Some algorithms for classes of split feasibility problems involving paramonotone equilibria and convex optimization View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-12

AUTHORS

Q. L. Dong, X. H. Li, D. Kitkuan, Y. J. Cho, P. Kumam

ABSTRACT

In this paper, we first introduce a new algorithm which involves projecting each iteration to solve a split feasibility problem with paramonotone equilibria and using unconstrained convex optimization. The strong convergence of the proposed algorithm is presented. Second, we also revisit this split feasibility problem and replace the unconstrained convex optimization by a constrained convex optimization. We introduce some algorithms for two different types of objective function of the constrained convex optimization and prove some strong convergence results of the proposed algorithms. Third, we apply our algorithms for finding an equilibrium point with minimal environmental cost for a model in electricity production. Finally, we give some numerical results to illustrate the effectiveness and advantages of the proposed algorithms. More... »

PAGES

77

References to SciGraph publications

  • 2011-08. Averaged Mappings and the Gradient-Projection Algorithm in JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS
  • 2012-03. Iterative methods for solving monotone equilibrium problems via dual gap functions in COMPUTATIONAL OPTIMIZATION AND APPLICATIONS
  • 2013-12. Strong convergence of a self-adaptive method for the split feasibility problem in FIXED POINT THEORY AND APPLICATIONS
  • 2018-01. Modified inertial Mann algorithm and inertial CQ-algorithm for nonexpansive mappings in OPTIMIZATION LETTERS
  • 2018-03. Inertial projection and contraction algorithms for variational inequalities in JOURNAL OF GLOBAL OPTIMIZATION
  • 2018-03. Iterative algorithms for solving the split feasibility problem in Hilbert spaces in JOURNAL OF FIXED POINT THEORY AND APPLICATIONS
  • 2014-10. Solving proximal split feasibility problems without prior knowledge of operator norms in OPTIMIZATION LETTERS
  • 2012-02. Algorithms for the Split Variational Inequality Problem in NUMERICAL ALGORITHMS
  • 2019-02. Selective projection methods for solving a class of variational inequalities in NUMERICAL ALGORITHMS
  • 2016-12. An algorithm for a class of split feasibility problems: application to a model in electricity production in MATHEMATICAL METHODS OF OPERATIONS RESEARCH
  • 1994-09. A multiprojection algorithm using Bregman projections in a product space in NUMERICAL ALGORITHMS
  • 2018-06. “Optimal” choice of the step length of the projection and contraction methods for solving the split feasibility problem in JOURNAL OF GLOBAL OPTIMIZATION
  • 2014-03. Weak convergence theorems of the modified relaxed projection algorithms for the split feasibility problem in Hilbert spaces in OPTIMIZATION LETTERS
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1186/s13660-019-2030-x

    DOI

    http://dx.doi.org/10.1186/s13660-019-2030-x

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1113040856


    Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
    Incoming Citations Browse incoming citations for this publication using opencitations.net

    JSON-LD is the canonical representation for SciGraph data.

    TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

    [
      {
        "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
        "about": [
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0103", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Numerical and Computational Mathematics", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/01", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Mathematical Sciences", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "Civil Aviation University of China", 
              "id": "https://www.grid.ac/institutes/grid.411713.1", 
              "name": [
                "Tianjin Key Laboratory for Advanced Signal Processing, College of Science, Civil Aviation University of China, Tianjin, P.R. China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Dong", 
            "givenName": "Q. L.", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Civil Aviation University of China", 
              "id": "https://www.grid.ac/institutes/grid.411713.1", 
              "name": [
                "Tianjin Key Laboratory for Advanced Signal Processing, College of Science, Civil Aviation University of China, Tianjin, P.R. China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Li", 
            "givenName": "X. H.", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "King Mongkut's University of Technology Thonburi", 
              "id": "https://www.grid.ac/institutes/grid.412151.2", 
              "name": [
                "KMUTTFixed Point Research Laboratory, Department of Mathematics, Faculty of Science, King Mongkut\u2019s University of Technology Thonburi (KMUTT), Bangkok, Thailand"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Kitkuan", 
            "givenName": "D.", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of Electronic Science and Technology of China", 
              "id": "https://www.grid.ac/institutes/grid.54549.39", 
              "name": [
                "Department of Mathematics Education, Gyeongsang National University, Jinju, Korea", 
                "School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, P.R. China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Cho", 
            "givenName": "Y. J.", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "King Mongkut's University of Technology Thonburi", 
              "id": "https://www.grid.ac/institutes/grid.412151.2", 
              "name": [
                "KMUTTFixed Point Research Laboratory, Department of Mathematics, Faculty of Science, King Mongkut\u2019s University of Technology Thonburi (KMUTT), Bangkok, Thailand", 
                "Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, Taiwan"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Kumam", 
            "givenName": "P.", 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "sg:pub.10.1007/s10957-011-9837-z", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1000868209", 
              "https://doi.org/10.1007/s10957-011-9837-z"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11590-013-0708-4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1001249957", 
              "https://doi.org/10.1007/s11590-013-0708-4"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/02331934.2014.883515", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1001569958"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/02331934.2016.1239266", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1003402358"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/02331934.2014.895897", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1007555695"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1073/pnas.38.2.121", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008770629"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11590-013-0619-4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1012759316", 
              "https://doi.org/10.1007/s11590-013-0619-4"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.aml.2011.10.035", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1013702451"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1081/nfa-200063882", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016501824"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1081/nfa-200063882", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016501824"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0362-546x(92)90159-c", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1018296441"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11590-016-1102-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1024330304", 
              "https://doi.org/10.1007/s11590-016-1102-9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11590-016-1102-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1024330304", 
              "https://doi.org/10.1007/s11590-016-1102-9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1687-1812-2013-201", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1024954899", 
              "https://doi.org/10.1186/1687-1812-2013-201"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1088/0266-5611/20/1/006", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1026022192"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1088/0266-5611/21/6/017", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1026264452"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1088/0266-5611/21/6/017", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1026264452"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1590/s1807-03022011000100005", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1026649440"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/01630560600569957", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1029114504"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10589-010-9360-4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1035820350", 
