Strong convergence of a modified extragradient algorithm to solve pseudomonotone equilibrium and application to classification of diabetes mellitus
This work studies pseudomonotone equilibrium problems. The modified inertial viscosity subgradient extragradient is proposed for obtaining strong convergence, and it is proved under the assumption that the bifunction satisfies the Lipchitz-type condition. Flexible use of different stepsize parameter...
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| Published in: | Chaos, solitons and fractals Vol. 168; p. 113108 |
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| Format: | Journal Article |
| Language: | English |
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01.03.2023
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| ISSN: | 0960-0779 |
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| Abstract | This work studies pseudomonotone equilibrium problems. The modified inertial viscosity subgradient extragradient is proposed for obtaining strong convergence, and it is proved under the assumption that the bifunction satisfies the Lipchitz-type condition. Flexible use of different stepsize parameters is offered. Moreover, the proposed algorithm is applied to solve diabetes mellitus classification problems. The algorithm’s efficiency is shown by comparing with many existing methods with 80.3% high accuracy. The training-validation loss and accuracy plots are presented to consider our good model fitting.
•The paper proposed an algorithm for solving pseudomonotone equilibrium problems.•The strong convergence result has been established subject to certain conditions.•Predict diabetes mellitus through the proposed algorithm by ELM.•The algorithm’s effectiveness is up to 80.3% accuracy. |
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| AbstractList | This work studies pseudomonotone equilibrium problems. The modified inertial viscosity subgradient extragradient is proposed for obtaining strong convergence, and it is proved under the assumption that the bifunction satisfies the Lipchitz-type condition. Flexible use of different stepsize parameters is offered. Moreover, the proposed algorithm is applied to solve diabetes mellitus classification problems. The algorithm’s efficiency is shown by comparing with many existing methods with 80.3% high accuracy. The training-validation loss and accuracy plots are presented to consider our good model fitting.
•The paper proposed an algorithm for solving pseudomonotone equilibrium problems.•The strong convergence result has been established subject to certain conditions.•Predict diabetes mellitus through the proposed algorithm by ELM.•The algorithm’s effectiveness is up to 80.3% accuracy. |
| ArticleNumber | 113108 |
| Author | Suparatulatorn, Raweerote Cholamjiak, Watcharaporn |
| Author_xml | – sequence: 1 givenname: Watcharaporn orcidid: 0000-0002-8563-017X surname: Cholamjiak fullname: Cholamjiak, Watcharaporn email: watcharaporn.ch@up.ac.th organization: School of Science, University of Phayao, Phayao 56000, Thailand – sequence: 2 givenname: Raweerote orcidid: 0000-0003-0790-3811 surname: Suparatulatorn fullname: Suparatulatorn, Raweerote email: raweerote.s@gmail.com organization: Department of Mathematics, Faculty of Science, Chiang Mai University, Chiang Mai 50200, Thailand |
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| Cites_doi | 10.1007/s10957-013-0494-2 10.1007/s13398-016-0328-9 10.1016/j.csda.2004.02.006 10.1016/0041-5553(64)90137-5 10.1016/j.jksuci.2020.01.010 10.37193/CJM.2021.03.15 10.1007/s11228-008-0102-z 10.1111/j.2517-6161.1996.tb02080.x 10.1080/02331930601122876 10.1016/S0925-2312(02)00599-4 10.22436/jmcs.024.04.03 10.1109/BIBE.2014.27 10.1007/s10559-014-9614-8 10.1007/s12652-020-02242-1 10.1016/0362-546X(92)90159-C 10.1007/s10957-010-9757-3 10.1007/11536444_35 10.3906/elk-1209-82 10.1137/14097238X 10.1112/S0024610702003332 10.1007/s11075-011-9490-5 |
