević, Stevanović, Trivunac (CR72) 2019; 230 Hein, Koschinsky, Mikesell (CR38) 2016; 6 Wang, Guo (CR84) 2022; 309 Singh, Singh (CR74) 2020; 97 da Silva, Mlayah, Gomes (CR24) 2010; 182 Rivas-Pérez, Paradelo-Núñez, Nóvoa-Muñoz (CR66) 2015; 12 X Wang (5452_CR85) 2020; 255 B Boumaza (5452_CR18) 2023 EF da Silva (5452_CR24) 2010; 182 SM Cabaneros (5452_CR19) 2019; 119 M Amiri (5452_CR8) 2021; 7 ET Arning (5452_CR12) 2009; 262 YK Bentor (5452_CR15) 1980 DA Otchere (5452_CR59) 2020 5452_CR56 JR Hein (5452_CR38) 2016; 6 C Garbin (5452_CR32) 2020; 79 T Mehmood (5452_CR50) 2009; 91 L Zjavka (5452_CR93) 2011; 2 H-T Pao (5452_CR61) 2012; 40 DN Moriasi (5452_CR55) 2007; 50 H Garnit (5452_CR33) 2017; 134 5452_CR91 BI Haque (5452_CR37) 2021; 2021 5452_CR90 A El-Taher (5452_CR27) 2016; 114 J Wang (5452_CR84) 2022; 309 Q Rao (5452_CR63) 2018; 32 A Shahsavar (5452_CR73) 2019; 131 GN Baturin (5452_CR13) 2017; 472 S Ghasemian (5452_CR34) 2022; 185 I Es-saidi (5452_CR28) 2021; 173 R El Zrelli (5452_CR25) 2018; 25 KN Khikmah (5452_CR44) 2022; 4 S Pusat (5452_CR62) 2020 P Ruengvirayudh (5452_CR68) 2016; 42 AS Al-Hobaib (5452_CR5) 2013; 132 L Mo (5452_CR51) 2018; 62 T Chai (5452_CR20) 2014; 7 SG Fashoto (5452_CR30) 2021; 6 O Sureiman (5452_CR81) 2020; 6 X Jia (5452_CR43) 2018; 62 F Ahmad (5452_CR4) 2020; 55 MZI Chowdhury (5452_CR23) 2020; 8 5452_CR89 D Chicco (5452_CR22) 2021; 7 V Lenoble (5452_CR47) 2002; 255 5452_CR42 X Wu (5452_CR87) 2020; 6 Z Zhuang (5452_CR92) 2020; 269 B Skiera (5452_CR75) 2022 D Singh (5452_CR74) 2020; 97 5452_CR83 EA Abou El-Anwar (5452_CR3) 2019; 34 FJ González (5452_CR35) 2016; 17 BS Amireh (5452_CR7) 2019; 150 H Naderpour (5452_CR57) 2020; 23 YE Güzelel (5452_CR36) 2022; 134 H Moayedi (5452_CR52) 2021; 37 M Hendryx (5452_CR39) 2020; 265 AG Ivakhnenko (5452_CR40) 1970; 6 B Anandan (5452_CR9) 2023; 34 M Khurana (5452_CR45) 2017; 8 IM Rivas-Pérez (5452_CR66) 2015; 12 W Chen (5452_CR21) 2021; 24 5452_CR71 AG Ivakhnenko (5452_CR41) 1976; 9 AM Abed (5452_CR1) 2013; 77 S Saud (5452_CR70) 2020; 40 E Arco-Lázaro (5452_CR11) 2016; 216 DR Legates (5452_CR46) 1999; 35 5452_CR6 DG Strawn (5452_CR79) 2018; 19 Z Sekulić (5452_CR72) 2019; 230 J Sun (5452_CR80) 2016; 153 B Boumaza (5452_CR17) 2021 F Faridullah (5452_CR29) 2017; 21 T Trzepieciński (5452_CR82) 2021; 14 D Mohapatra (5452_CR53) 2007; 24 H Mola-Abasi (5452_CR54) 2019; 37 D Rezazadeh Eidgahee (5452_CR65) 2022; 34 5452_CR67 J Antelo (5452_CR10) 2015; 410 SF Lütke (5452_CR48) 2020; 256 G Smith (5452_CR77) 2018; 5 TG Souza (5452_CR78) 2021; 420 D Maulud (5452_CR49) 2020; 1 F Renard (5452_CR64) 2017; 449 H Yang (5452_CR88) 2019; 182 K Elbaz (5452_CR26) 2021; 7 GJ Nelson (5452_CR58) 2010; 226 GA Wasserman (5452_CR86) 2004; 112 DC Slaughter (5452_CR76) 2012; 167 W Salama (5452_CR69) 2018; 376 GN Baturin (5452_CR14) 2014; 459 Y Pan (5452_CR60) 2002; 48 H Galai (5452_CR31) 2019; 12 AM Abed (5452_CR2) 2014; 7 G Borboudakis (5452_CR16) 2019; 20
References_xml	– volume: 8 year: 2020 ident: CR23 article-title: Variable selection strategies and its importance in clinical prediction modelling publication-title: Fam Med Commun Health doi: 10.1136/fmch-2019-000262 – volume: 40 start-page: 400 year: 2012 end-page: 409 ident: CR61 article-title: Forecasting of CO2 emissions, energy consumption and economic growth in China using an improved grey model publication-title: Energy doi: 10.1016/j.energy.2012.01.037 – volume: 97 year: 2020 ident: CR74 article-title: Investigating the impact of data normalization on classification performance publication-title: Appl Soft Comput doi: 10.1016/j.asoc.2019.105524 – volume: 23 start-page: 382 year: 2020 end-page: 391 ident: CR57 article-title: A new proposed approach for moment capacity estimation of ferrocement members using Group Method of Data Handling publication-title: Eng Sci Technol Int J doi: 10.1016/j.jestch.2019.05.013 – volume: 7 start-page: 253 year: 2014 end-page: 271 ident: CR2 article-title: Spatial distribution of uranium and vanadium in the upper phosphorite member in Eshidiyya basin, southern Jordan publication-title: Arab J Geosci doi: 10.1007/s12517-013-0837-1 – volume: 34 start-page: 17289 year: 2022 end-page: 17314 ident: CR65 article-title: Data-driven estimation models of asphalt mixtures dynamic modulus using ANN, GP and combinatorial GMDH approaches publication-title: Neural Comput Appl doi: 10.1007/s00521-022-07382-3 – volume: 6 start-page: 207 year: 1970 end-page: 219 ident: CR40 article-title: Heuristic self-organization in problems of engineering cybernetics publication-title: Automatica doi: 10.1016/0005-1098(70)90092-0 – volume: 17 start-page: 346 year: 2016 end-page: 374 ident: CR35 article-title: Phosphorites, Co-rich Mn nodules, and Fe-Mn crusts from Galicia Bank, NE Atlantic: reflections of Cenozoic tectonics and paleoceanography publication-title: Geochem Geophys Geosystems doi: 10.1002/2015GC005861 – volume: 410 start-page: 53 year: 2015 end-page: 62 ident: CR10 article-title: Arsenate and phosphate adsorption on ferrihydrite nanoparticles. Synergetic interaction with calcium ions publication-title: Chem Geol doi: 10.1016/j.chemgeo.2015.06.011 – volume: 134 year: 2022 ident: CR36 article-title: New multiple regression and machine learning models of rotary desiccant wheel for unbalanced flow conditions publication-title: Int Commun Heat Mass Transf doi: 10.1016/j.icheatmasstransfer.2022.106006 – year: 2020 ident: CR59 article-title: Application of supervised machine learning paradigms in the prediction of petroleum reservoir properties: comparative analysis of ANN and SVM models publication-title: J Pet Sci Eng doi: 10.1016/j.petrol.2020.108182 – volume: 230 start-page: 23 year: 2019 ident: CR72 article-title: The prediction of heavy metal permeate flux in complexation-microfiltration process: polynomial neural network approach publication-title: Water Air Soil Pollut doi: 10.1007/s11270-018-4072-y – volume: 269 year: 2020 ident: CR92 article-title: Accumulation of potentially toxic elements in agricultural soil and scenario analysis of cadmium inputs by fertilization: a case study in Quzhou county publication-title: J Environ Manage doi: 10.1016/j.jenvman.2020.110797 – ident: CR42 – volume: 77 start-page: 31 year: 2013 end-page: 40 ident: CR1 article-title: Enrichment of uranium in the uppermost Al-Hisa Phosphorite Formation, Eshidiyya basin, southern Jordan publication-title: J Afr Earth Sci doi: 10.1016/j.jafrearsci.2012.09.009 – volume: 4 start-page: 177 year: 2022 end-page: 187 ident: CR44 article-title: Backwards stepwise binary logistic regression for determination population growth rate factor in Java Island publication-title: Jambura J Math doi: 10.34312/jjom.v4i2.13529 – volume: 24 start-page: 426 year: 2007 end-page: 430 ident: CR53 article-title: Arsenic adsorption mechanism on clay minerals and its dependence on temperature publication-title: Korean J Chem Eng doi: 10.1007/s11814-007-0073-z – volume: 255 start-page: 52 year: 2002 end-page: 58 ident: CR47 article-title: Arsenic adsorption onto pillared clays and iron oxides publication-title: J Colloid Interface Sci doi: 10.1006/jcis.2002.8646 – ident: CR71 – volume: 12 start-page: 1607 year: 2019 end-page: 1614 ident: CR31 article-title: Mineral characterization of the Oum El Khacheb phosphorites (Gafsa-Metlaoui basin; S Tunisia) publication-title: Arab J Chem doi: 10.1016/j.arabjc.2014.10.007 – year: 2023 ident: CR18 article-title: Geochemical distribution and environmental assessment of potentially toxic elements in farmland soils, sediments, and tailings from phosphate industrial area (NE Algeria) publication-title: J Hazard Mater doi: 10.1016/j.jhazmat.2023.133110 – volume: 226 start-page: 9 year: 2010 end-page: 21 ident: CR58 article-title: Paleoceanographic constraints on Precambrian phosphorite accumulation, Baraga Group, Michigan, USA publication-title: Sediment Geol doi: 10.1016/j.sedgeo.2010.02.001 – ident: CR67 – volume: 114 start-page: 121 year: 2016 end-page: 127 ident: CR27 article-title: Elemental characterization of Hazm El-Jalamid phosphorite by instrumental neutron activation analysis publication-title: Appl Radiat Isot doi: 10.1016/j.apradiso.2016.05.012 – volume: 459 start-page: 1533 year: 2014 end-page: 1538 ident: CR14 article-title: The geochemical similarity of Oligocene and recent phosphorites from the Chiatura deposit (Georgia) and the Namibian shelf publication-title: Dokl Earth Sci doi: 10.1134/S1028334X14120022 – volume: 37 start-page: 180 year: 2019 end-page: 189 ident: CR54 article-title: Prediction of drained soil shear strength parameters of marine deposit from CPTu data using GMDH-type neural network publication-title: Mar Georesources Geotechnol doi: 10.1080/1064119X.2017.1415400 – volume: 12 