              "https://doi.org/10.1007/s10589-010-9360-4"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/02331930412331327157", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1045441216"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/bf02142692", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1045687057", 
              "https://doi.org/10.1007/bf02142692"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/bf02142692", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1045687057", 
              "https://doi.org/10.1007/bf02142692"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00186-016-0553-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1049713441", 
              "https://doi.org/10.1007/s00186-016-0553-1"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00186-016-0553-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1049713441", 
              "https://doi.org/10.1007/s00186-016-0553-1"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11075-011-9490-5", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1052842978", 
              "https://doi.org/10.1007/s11075-011-9490-5"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1088/0031-9155/51/10/001", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1059026021"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/tpwrs.2003.820692", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061776415"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1561/2400000003", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1068001442"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10898-017-0506-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1084027825", 
              "https://doi.org/10.1007/s10898-017-0506-0"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10898-017-0506-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1084027825", 
              "https://doi.org/10.1007/s10898-017-0506-0"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.22436/jnsa.010.02.43", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1084400694"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11784-017-0480-7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1100671345", 
              "https://doi.org/10.1007/s11784-017-0480-7"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11075-018-0499-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1101127577", 
              "https://doi.org/10.1007/s11075-018-0499-x"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11075-018-0499-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1101127577", 
              "https://doi.org/10.1007/s11075-018-0499-x"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10898-018-0628-z", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1101288954", 
              "https://doi.org/10.1007/s10898-018-0628-z"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10898-018-0628-z", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1101288954", 
              "https://doi.org/10.1007/s10898-018-0628-z"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10898-018-0628-z", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1101288954", 
              "https://doi.org/10.1007/s10898-018-0628-z"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/02331934.2018.1522636", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1107130045"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2019-12", 
        "datePublishedReg": "2019-12-01", 
        "description": "In this paper, we first introduce a new algorithm which involves projecting each iteration to solve a split feasibility problem with paramonotone equilibria and using unconstrained convex optimization. The strong convergence of the proposed algorithm is presented. Second, we also revisit this split feasibility problem and replace the unconstrained convex optimization by a constrained convex optimization. We introduce some algorithms for two different types of objective function of the constrained convex optimization and prove some strong convergence results of the proposed algorithms. Third, we apply our algorithms for finding an equilibrium point with minimal environmental cost for a model in electricity production. Finally, we give some numerical results to illustrate the effectiveness and advantages of the proposed algorithms.", 
        "genre": "research_article", 
        "id": "sg:pub.10.1186/s13660-019-2030-x", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": false, 
        "isPartOf": [
          {
            "id": "sg:journal.1136856", 
            "issn": [
              "1025-5834", 
              "1029-242X"
            ], 
            "name": "Journal of Inequalities and Applications", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "1", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "2019"
          }
        ], 
        "name": "Some algorithms for classes of split feasibility problems involving paramonotone equilibria and convex optimization", 
        "pagination": "77", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "0004edb7dc2f7e2a721ccdb1decd0da32f78fd90df4ef8b821b5f4a8ffaa33d7"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1186/s13660-019-2030-x"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1113040856"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1186/s13660-019-2030-x", 
          "https://app.dimensions.ai/details/publication/pub.1113040856"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-11T13:20", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000368_0000000368/records_78970_00000001.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "https://link.springer.com/10.1186%2Fs13660-019-2030-x"
      }
    ]
     