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| Keywords | 65K15 Strong convergence Data classification problem 49M37 Subgradient extragradient algorithm 47H05 Pseudomonotone equilibrium problem |
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| References | Saxena, Sharma, Gupta, Sampada (b31) 2022 Korpelevich (b8) 1976; 12 Tran, Dung, Nguyen (b7) 2008; 57 Deng, Kasabov (b27) 2003; 51 Quinlan (b29) 2014 Muangchoo (b15) 2022; 24 Shehu, Izuchukwu, Yao, Qin (b17) 2021 Rockafellar (b18) 1970 Malitsky, Semenov (b12) 2014; 50 Zhao, Yao, Yao (b6) 2022; 6 Malitsky (b11) 2015; 25 Xu (b19) 2002; 66 Blum (b2) 1994; 63 Chatrati, Hossain, Goyal (b25) 2020; 34 Polyak (b16) 1964; 4 Dadashi, Iyiola, Shehu (b21) 2019 Blum, Oettli (b3) 1994; 63 Choubey, Kumar, Shukla, Tripathi, Dhandhania (b26) 2020; 16 Muu, Oettli (b1) 1992; 18 Yao, Shahzad, Yao (b5) 2021; 37 Selvi, Muthulakshmi (b33) 2021; 12 Maingé (b20) 2008; 16 Li L. Diagnosis of diabetes using a weight- adjusted voting approach. In: Proceedings of the IEEE international conference bioinformatics bioengineering. Boca Raton, FL, USA; 2014, p. 320–4. Thomas, Pradhan, Dhaka (b35) 2020 Tibshirani (b34) 1996; 58 Censor, Gibali, Reich (b10) 2011; 148 Van Hieu (b14) 2017; 111 Censor, Gibali, Reich (b9) 2012; 59 Kraikaew, Saejung (b13) 2014; 163 Sahan SS, Polat K, Kodaz H, Gunes S. The Medical applications of attribute weighted artificial immune system (AWAIS): Diagnosis of heart and diabetes diseas. In: Proceedings of the artificial immune systems: 4th international conference. Banff, Alberta, Canada; 2005, p. 456–68. Bozkurt, Yurtay, Yilmaz, Setkaya (b23) 2014; 22 Tan, Cho (b4) 2021 Kumari, Chitra (b22) 2013; 3 Brahim-Belhouari, Bermak (b24) 2004; 47 Smith JW, Everhart JE, Dickson WC, Knowler WC, Johannes RS. Using the ADAP learning algorithm to forecast the onset of diabetes mellitus. In: Proceedings of the annual symposium on computer applications in medical care. Baltimore, Maryland; 1988, p. 261. Maingé (10.1016/j.chaos.2023.113108_b20) 2008; 16 Van Hieu (10.1016/j.chaos.2023.113108_b14) 2017; 111 Kumari (10.1016/j.chaos.2023.113108_b22) 2013; 3 Quinlan (10.1016/j.chaos.2023.113108_b29) 2014 Chatrati (10.1016/j.chaos.2023.113108_b25) 2020; 34 Kraikaew (10.1016/j.chaos.2023.113108_b13) 2014; 163 Polyak (10.1016/j.chaos.2023.113108_b16) 1964; 4 Xu (10.1016/j.chaos.2023.113108_b19) 2002; 66 Tibshirani (10.1016/j.chaos.2023.113108_b34) 1996; 58 Blum (10.1016/j.chaos.2023.113108_b2) 1994; 63 Yao (10.1016/j.chaos.2023.113108_b5) 2021; 37 10.1016/j.chaos.2023.113108_b28 Tran (10.1016/j.chaos.2023.113108_b7) 2008; 57 Malitsky (10.1016/j.chaos.2023.113108_b12) 2014; 50 Saxena (10.1016/j.chaos.2023.113108_b31) 2022 Deng (10.1016/j.chaos.2023.113108_b27) 2003; 51 Muu (10.1016/j.chaos.2023.113108_b1) 1992; 18 Tan (10.1016/j.chaos.2023.113108_b4) 2021 Dadashi (10.1016/j.chaos.2023.113108_b21) 2019 Brahim-Belhouari (10.1016/j.chaos.2023.113108_b24) 2004; 47 Blum (10.1016/j.chaos.2023.113108_b3) 1994; 63 10.1016/j.chaos.2023.113108_b30 Choubey (10.1016/j.chaos.2023.113108_b26) 2020; 16 10.1016/j.chaos.2023.113108_b32 Zhao (10.1016/j.chaos.2023.113108_b6) 2022; 6 Thomas (10.1016/j.chaos.2023.113108_b35) 2020 Censor (10.1016/j.chaos.2023.113108_b10) 2011; 148 Shehu (10.1016/j.chaos.2023.113108_b17) 2021 Censor (10.1016/j.chaos.2023.113108_b9) 2012; 59 Muangchoo (10.1016/j.chaos.2023.113108_b15) 2022; 24 Selvi (10.1016/j.chaos.2023.113108_b33) 2021; 12 Malitsky (10.1016/j.chaos.2023.113108_b11) 2015; 25 Rockafellar (10.1016/j.chaos.2023.113108_b18) 1970 Bozkurt (10.1016/j.chaos.2023.113108_b23) 2014; 22 Korpelevich (10.1016/j.chaos.2023.113108_b8) 1976; 12 |