start-page: 15706 year: 2015 end-page: 15715 ident: CR66 article-title: As (V) and P competitive sorption on soils, by-products and waste materials publication-title: Int J Environ Res Public Health doi: 10.3390/ijerph121215016 – volume: 216 start-page: 71 year: 2016 end-page: 79 ident: CR11 article-title: Arsenic (V) adsorption-desorption in agricultural and mine soils: effects of organic matter addition and phosphate competition publication-title: Environ Pollut doi: 10.1016/j.envpol.2016.05.054 – volume: 182 start-page: 232 year: 2010 end-page: 245 ident: CR24 article-title: Heavy elements in the phosphorite from Kalaat Khasba mine (North-western Tunisia): potential implications on the environment and human health publication-title: J Hazard Mater doi: 10.1016/j.jhazmat.2010.06.020 – volume: 131 start-page: 432 year: 2019 end-page: 441 ident: CR73 article-title: A novel comprehensive experimental study concerned synthesizes and prepare liquid paraffin-Fe3O4 mixture to develop models for both thermal conductivity & viscosity: a new approach of GMDH type of neural network publication-title: Int J Heat Mass Transf doi: 10.1016/j.ijheatmasstransfer.2018.11.069 – volume: 62 start-page: 478 year: 2018 end-page: 490 ident: CR51 article-title: GMDH-based hybrid model for container throughput forecasting: selective combination forecasting in nonlinear subseries publication-title: Appl Soft Comput doi: 10.1016/j.asoc.2017.10.033 – volume: 14 start-page: 2570 year: 2021 ident: CR82 article-title: Modeling of friction phenomena of Ti-6Al-4V sheets based on backward elimination regression and multi-layer artificial neural networks publication-title: Materials doi: 10.3390/ma14102570 – volume: 20 start-page: 276 year: 2019 end-page: 314 ident: CR16 article-title: Forward-backward selection with early dropping publication-title: J Mach Learn Res – volume: 7 start-page: 2949 year: 2021 end-page: 2960 ident: CR8 article-title: ML-based group method of data handling: an improvement on the conventional GMDH publication-title: Complex Intell Syst doi: 10.1007/s40747-021-00480-0 – volume: 182 year: 2019 ident: CR88 article-title: Origin of the Ediacaran Weng’an and Kaiyang phosphorite deposits in the Nanhua Basin publication-title: SW China J Asian Earth Sci doi: 10.1016/j.jseaes.2019.103931 – volume: 6 start-page: 88 year: 2016 ident: CR38 article-title: Marine phosphorites as potential resources for heavy rare earth elements and yttrium publication-title: Minerals doi: 10.3390/min6030088 – volume: 42 start-page: 1 issue: 1 year: 2016 end-page: 14 ident: CR68 article-title: Comparing stepwise regression models to the best-subsets models, or, the art of stepwise publication-title: Gen Linear Model J – volume: 24 year: 2021 ident: CR21 article-title: Distribution and ecological risk assessment of arsenic and some trace elements in soil of different land use types, Tianba Town, China publication-title: Environ Technol Innov doi: 10.1016/j.eti.2021.102041 – volume: 62 start-page: 44 year: 2018 end-page: 54 ident: CR43 article-title: Adaptive virtual metrology for semiconductor chemical mechanical planarization process using GMDH-type polynomial neural networks publication-title: J Process Control doi: 10.1016/j.jprocont.2017.12.004 – volume: 50 start-page: 885 year: 2007 end-page: 900 ident: CR55 article-title: Model evaluation guidelines for systematic quantification of accuracy in watershed simulations publication-title: Trans ASABE doi: 10.13031/2013.23153 – volume: 167 start-page: 151 year: 2012 end-page: 156 ident: CR76 article-title: Inhibition of microbial arsenate reduction by phosphate publication-title: Microbiol Res doi: 10.1016/j.micres.2011.05.007 – volume: 34 start-page: 793 year: 2019 end-page: 805 ident: CR3 article-title: Lithologic characterization of the phosphorite-bearing Duwi Formation (Campanian), South Esna, West Nile Valley publication-title: Egypt Carbonates Evaporites doi: 10.1007/s13146-018-0442-1 – volume: 9 start-page: 21 year: 1976 end-page: 30 ident: CR41 article-title: The group method of data handling in prediction problems publication-title: Sov Autom Control – volume: 40 year: 2020 ident: CR70 article-title: Performance improvement of empirical models for estimation of global solar radiation in India: A k-fold cross-validation approach publication-title: Sustain Energy Technol Assess doi: 