    Download the RDF metadata as:  json-ld nt turtle xml License info

    HOW TO GET THIS DATA PROGRAMMATICALLY:

    JSON-LD is a popular format for linked data which is fully compatible with JSON.

    curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1186/s13660-019-2030-x'

    N-Triples is a line-based linked data format ideal for batch operations.

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/s13660-019-2030-x'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s13660-019-2030-x'

    RDF/XML is a standard XML format for linked data.

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s13660-019-2030-x'


     

    This table displays all metadata directly associated to this object as RDF triples.

    195 TRIPLES      21 PREDICATES      57 URIs      19 LITERALS      7 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1186/s13660-019-2030-x schema:about anzsrc-for:01
    2 anzsrc-for:0103
    3 schema:author Na505591b168f468183210ec2450e616f
    4 schema:citation sg:pub.10.1007/bf02142692
    5 sg:pub.10.1007/s00186-016-0553-1
    6 sg:pub.10.1007/s10589-010-9360-4
    7 sg:pub.10.1007/s10898-017-0506-0
    8 sg:pub.10.1007/s10898-018-0628-z
    9 sg:pub.10.1007/s10957-011-9837-z
    10 sg:pub.10.1007/s11075-011-9490-5
    11 sg:pub.10.1007/s11075-018-0499-x
    12 sg:pub.10.1007/s11590-013-0619-4
    13 sg:pub.10.1007/s11590-013-0708-4
    14 sg:pub.10.1007/s11590-016-1102-9
    15 sg:pub.10.1007/s11784-017-0480-7
    16 sg:pub.10.1186/1687-1812-2013-201
    17 https://doi.org/10.1016/0362-546x(92)90159-c
    18 https://doi.org/10.1016/j.aml.2011.10.035
    19 https://doi.org/10.1073/pnas.38.2.121
    20 https://doi.org/10.1080/01630560600569957
    21 https://doi.org/10.1080/02331930412331327157
    22 https://doi.org/10.1080/02331934.2014.883515
    23 https://doi.org/10.1080/02331934.2014.895897
    24 https://doi.org/10.1080/02331934.2016.1239266
    25 https://doi.org/10.1080/02331934.2018.1522636
    26 https://doi.org/10.1081/nfa-200063882
    27 https://doi.org/10.1088/0031-9155/51/10/001
    28 https://doi.org/10.1088/0266-5611/20/1/006
    29 https://doi.org/10.1088/0266-5611/21/6/017
    30 https://doi.org/10.1109/tpwrs.2003.820692
    31 https://doi.org/10.1561/2400000003
    32 https://doi.org/10.1590/s1807-03022011000100005
    33 https://doi.org/10.22436/jnsa.010.02.43
    34 schema:datePublished 2019-12
    35 schema:datePublishedReg 2019-12-01
    36 schema:description In this paper, we first introduce a new algorithm which involves projecting each iteration to solve a split feasibility problem with paramonotone equilibria and using unconstrained convex optimization. The strong convergence of the proposed algorithm is presented. Second, we also revisit this split feasibility problem and replace the unconstrained convex optimization by a constrained convex optimization. We introduce some algorithms for two different types of objective function of the constrained convex optimization and prove some strong convergence results of the proposed algorithms. Third, we apply our algorithms for finding an equilibrium point with minimal environmental cost for a model in electricity production. Finally, we give some numerical results to illustrate the effectiveness and advantages of the proposed algorithms.
    37 schema:genre research_article
    38 schema:inLanguage en
    39 schema:isAccessibleForFree false
    40 schema:isPartOf N3fb9c32d0ef24b8b83216cd01afbbf73
    41 N715d0ff1e1cc425c8ec83298daba1cf4
    42 sg:journal.1136856
    43 schema:name Some algorithms for classes of split feasibility problems involving paramonotone equilibria and convex optimization
    44 schema:pagination 77
    45 schema:productId N49187cf1bb4e43338bf9c8e368a0492b
    46 Na0613190e15a425e891152a3431935c0
    47 Nde8a390b2484448b8253f86a57a2dc7d
    48 schema:sameAs https://app.dimensions.ai/details/publication/pub.1113040856
    49 https://doi.org/10.1186/s13660-019-2030-x
    50 schema:sdDatePublished 2019-04-11T13:20
    51 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    52 schema:sdPublisher Ne7213c57aefb4675972c43f318cffb7a
    53 schema:url https://link.springer.com/10.1186%2Fs13660-019-2030-x
    54 sgo:license sg:explorer/license/
    55 sgo:sdDataset articles
    56 rdf:type schema:ScholarlyArticle
    57 N28e94da6a1df4a7992eb363181bd9d21 rdf:first Nc2991390a22e4c01a13b2e65f263a2cf
    58 rdf:rest N89fa26b2656941588339c909e0062946