| References_xml | – volume: 50 start-page: 125 year: 2014 end-page: 131 ident: b12 article-title: An extragradient algorithm for monotone variational inequalities publication-title: Cybernet Systems Anal – start-page: 1 year: 2021 end-page: 29 ident: b17 article-title: Strongly convergent inertial extragradient type methods for equilibrium problems publication-title: Appl Anal – start-page: 192 year: 2020 end-page: 196 ident: b35 article-title: Comparative analysis to predict breast cancer using machine learning algorithms: A survey publication-title: 2020 international conference on inventive computation technologies – year: 2019 ident: b21 article-title: The subgradient extragradient method for pseudomonotone equilibrium problems publication-title: Optimization – reference: Smith JW, Everhart JE, Dickson WC, Knowler WC, Johannes RS. Using the ADAP learning algorithm to forecast the onset of diabetes mellitus. In: Proceedings of the annual symposium on computer applications in medical care. Baltimore, Maryland; 1988, p. 261. – volume: 25 start-page: 502 year: 2015 end-page: 520 ident: b11 article-title: Projected reflected gradient methods for monotone variational inequalities publication-title: SIAM J Optim – volume: 3 start-page: 1797 year: 2013 end-page: 1801 ident: b22 article-title: Classification of diabetes disease using support vector machine publication-title: Int J Eng Res Afr – volume: 47 start-page: 705 year: 2004 end-page: 712 ident: b24 article-title: Gaussian process for nonstationary time series prediction publication-title: Comput Stat Data Anal – year: 2021 ident: b4 article-title: Strong convergence of inertial forward–backward methods for solving monotone inclusions publication-title: Appl Anal – volume: 57 start-page: 749 year: 2008 end-page: 776 ident: b7 article-title: Extragradient algorithms extended to equilibrium problems publication-title: Optimization – volume: 22 start-page: 1044 year: 2014 end-page: 1055 ident: b23 article-title: Comparison of different methodologies for determining diabetes publication-title: Turk J Electr Eng Comput Sci – volume: 59 start-page: 301 year: 2012 end-page: 323 ident: b9 article-title: Algorithms for the split variational inequality problem publication-title: Numer Algorithms – volume: 58 start-page: 267 year: 1996 end-page: 288 ident: b34 article-title: Regression shrinkage and selection via the lasso publication-title: J R Stat Soc Ser B Stat Methodol – volume: 63 start-page: 123 year: 1994 end-page: 145 ident: b3 article-title: From optimization and variational inequalities to equilibrium problems publication-title: Math Program – volume: 63 start-page: 123 year: 1994 end-page: 145 ident: b2 article-title: From optimization and variational inequalities to equilibrium problems publication-title: Math Stud – volume: 24 start-page: 308 year: 2022 end-page: 322 ident: b15 article-title: A new strongly convergent algorithm to solve pseudomonotone equilibrium problems in a real Hilbert space publication-title: J Math Computer Sci – volume: 4 start-page: 1 year: 1964 end-page: 17 ident: b16 article-title: Some methods of speeding up the convergence of iteration methods publication-title: USSR Comput Math Math Phys – volume: 37 start-page: 541 year: 2021 end-page: 550 ident: b5 article-title: Convergence of tseng-type self-adaptive algorithms for variational inequalities and fixed point problems publication-title: Carpathian J Math – volume: 12 start-page: 747 year: 1976 end-page: 756 ident: b8 article-title: The