10.1016/j.seta.2020.100768 – volume: 6 start-page: 116 year: 2020 end-page: 122 ident: CR81 article-title: F-test of overall significance in regression analysis simplified publication-title: J Pract Cardiovasc Sci doi: 10.4103/jpcs.jpcs_18_20 – volume: 8 start-page: 1 year: 2017 end-page: 17 ident: CR45 article-title: An asymmetric image encryption based on phase truncated hybrid transform publication-title: 3D Res doi: 10.1007/s13319-017-0137-8 – volume: 1 start-page: 140 year: 2020 end-page: 147 ident: CR49 article-title: A review on linear regression comprehensive in machine learning publication-title: J Appl Sci Technol Trends doi: 10.38094/jastt1457 – ident: CR91 – volume: 262 start-page: 68 year: 2009 end-page: 81 ident: CR12 article-title: Genesis of phosphorite crusts off Peru publication-title: Mar Geol doi: 10.1016/j.margeo.2009.03.006 – volume: 7 start-page: 1247 year: 2014 end-page: 1250 ident: CR20 article-title: Root mean square error (RMSE) or mean absolute error (MAE)?–Arguments against avoiding RMSE in the literature publication-title: Geosci Model Dev doi: 10.5194/gmd-7-1247-2014 – volume: 32 start-page: 2889 year: 2018 end-page: 2902 ident: CR63 article-title: Assessment of arsenic and heavy metal pollution and ecological risk in inshore sediments of the Yellow River estuary, China publication-title: Stoch Environ Res Risk Assess doi: 10.1007/s00477-018-1588-z – volume: 420 year: 2021 ident: CR78 article-title: Defects induced by Al substitution enhance As (V) adsorption on ferrihydrites publication-title: J Hazard Mater doi: 10.1016/j.jhazmat.2021.126544 – volume: 34 year: 2023 ident: CR9 article-title: Machine learning approach with various regression models for predicting the ultimate tensile strength of the friction stir welded AA 2050–T8 joints by the K-Fold cross-validation method publication-title: Mater Today Commun doi: 10.1016/j.mtcomm.2022.105286 – volume: 7 start-page: 238 year: 2021 end-page: 251 ident: CR26 article-title: Prediction of Disc Cutter Life During Shield Tunneling with AI via the Incorporation of a Genetic Algorithm into a GMDH-Type Neural Network publication-title: Engineering doi: 10.1016/j.eng.2020.02.016 – volume: 309 year: 2022 ident: CR84 article-title: Rethinking of the intraparticle diffusion adsorption kinetics model: interpretation, solving methods and applications publication-title: Chemosphere doi: 10.1016/j.chemosphere.2022.136732 – ident: CR89 – volume: 25 start-page: 14690 year: 2018 end-page: 14702 ident: CR25 article-title: Characterization of phosphate rock and phosphogypsum from Gabes phosphate fertilizer factories (SE Tunisia): high mining potential and implications for environmental protection publication-title: Environ Sci Pollut Res doi: 10.1007/s11356-018-1648-4 – volume: 185 year: 2022 ident: CR34 article-title: Geochemistry of red and cream phosphorites from the Şemikan phosphorite deposit, SE Turkey: Implication for phosphorite deposition conditions in the Upper Cretaceous publication-title: J Afr Earth Sci doi: 10.1016/j.jafrearsci.2021.104398 – volume: 255 year: 2020 ident: CR85 article-title: Activated dolomite phosphate rock fertilizers to reduce leaching of phosphorus and trace metals as compared to superphosphate publication-title: J Environ Manage doi: 10.1016/j.jenvman.2019.109872 – volume: 91 start-page: 94 year: 2009 end-page: 99 ident: CR50 article-title: Heavy metal pollution from phosphate rock used for the production of fertilizer in Pakistan publication-title: Microchem J doi: 10.1016/j.microc.2008.08.009 – volume: 79 start-page: 12777 year: 2020 end-page: 12815 ident: CR32 article-title: Dropout vs. batch normalization: an empirical study of their impact to deep learning publication-title: Multimed Tools Appl doi: 10.1007/s11042-019-08453-9 – ident: CR6 – volume: 2021 start-page: 1 year: 2021 end-page: 11 ident: CR37 article-title: An effective solution of the cube-root truly nonlinear oscillator: extended iteration procedure publication-title: Int J Differ Equ doi: 10.1155/2021/7819209 – ident: CR56 – volume: 6 start-page: 679 year: 2021 end-page: 697 ident: CR30 article-title: Implementation of machine learning for predicting maize crop yields using multiple linear regression and backward elimination publication-title: Malays J Comput MJoC doi: 10.24191/mjoc.v6i1.8822 – volume: 37 start-page: 369 year: 2021 end-page: 