    59 N3fb9c32d0ef24b8b83216cd01afbbf73 schema:issueNumber 1
    60 rdf:type schema:PublicationIssue
    61 N49187cf1bb4e43338bf9c8e368a0492b schema:name readcube_id
    62 schema:value 0004edb7dc2f7e2a721ccdb1decd0da32f78fd90df4ef8b821b5f4a8ffaa33d7
    63 rdf:type schema:PropertyValue
    64 N4d9d219728b948808b6963341d48ecc6 rdf:first Nf304a8c3378942f2acb97aa1a509202a
    65 rdf:rest rdf:nil
    66 N715d0ff1e1cc425c8ec83298daba1cf4 schema:volumeNumber 2019
    67 rdf:type schema:PublicationVolume
    68 N89fa26b2656941588339c909e0062946 rdf:first N93af72b6a3694bb980816a318920ffe6
    69 rdf:rest N4d9d219728b948808b6963341d48ecc6
    70 N93af72b6a3694bb980816a318920ffe6 schema:affiliation https://www.grid.ac/institutes/grid.54549.39
    71 schema:familyName Cho
    72 schema:givenName Y. J.
    73 rdf:type schema:Person
    74 Na0613190e15a425e891152a3431935c0 schema:name dimensions_id
    75 schema:value pub.1113040856
    76 rdf:type schema:PropertyValue
    77 Na505591b168f468183210ec2450e616f rdf:first Ne4dc24229a12497580c3d4f760004070
    78 rdf:rest Neb26eec8f1b04f48877b2119620c260d
    79 Na6f6ff11faee4a5ea6db6df33186c487 schema:affiliation https://www.grid.ac/institutes/grid.411713.1
    80 schema:familyName Li
    81 schema:givenName X. H.
    82 rdf:type schema:Person
    83 Nc2991390a22e4c01a13b2e65f263a2cf schema:affiliation https://www.grid.ac/institutes/grid.412151.2
    84 schema:familyName Kitkuan
    85 schema:givenName D.
    86 rdf:type schema:Person
    87 Nde8a390b2484448b8253f86a57a2dc7d schema:name doi
    88 schema:value 10.1186/s13660-019-2030-x
    89 rdf:type schema:PropertyValue
    90 Ne4dc24229a12497580c3d4f760004070 schema:affiliation https://www.grid.ac/institutes/grid.411713.1
    91 schema:familyName Dong
    92 schema:givenName Q. L.
    93 rdf:type schema:Person
    94 Ne7213c57aefb4675972c43f318cffb7a schema:name Springer Nature - SN SciGraph project
    95 rdf:type schema:Organization
    96 Neb26eec8f1b04f48877b2119620c260d rdf:first Na6f6ff11faee4a5ea6db6df33186c487
    97 rdf:rest N28e94da6a1df4a7992eb363181bd9d21
    98 Nf304a8c3378942f2acb97aa1a509202a schema:affiliation https://www.grid.ac/institutes/grid.412151.2
    99 schema:familyName Kumam
    100 schema:givenName P.
    101 rdf:type schema:Person
    102 anzsrc-for:01 schema:inDefinedTermSet anzsrc-for:
    103 schema:name Mathematical Sciences
    104 rdf:type schema:DefinedTerm
    105 anzsrc-for:0103 schema:inDefinedTermSet anzsrc-for:
    106 schema:name Numerical and Computational Mathematics
    107 rdf:type schema:DefinedTerm
    108 sg:journal.1136856 schema:issn 1025-5834
    109 1029-242X
    110 schema:name Journal of Inequalities and Applications
    111 rdf:type schema:Periodical
    112 sg:pub.10.1007/bf02142692 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045687057
    113 https://doi.org/10.1007/bf02142692
    114 rdf:type schema:CreativeWork
    115 sg:pub.10.1007/s00186-016-0553-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049713441
    116 https://doi.org/10.1007/s00186-016-0553-1
    117 rdf:type schema:CreativeWork
    118 sg:pub.10.1007/s10589-010-9360-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035820350
    119 https://doi.org/10.1007/s10589-010-9360-4
    120 rdf:type schema:CreativeWork
    121 sg:pub.10.1007/s10898-017-0506-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1084027825
    122 https://doi.org/10.1007/s10898-017-0506-0
    123 rdf:type schema:CreativeWork
    124 sg:pub.10.1007/s10898-018-0628-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1101288954
    125 https://doi.org/10.1007/s10898-018-0628-z
    126 rdf:type schema:CreativeWork
    127 sg:pub.10.1007/s10957-011-9837-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1000868209
    128 https://doi.org/10.1007/s10957-011-9837-z
    129 rdf:type schema:CreativeWork
    130 sg:pub.10.1007/s11075-011-9490-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052842978
    131 https://doi.org/10.1007/s11075-011-9490-5
    132 rdf:type schema:CreativeWork
    133 sg:pub.10.1007/s11075-018-0499-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1101127577
    134 https://doi.org/10.1007/s11075-018-0499-x
    135 rdf:type schema:CreativeWork
    136 sg:pub.10.1007/s11590-013-0619-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012759316
    137 https://doi.org/10.1007/s11590-013-0619-4
    138 rdf:type schema:CreativeWork