extragradient method for finding saddle points and other problems publication-title: Matecon – volume: 34 start-page: 862 year: 2020 end-page: 870 ident: b25 article-title: Smart home health monitoring system for predicting type 2 diabetes and hypertension publication-title: J King Saud Univ, Comput Inf Sci – start-page: 11 pages year: 2022 ident: b31 article-title: A novel approach for feature selection and classification of diabetes mellitus: Machine learning methods publication-title: Comput Intell Neurosci – volume: 66 start-page: 240 year: 2002 end-page: 256 ident: b19 article-title: Iterative algorithms for nonlinear operators publication-title: J Lond Math Soc – volume: 148 start-page: 318 year: 2011 end-page: 335 ident: b10 article-title: The subgradient extragradient method for solving variational inequalities in Hilbert space publication-title: J Optim Theory Appl – volume: 163 start-page: 399 year: 2014 end-page: 412 ident: b13 article-title: Strong convergence of the Halpern subgradient extragradient method for solving variational inequalities in Hilbert spaces publication-title: J Optim Theory Appl – volume: 111 start-page: 823 year: 2017 end-page: 840 ident: b14 article-title: Halpern subgradient extragradient method extended to equilibrium problems publication-title: Rev R Acad Cienc Exactas Fis Nat Ser A Mat – reference: Sahan SS, Polat K, Kodaz H, Gunes S. The Medical applications of attribute weighted artificial immune system (AWAIS): Diagnosis of heart and diabetes diseas. In: Proceedings of the artificial immune systems: 4th international conference. Banff, Alberta, Canada; 2005, p. 456–68. – volume: 16 start-page: 833 year: 2020 end-page: 850 ident: b26 article-title: Comparative analysis of classification methods with PCA and LDA for diabetes publication-title: Current Diabetes Rev – reference: Li L. Diagnosis of diabetes using a weight- adjusted voting approach. In: Proceedings of the IEEE international conference bioinformatics bioengineering. Boca Raton, FL, USA; 2014, p. 320–4. – volume: 51 start-page: 87 year: 2003 end-page: 103 ident: b27 article-title: On-line pattern analysis by evolving self-organizing maps publication-title: Neurocomputing – year: 2014 ident: b29 article-title: Programs for machine learning – volume: 6 start-page: 693 year: 2022 end-page: 706 ident: b6 article-title: A nonmonotone gradient method for constrained multiobjective optimization problems publication-title: J Nonlinear Var Anal – volume: 16 start-page: 899 year: 2008 end-page: 912 ident: b20 article-title: Strong convergence of projected subgradient methods for nonsmooth and nonstrictly convex minimization publication-title: Set-Valued Anal – volume: 18 start-page: 1159 year: 1992 end-page: 1166 ident: b1 article-title: Convergence of an adaptive penalty scheme for finding constrained equilibria publication-title: Nonlinear Anal Theory Methods Appl – year: 1970 ident: b18 article-title: Convex analysis – volume: 12 start-page: 1717 year: 2021 end-page: 1730 ident: b33 article-title: Modelling the map reduce based optimal gradient boosted tree classification algorithm for diabetes mellitus diagnosis system publication-title: J Ambient Intell Humaniz Comput – volume: 163 start-page: 399 issue: 2 year: 2014 ident: 10.1016/j.chaos.2023.113108_b13 article-title: Strong convergence of the Halpern subgradient extragradient method for solving variational inequalities in Hilbert spaces publication-title: J Optim Theory Appl doi: 10.1007/s10957-013-0494-2 – volume: 111 start-page: 823 issue: 3 year: 2017 ident: 10.1016/j.chaos.2023.113108_b14 article-title: Halpern subgradient extragradient method extended to equilibrium problems publication-title: Rev R Acad