379 ident: CR52 article-title: A novel Harris hawks’ optimization and k-fold cross-validation predicting slope stability publication-title: Eng Comput doi: 10.1016/j.asoc.2017.10.033 – volume: 173 year: 2021 ident: CR28 article-title: Characterization and valorization of natural phosphate in removing of heavy metals and toxic organic species from water publication-title: J Afr Earth Sci doi: 10.1016/j.jafrearsci.2020.104022 – volume: 6 start-page: eabd4049 year: 2020 ident: CR87 article-title: Air pollution and COVID-19 mortality in the United States: strengths and limitations of an ecological regression analysis publication-title: Sci Adv doi: 10.1126/sciadv.abd4049 – volume: 376 start-page: 90 year: 2018 end-page: 112 ident: CR69 article-title: Diagenetic evolution of the upper Devonian phosphorites, Alborz Mountain Range, northern Iran publication-title: Sediment Geol doi: 10.1016/j.sedgeo.2018.08.001 – volume: 48 start-page: 13 year: 2002 end-page: 49 ident: CR60 article-title: Compositions of the apatite-group minerals: substitution mechanisms and controlling factors publication-title: Rev Min Geochem doi: 10.2138/rmg.2002.48.2 – ident: CR90 – volume: 21 start-page: 743 year: 2017 end-page: 752 ident: CR29 article-title: Assessment of heavy metals concentration in phosphate rock deposits, Hazara basin, Lesser Himalaya Pakistan publication-title: Geosci J doi: 10.1007/s12303-017-0013-9 – volume: 119 start-page: 285 year: 2019 end-page: 304 ident: CR19 article-title: A review of artificial neural network models for ambient air pollution prediction publication-title: Environ Model Softw doi: 10.1016/j.envsoft.2019.06.014 – volume: 132 start-page: 15 year: 2013 end-page: 25 ident: CR5 article-title: Geochemistry and origin of the Paleocene phosphorites from the Hazm Al-Jalamid area, northern Saudi Arabia publication-title: J Geochem Explor doi: 10.1016/j.gexplo.2013.04.001 – volume: 472 start-page: 226 year: 2017 end-page: 230 ident: CR13 article-title: Trace elements in phosphorites from Kotelny Island (New Siberian Islands) publication-title: Dokl Earth Sci doi: 10.1134/S1028334X17020222 – volume: 35 start-page: 233 year: 1999 end-page: 241 ident: CR46 article-title: Evaluating the use of “goodness-of-fit” Measures in hydrologic and hydroclimatic model validation publication-title: Water Resour Res doi: 10.1029/1998WR900018 – volume: 19 start-page: 1 year: 2018 end-page: 13 ident: CR79 article-title: Review of interactions between phosphorus and arsenic in soils from four case studies publication-title: Geochem Trans doi: 10.1186/s12932-018-0055-6 – volume: 112 start-page: 1329 year: 2004 end-page: 1333 ident: CR86 article-title: Water arsenic exposure and children’s intellectual function in Araihazar, Bangladesh publication-title: Environ Health Perspect doi: 10.1289/ehp.6964 – volume: 150 start-page: 701 year: 2019 end-page: 721 ident: CR7 article-title: Petrogenesis, provenance, and rare earth element geochemistry, southeast desert phosphorite, Jordan publication-title: J Afr Earth Sci doi: 10.1016/j.jafrearsci.2018.09.023 – volume: 265 year: 2020 ident: CR39 article-title: COVID-19 prevalence and fatality rates in association with air pollution emission concentrations and emission sources publication-title: Environ Pollut doi: 10.1016/j.envpol.2020.115126 – year: 2020 ident: CR62 article-title: Explicit equation derivation for predicting coal moisture content in convective drying process by GMDH-type neural network publication-title: Int J Coal Prep Util doi: 10.1080/19392699.2020.1774563 – year: 1980 ident: CR15 article-title: Marine phosphorites: geochemistry, occurrence publication-title: Genesis SEPM (society for Sedimentary Geology) doi: 10.2110/pec.80.29 – volume: 134 start-page: 704 year: 2017 end-page: 736 ident: CR33 article-title: Geochemistry and depositional environments of Paleocene-Eocene phosphorites: Metlaoui Group, Tunisia publication-title: J Afr Earth Sci doi: 10.1016/j.jafrearsci.2017.07.021 – volume: 153 start-page: 254 year: 2016 end-page: 261 ident: CR80 article-title: Arsenic mobilization from sediments in microcosms under sulfate reduction publication-title: Chemosphere doi: 10.1016/j.chemosphere.2016.02.117 – volume: 256 year: 2020 ident: CR48 article-title: Nanominerals assemblages and hazardous elements assessment in phosphogypsum from an abandoned phosphate