    139 sg:pub.10.1007/s11590-013-0708-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001249957
    140 https://doi.org/10.1007/s11590-013-0708-4
    141 rdf:type schema:CreativeWork
    142 sg:pub.10.1007/s11590-016-1102-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024330304
    143 https://doi.org/10.1007/s11590-016-1102-9
    144 rdf:type schema:CreativeWork
    145 sg:pub.10.1007/s11784-017-0480-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1100671345
    146 https://doi.org/10.1007/s11784-017-0480-7
    147 rdf:type schema:CreativeWork
    148 sg:pub.10.1186/1687-1812-2013-201 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024954899
    149 https://doi.org/10.1186/1687-1812-2013-201
    150 rdf:type schema:CreativeWork
    151 https://doi.org/10.1016/0362-546x(92)90159-c schema:sameAs https://app.dimensions.ai/details/publication/pub.1018296441
    152 rdf:type schema:CreativeWork
    153 https://doi.org/10.1016/j.aml.2011.10.035 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013702451
    154 rdf:type schema:CreativeWork
    155 https://doi.org/10.1073/pnas.38.2.121 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008770629
    156 rdf:type schema:CreativeWork
    157 https://doi.org/10.1080/01630560600569957 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029114504
    158 rdf:type schema:CreativeWork
    159 https://doi.org/10.1080/02331930412331327157 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045441216
    160 rdf:type schema:CreativeWork
    161 https://doi.org/10.1080/02331934.2014.883515 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001569958
    162 rdf:type schema:CreativeWork
    163 https://doi.org/10.1080/02331934.2014.895897 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007555695
    164 rdf:type schema:CreativeWork
    165 https://doi.org/10.1080/02331934.2016.1239266 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003402358
    166 rdf:type schema:CreativeWork
    167 https://doi.org/10.1080/02331934.2018.1522636 schema:sameAs https://app.dimensions.ai/details/publication/pub.1107130045
    168 rdf:type schema:CreativeWork
    169 https://doi.org/10.1081/nfa-200063882 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016501824
    170 rdf:type schema:CreativeWork
    171 https://doi.org/10.1088/0031-9155/51/10/001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059026021
    172 rdf:type schema:CreativeWork
    173 https://doi.org/10.1088/0266-5611/20/1/006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026022192
    174 rdf:type schema:CreativeWork
    175 https://doi.org/10.1088/0266-5611/21/6/017 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026264452
    176 rdf:type schema:CreativeWork
    177 https://doi.org/10.1109/tpwrs.2003.820692 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061776415
    178 rdf:type schema:CreativeWork
    179 https://doi.org/10.1561/2400000003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1068001442
    180 rdf:type schema:CreativeWork
    181 https://doi.org/10.1590/s1807-03022011000100005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026649440
    182 rdf:type schema:CreativeWork
    183 https://doi.org/10.22436/jnsa.010.02.43 schema:sameAs https://app.dimensions.ai/details/publication/pub.1084400694
    184 rdf:type schema:CreativeWork
    185 https://www.grid.ac/institutes/grid.411713.1 schema:alternateName Civil Aviation University of China
    186 schema:name Tianjin Key Laboratory for Advanced Signal Processing, College of Science, Civil Aviation University of China, Tianjin, P.R. China
    187 rdf:type schema:Organization
    188 https://www.grid.ac/institutes/grid.412151.2 schema:alternateName King Mongkut's University of Technology Thonburi
    189 schema:name Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, Taiwan
    190 KMUTTFixed Point Research Laboratory, Department of Mathematics, Faculty of Science, King Mongkut’s University of Technology Thonburi (KMUTT), Bangkok, Thailand
    191 rdf:type schema:Organization
    192 https://www.grid.ac/institutes/grid.54549.39 schema:alternateName University of Electronic Science and Technology of China
    193 schema:name Department of Mathematics Education, Gyeongsang National University, Jinju, Korea
    194 School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, P.R. China
    195 rdf:type schema:Organization
     




    Preview window. Press ESC to close (or click here)


    ...