Cienc Exactas Fis Nat Ser A Mat doi: 10.1007/s13398-016-0328-9 – start-page: 11 pages year: 2022 ident: 10.1016/j.chaos.2023.113108_b31 article-title: A novel approach for feature selection and classification of diabetes mellitus: Machine learning methods publication-title: Comput Intell Neurosci – volume: 47 start-page: 705 year: 2004 ident: 10.1016/j.chaos.2023.113108_b24 article-title: Gaussian process for nonstationary time series prediction publication-title: Comput Stat Data Anal doi: 10.1016/j.csda.2004.02.006 – volume: 63 start-page: 123 year: 1994 ident: 10.1016/j.chaos.2023.113108_b3 article-title: From optimization and variational inequalities to equilibrium problems publication-title: Math Program – volume: 4 start-page: 1 issue: 5 year: 1964 ident: 10.1016/j.chaos.2023.113108_b16 article-title: Some methods of speeding up the convergence of iteration methods publication-title: USSR Comput Math Math Phys doi: 10.1016/0041-5553(64)90137-5 – volume: 34 start-page: 862 issue: 3 year: 2020 ident: 10.1016/j.chaos.2023.113108_b25 article-title: Smart home health monitoring system for predicting type 2 diabetes and hypertension publication-title: J King Saud Univ, Comput Inf Sci doi: 10.1016/j.jksuci.2020.01.010 – volume: 37 start-page: 541 year: 2021 ident: 10.1016/j.chaos.2023.113108_b5 article-title: Convergence of tseng-type self-adaptive algorithms for variational inequalities and fixed point problems publication-title: Carpathian J Math doi: 10.37193/CJM.2021.03.15 – volume: 6 start-page: 693 issue: 6 year: 2022 ident: 10.1016/j.chaos.2023.113108_b6 article-title: A nonmonotone gradient method for constrained multiobjective optimization problems publication-title: J Nonlinear Var Anal – start-page: 192 year: 2020 ident: 10.1016/j.chaos.2023.113108_b35 article-title: Comparative analysis to predict breast cancer using machine learning algorithms: A survey – year: 2021 ident: 10.1016/j.chaos.2023.113108_b4 article-title: Strong convergence of inertial forward–backward methods for solving monotone inclusions publication-title: Appl Anal – volume: 16 start-page: 899 issue: 7–8 year: 2008 ident: 10.1016/j.chaos.2023.113108_b20 article-title: Strong convergence of projected subgradient methods for nonsmooth and nonstrictly convex minimization publication-title: Set-Valued Anal doi: 10.1007/s11228-008-0102-z – volume: 58 start-page: 267 year: 1996 ident: 10.1016/j.chaos.2023.113108_b34 article-title: Regression shrinkage and selection via the lasso publication-title: J R Stat Soc Ser B Stat Methodol doi: 10.1111/j.2517-6161.1996.tb02080.x – volume: 57 start-page: 749 issue: 6 year: 2008 ident: 10.1016/j.chaos.2023.113108_b7 article-title: Extragradient algorithms extended to equilibrium problems publication-title: Optimization doi: 10.1080/02331930601122876 – volume: 51 start-page: 87 year: 2003 ident: 10.1016/j.chaos.2023.113108_b27 article-title: On-line pattern analysis by evolving self-organizing maps publication-title: Neurocomputing doi: 10.1016/S0925-2312(02)00599-4 – volume: 16 start-page: 833 issue: 8 year: 2020 ident: 10.1016/j.chaos.2023.113108_b26 article-title: Comparative analysis of classification methods with PCA and LDA for diabetes publication-title: Current Diabetes Rev – year: 2014 ident: 10.1016/j.chaos.2023.113108_b29 – volume: 12 start-page: 747 year: 1976 ident: 10.1016/j.chaos.2023.113108_b8 article-title: The extragradient method for finding saddle points and other problems publication-title: Matecon – volume: 24 start-page: 308 year: 2022 ident: 10.1016/j.chaos.2023.113108_b15 article-title: A new strongly convergent algorithm to solve pseudomonotone equilibrium problems in a real Hilbert space publication-title: J Math