fertilizer industry publication-title: Chemosphere doi: 10.1016/j.chemosphere.2020.127138 – volume: 5 start-page: 32 year: 2018 ident: CR77 article-title: Step away from stepwise publication-title: J Big Data doi: 10.1186/s40537-018-0143-6 – ident: CR83 – volume: 55 start-page: 4453 year: 2020 end-page: 4468 ident: CR4 article-title: Geochemistry and stable isotopes of the upper Campanian–lower Maastrichtian phosphorite-bearing sequence, Central Jordan: Implications for their age, origin, and diagenesis publication-title: Geol J doi: 10.1002/gj.3692 – volume: 7 year: 2021 ident: CR22 article-title: The coefficient of determination R-squared is more informative than SMAPE, MAE, MAPE, MSE and RMSE in regression analysis evaluation publication-title: PeerJ Comput Sci doi: 10.7717/peerj-cs.623 – volume: 2 start-page: 40 year: 2011 end-page: 50 ident: CR93 article-title: Construction and adjustment of differential polynomial neural network publication-title: J Eng Comput Innov doi: 10.5897/JECI.9000004 – volume: 449 start-page: 123 year: 2017 end-page: 134 ident: CR64 article-title: Siderite dissolution coupled to iron oxyhydroxide precipitation in the presence of arsenic revealed by nanoscale imaging publication-title: Chem Geol doi: 10.1016/j.chemgeo.2016.12.001 – start-page: 299 year: 2022 end-page: 327 ident: CR75 article-title: Regression analysis publication-title: Handbook of market research doi: 10.1007/978-3-319-57413-4_17 – year: 2021 ident: CR17 article-title: Trace metal elements in phosphate rock wastes from the Djebel Onk mining area (Tébessa, Eastern Algeria): a geochemical study and environmental implications publication-title: Appl Geochem doi: 10.1016/j.apgeochem.2021.104910 – volume: 182 year: 2019 ident: 5452_CR88 publication-title: SW China J Asian Earth Sci doi: 10.1016/j.jseaes.2019.103931 – year: 2023 ident: 5452_CR18 publication-title: J Hazard Mater doi: 10.1016/j.jhazmat.2023.133110 – volume: 40 year: 2020 ident: 5452_CR70 publication-title: Sustain Energy Technol Assess doi: 10.1016/j.seta.2020.100768 – volume: 37 start-page: 369 year: 2021 ident: 5452_CR52 publication-title: Eng Comput doi: 10.1016/j.asoc.2017.10.033 – year: 2020 ident: 5452_CR62 publication-title: Int J Coal Prep Util doi: 10.1080/19392699.2020.1774563 – volume: 7 start-page: 253 year: 2014 ident: 5452_CR2 publication-title: Arab J Geosci doi: 10.1007/s12517-013-0837-1 – volume: 185 year: 2022 ident: 5452_CR34 publication-title: J Afr Earth Sci doi: 10.1016/j.jafrearsci.2021.104398 – volume: 230 start-page: 23 year: 2019 ident: 5452_CR72 publication-title: Water Air Soil Pollut doi: 10.1007/s11270-018-4072-y – ident: 5452_CR56 doi: 10.1007/978-3-030-63270-0_30 – volume: 216 start-page: 71 year: 2016 ident: 5452_CR11 publication-title: Environ Pollut doi: 10.1016/j.envpol.2016.05.054 – volume: 79 start-page: 12777 year: 2020 ident: 5452_CR32 publication-title: Multimed Tools Appl doi: 10.1007/s11042-019-08453-9 – volume: 91 start-page: 94 year: 2009 ident: 5452_CR50 publication-title: Microchem J doi: 10.1016/j.microc.2008.08.009 – volume: 420 year: 2021 ident: 5452_CR78 publication-title: J Hazard Mater doi: 10.1016/j.jhazmat.2021.126544 – volume: 2021 start-page: 1 year: 2021 ident: 5452_CR37 publication-title: Int J Differ Equ doi: 10.1155/2021/7819209 – volume: 132 start-page: 15 year: 2013 ident: 5452_CR5 publication-title: J Geochem Explor doi: 10.1016/j.gexplo.2013.04.001 – volume: 20 start-page: 276 year: 2019 ident: 5452_CR16 publication-title: J Mach Learn Res – volume: 269 year: 2020 ident: 5452_CR92 publication-title: J Environ Manage doi: 10.1016/j.jenvman.2020.110797 – volume: 1 start-page: 140 year: 2020 ident: 5452_CR49 publication-title: J Appl Sci Technol Trends doi: 10.38094/jastt1457 – volume: 34 year: 2023 ident: 5452_CR9 publication-title: Mater Today Commun doi: 10.1016/j.mtcomm.2022.105286 – start-page: 299 volume-title: Handbook of market research year: 2022 ident: 5452_CR75 doi: 10.1007/978-3-319-57413-4_17 – volume: 5 start-page: 32 year: 2018 ident: 5452_CR77 publication-title: J Big Data doi: 10.1186/s40537-018-0143-6 – volume: 23 start-page: 382 year: 2020 ident: 5452_CR57 publication-title: Eng Sci Technol Int J doi: 10.1016/j.jestch.2019.05.013 – volume: 256 year: 2020 ident: 5452_CR48 publication-title: Chemosphere doi: 10.1016/j.chemosphere.2020.127138 – ident: 5452_CR91 doi: 