Computer Sci doi: 10.22436/jmcs.024.04.03 – ident: 10.1016/j.chaos.2023.113108_b28 doi: 10.1109/BIBE.2014.27 – volume: 50 start-page: 125 issue: 2 year: 2014 ident: 10.1016/j.chaos.2023.113108_b12 article-title: An extragradient algorithm for monotone variational inequalities publication-title: Cybernet Systems Anal doi: 10.1007/s10559-014-9614-8 – volume: 12 start-page: 1717 issue: 2 year: 2021 ident: 10.1016/j.chaos.2023.113108_b33 article-title: Modelling the map reduce based optimal gradient boosted tree classification algorithm for diabetes mellitus diagnosis system publication-title: J Ambient Intell Humaniz Comput doi: 10.1007/s12652-020-02242-1 – volume: 3 start-page: 1797 issue: 2 year: 2013 ident: 10.1016/j.chaos.2023.113108_b22 article-title: Classification of diabetes disease using support vector machine publication-title: Int J Eng Res Afr – year: 1970 ident: 10.1016/j.chaos.2023.113108_b18 – ident: 10.1016/j.chaos.2023.113108_b32 – volume: 18 start-page: 1159 issue: 12 year: 1992 ident: 10.1016/j.chaos.2023.113108_b1 article-title: Convergence of an adaptive penalty scheme for finding constrained equilibria publication-title: Nonlinear Anal Theory Methods Appl doi: 10.1016/0362-546X(92)90159-C – volume: 148 start-page: 318 issue: 2 year: 2011 ident: 10.1016/j.chaos.2023.113108_b10 article-title: The subgradient extragradient method for solving variational inequalities in Hilbert space publication-title: J Optim Theory Appl doi: 10.1007/s10957-010-9757-3 – ident: 10.1016/j.chaos.2023.113108_b30 doi: 10.1007/11536444_35 – year: 2019 ident: 10.1016/j.chaos.2023.113108_b21 article-title: The subgradient extragradient method for pseudomonotone equilibrium problems publication-title: Optimization – volume: 22 start-page: 1044 issue: 4 year: 2014 ident: 10.1016/j.chaos.2023.113108_b23 article-title: Comparison of different methodologies for determining diabetes publication-title: Turk J Electr Eng Comput Sci doi: 10.3906/elk-1209-82 – volume: 63 start-page: 123 year: 1994 ident: 10.1016/j.chaos.2023.113108_b2 article-title: From optimization and variational inequalities to equilibrium problems publication-title: Math Stud – volume: 25 start-page: 502 issue: 1 year: 2015 ident: 10.1016/j.chaos.2023.113108_b11 article-title: Projected reflected gradient methods for monotone variational inequalities publication-title: SIAM J Optim doi: 10.1137/14097238X – start-page: 1 year: 2021 ident: 10.1016/j.chaos.2023.113108_b17 article-title: Strongly convergent inertial extragradient type methods for equilibrium problems publication-title: Appl Anal – volume: 66 start-page: 240 issue: 1 year: 2002 ident: 10.1016/j.chaos.2023.113108_b19 article-title: Iterative algorithms for nonlinear operators publication-title: J Lond Math Soc doi: 10.1112/S0024610702003332 – volume: 59 start-page: 301 year: 2012 ident: 10.1016/j.chaos.2023.113108_b9 article-title: Algorithms for the split variational inequality problem publication-title: Numer Algorithms doi: 10.1007/s11075-011-9490-5 |
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| Snippet | This work studies pseudomonotone equilibrium problems. The modified inertial viscosity subgradient extragradient is proposed for obtaining strong convergence,... |
| SourceID | crossref elsevier |
| SourceType | Enrichment Source Index Database Publisher |
| StartPage | 113108 |
| SubjectTerms | Data classification problem Pseudomonotone equilibrium problem Strong convergence Subgradient extragradient algorithm |
| Title | Strong convergence of a modified extragradient algorithm to solve pseudomonotone equilibrium and application to classification of diabetes mellitus |
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