10.1088/1742-6596/1168/2/022022 – volume: 34 start-page: 793 year: 2019 ident: 5452_CR3 publication-title: Egypt Carbonates Evaporites doi: 10.1007/s13146-018-0442-1 – volume: 7 start-page: 2949 year: 2021 ident: 5452_CR8 publication-title: Complex Intell Syst doi: 10.1007/s40747-021-00480-0 – volume: 134 start-page: 704 year: 2017 ident: 5452_CR33 publication-title: J Afr Earth Sci doi: 10.1016/j.jafrearsci.2017.07.021 – volume: 62 start-page: 44 year: 2018 ident: 5452_CR43 publication-title: J Process Control doi: 10.1016/j.jprocont.2017.12.004 – ident: 5452_CR90 doi: 10.1109/CSF.2018.00027 – volume: 309 year: 2022 ident: 5452_CR84 publication-title: Chemosphere doi: 10.1016/j.chemosphere.2022.136732 – volume: 21 start-page: 743 year: 2017 ident: 5452_CR29 publication-title: Geosci J doi: 10.1007/s12303-017-0013-9 – volume: 153 start-page: 254 year: 2016 ident: 5452_CR80 publication-title: Chemosphere doi: 10.1016/j.chemosphere.2016.02.117 – volume: 24 year: 2021 ident: 5452_CR21 publication-title: Environ Technol Innov doi: 10.1016/j.eti.2021.102041 – volume: 449 start-page: 123 year: 2017 ident: 5452_CR64 publication-title: Chem Geol doi: 10.1016/j.chemgeo.2016.12.001 – volume: 376 start-page: 90 year: 2018 ident: 5452_CR69 publication-title: Sediment Geol doi: 10.1016/j.sedgeo.2018.08.001 – volume: 19 start-page: 1 year: 2018 ident: 5452_CR79 publication-title: Geochem Trans doi: 10.1186/s12932-018-0055-6 – volume: 6 start-page: 207 year: 1970 ident: 5452_CR40 publication-title: Automatica doi: 10.1016/0005-1098(70)90092-0 – volume: 6 start-page: 679 year: 2021 ident: 5452_CR30 publication-title: Malays J Comput MJoC doi: 10.24191/mjoc.v6i1.8822 – volume: 14 start-page: 2570 year: 2021 ident: 5452_CR82 publication-title: Materials doi: 10.3390/ma14102570 – volume: 37 start-page: 180 year: 2019 ident: 5452_CR54 publication-title: Mar Georesources Geotechnol doi: 10.1080/1064119X.2017.1415400 – volume: 42 start-page: 1 issue: 1 year: 2016 ident: 5452_CR68 publication-title: Gen Linear Model J – volume: 167 start-page: 151 year: 2012 ident: 5452_CR76 publication-title: Microbiol Res doi: 10.1016/j.micres.2011.05.007 – volume: 40 start-page: 400 year: 2012 ident: 5452_CR61 publication-title: Energy doi: 10.1016/j.energy.2012.01.037 – volume: 6 start-page: 116 year: 2020 ident: 5452_CR81 publication-title: J Pract Cardiovasc Sci doi: 10.4103/jpcs.jpcs_18_20 – volume: 265 year: 2020 ident: 5452_CR39 publication-title: Environ Pollut doi: 10.1016/j.envpol.2020.115126 – volume: 255 year: 2020 ident: 5452_CR85 publication-title: J Environ Manage doi: 10.1016/j.jenvman.2019.109872 – volume: 459 start-page: 1533 year: 2014 ident: 5452_CR14 publication-title: Dokl Earth Sci doi: 10.1134/S1028334X14120022 – volume: 8 year: 2020 ident: 5452_CR23 publication-title: Fam Med Commun Health doi: 10.1136/fmch-2019-000262 – volume: 112 start-page: 1329 year: 2004 ident: 5452_CR86 publication-title: Environ Health Perspect doi: 10.1289/ehp.6964 – ident: 5452_CR89 doi: 10.1007/978-3-319-70581-1_42 – year: 2021 ident: 5452_CR17 publication-title: Appl Geochem doi: 10.1016/j.apgeochem.2021.104910 – volume: 150 start-page: 701 year: 2019 ident: 5452_CR7 publication-title: J Afr Earth Sci doi: 10.1016/j.jafrearsci.2018.09.023 – volume: 25 start-page: 14690 year: 2018 ident: 5452_CR25 publication-title: Environ Sci Pollut Res doi: 10.1007/s11356-018-1648-4 – volume: 50 start-page: 885 year: 2007 ident: 5452_CR55 publication-title: Trans ASABE doi: 10.13031/2013.23153 – volume: 4 start-page: 177 year: 2022 ident: 5452_CR44 publication-title: Jambura J Math doi: 10.34312/jjom.v4i2.13529 – volume: 134 year: 2022 ident: 5452_CR36 publication-title: Int Commun Heat Mass Transf doi: 10.1016/j.icheatmasstransfer.2022.106006 – volume: 2 start-page: 40 year: 2011 ident: 5452_CR93 publication-title: J Eng Comput Innov doi: 10.5897/JECI.9000004 – volume: 12 start-page: 15706 year: 2015 ident: 5452_CR66 publication-title: Int J Environ Res Public Health doi: 10.3390/ijerph121215016 – volume: 17 start-page: 346 year: 2016 ident: 5452_CR35 publication-title: Geochem Geophys Geosystems doi: 10.1002/2015GC005861 – volume: 55 start-page: 4453 year: 2020 ident: 5452_CR4 publication-title: Geol J doi: 10.1002/gj.3692 – volume: 48 start-page: 13 year: 2002 ident: 5452_CR60 publication-title: Rev Min Geochem doi: 10.2138/rmg.2002.48.2 – volume: 173 year: 2021 ident: 5452_CR28 publication-title: J Afr Earth Sci doi: 10.1016/j.jafrearsci.2020.104022 – volume: 7 year: 2021 ident: 5452_CR22 publication-title: PeerJ Comput Sci doi: 10.7717/peerj-cs.623 – volume: 35 start-page: 233 year: 1999 ident: 5452_CR46 publication-title: Water Resour Res doi: 10.1029/1998WR900018 – volume: 32 start-page: 2889 year: 2018 ident: 5452_CR63 publication-title: Stoch Environ Res Risk Assess doi: 10.1007/s00477-018-1588-z – volume: 6 start-page: eabd4049 year: 2020 ident: 5452_CR87 publication-title: Sci Adv doi: 10.1126/sciadv.abd4049 – volume: 34 start-page: 17289 year: 2022 ident: 5452_CR65 publication-title: Neural Comput Appl doi: 10.1007/s00521-022-07382-3 – volume: 255 start-page: 52 year: 2002 ident: 5452_CR47 publication-title: J Colloid Interface Sci doi: 10.1006/jcis.2002.8646 – volume: 114 start-page: 121 year: 2016 ident: 5452_CR27 publication-title: Appl Radiat Isot doi: 10.1016/j.apradiso.2016.05.012 – volume: 9 start-page: 21 year: 1976 ident: 5452_CR41 publication-title: Sov Autom Control – ident: 5452_CR83 doi: 10.1088/1757-899X/324/1/012049 – volume: 8 start-page: 1 year: 2017 ident: 5452_CR45 publication-title: 3D Res doi: 10.1007/s13319-017-0137-8 – volume: 182 start-page: 232 year: 2010 ident: 5452_CR24 publication-title: J Hazard Mater doi: 10.1016/j.jhazmat.2010.06.020 – volume: 7 start-page: 1247 year: 2014 ident: 5452_CR20 publication-title: Geosci Model Dev doi: 10.5194/gmd-7-1247-2014 – volume: 6 start-page: 88 year: 2016 ident: 5452_CR38 publication-title: Minerals doi: 10.3390/min6030088 – volume: 77 start-page: 31 year: 2013 ident: 5452_CR1 publication-title: J Afr Earth Sci doi: 10.1016/j.jafrearsci.2012.09.009 – volume: 131 start-page: 432 year: 2019 ident: 5452_CR73 publication-title: Int J Heat Mass Transf doi: 10.1016/j.ijheatmasstransfer.2018.11.069 – volume: 410 start-page: 53 year: 2015 ident: 5452_CR10 publication-title: Chem Geol doi: 10.1016/j.chemgeo.2015.06.011 – year: 1980 ident: 5452_CR15 publication-title: Genesis SEPM (society for Sedimentary Geology) doi: 10.2110/pec.80.29 – ident: 5452_CR71 doi: 10.1016/B978-0-12-823818-9.00013-4 – volume: 62 start-page: 478 year: 2018 ident: 5452_CR51 publication-title: Appl Soft Comput doi: 10.1016/j.asoc.2017.10.033 – volume: 472 start-page: 226 year: 2017 ident: 5452_CR13 publication-title: Dokl Earth Sci doi: 10.1134/S1028334X17020222 – volume: 12 start-page: 1607 year: 2019 ident: 5452_CR31 publication-title: Arab J Chem doi: 10.1016/j.arabjc.2014.10.007 – ident: 5452_CR67 doi: 10.1007/9789463510868_011 – volume: 262 start-page: 68 year: 2009 ident: 5452_CR12 publication-title: Mar Geol doi: 10.1016/j.margeo.2009.03.006 – volume: 7 start-page: 238 year: 2021 ident: 5452_CR26 publication-title: Engineering doi: 10.1016/j.eng.2020.02.016 – year: 2020 ident: 5452_CR59 publication-title: J Pet Sci Eng doi: 10.1016/j.petrol.2020.108182 – volume: 119 start-page: 285 year: 2019 ident: 5452_CR19 publication-title: Environ Model Softw doi: 10.1016/j.envsoft.2019.06.014 – volume: 24 start-page: 426 year: 2007 ident: 5452_CR53 publication-title: Korean J Chem Eng doi: 10.1007/s11814-007-0073-z – volume: 226 start-page: 9 year: 2010 ident: 5452_CR58 publication-title: Sediment Geol doi: 10.1016/j.sedgeo.2010.02.001 – ident: 5452_CR6 doi: 10.1016/j.jafrearsci.2020.103826 – volume: 97 year: 2020 ident: 5452_CR74 publication-title: Appl Soft Comput doi: 10.1016/j.asoc.2019.105524 – ident: 5452_CR42 doi: 10.1109/TSMC.1971.4308320
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Snippet	Marine sedimentary phosphate rock is the primary source for manufacturing phosphate fertilizers. It is composed mainly of phosphorus and other elements. Some...
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SubjectTerms	algorithms Aquatic Pollution arsenic calcium oxide carcinogens data collection Earth and Environmental Science Ecotoxicology Environment Environmental Chemistry Environmental Science and Engineering equations heavy metals humans neurons Original Paper phosphorus prediction regression analysis rock phosphate Soil Science & Conservation Waste Water Technology Water Management Water Pollution Control
Title	Multiple regression and group method of data handling-based models for predicting arsenic concentration in sedimentary phosphate rock
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