A linear programming approach to weak reversibility and linear conjugacy of chemical reaction networks View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2012-01

AUTHORS

Matthew D. Johnston, David Siegel, Gábor Szederkényi

ABSTRACT

A numerically effective procedure for determining weakly reversible chemical reaction networks that are linearly conjugate to a known reaction network is proposed in this paper. The method is based on translating the structural and algebraic characteristics of weak reversibility to logical statements and solving the obtained set of linear (in)equalities in the framework of mixed integer linear programming. The unknowns in the problem are the reaction rate coefficients and the parameters of the linear conjugacy transformation. The efficacy of the approach is shown through numerical examples. More... »

PAGES

274-288

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10910-011-9911-7

DOI

http://dx.doi.org/10.1007/s10910-011-9911-7

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1030049136


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/2008/0306", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Physical Chemistry (incl. Structural)", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/03", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Chemical Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "University of Waterloo", 
          "id": "https://www.grid.ac/institutes/grid.46078.3d", 
          "name": [
            "Department of Applied Mathematics, University of Waterloo, N2L 3G1, Waterloo, ON, Canada"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Johnston", 
        "givenName": "Matthew D.", 
        "id": "sg:person.01174250571.19", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01174250571.19"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Waterloo", 
          "id": "https://www.grid.ac/institutes/grid.46078.3d", 
          "name": [
            "Department of Applied Mathematics, University of Waterloo, N2L 3G1, Waterloo, ON, Canada"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Siegel", 
        "givenName": "David", 
        "id": "sg:person.01242363771.96", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01242363771.96"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "MTA Institute for Computer Science and Control", 
          "id": "https://www.grid.ac/institutes/grid.4836.9", 
          "name": [
            "(Bio)Process Engineering Group, IIM-CSIC, Spanish National Research Council, C/Eduardo Cabello, 6, 36208, Vigo, Spain", 
            "Computer and Automation Research Institute, Hungarian Academy of Sciences, P.O. Box 63, 1518, Budapest, Hungary"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Szederk\u00e9nyi", 
        "givenName": "G\u00e1bor", 
        "id": "sg:person.012760224621.12", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012760224621.12"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1007/978-1-4757-4067-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000039730", 
          "https://doi.org/10.1007/978-1-4757-4067-7"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4757-4067-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000039730", 
          "https://doi.org/10.1007/978-1-4757-4067-7"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf00255664", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001728211", 
          "https://doi.org/10.1007/bf00255664"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf00255664", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001728211", 
          "https://doi.org/10.1007/bf00255664"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1073/pnas.0602767103", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002189124"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf00251527", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009390404", 
          "https://doi.org/10.1007/bf00251527"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf00251527", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009390404", 
          "https://doi.org/10.1007/bf00251527"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/14689360802243813", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015258538"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.mbs.2007.07.003", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015550957"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10910-007-9307-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021306492", 
          "https://doi.org/10.1007/s10910-007-9307-x"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0020-0190(94)90047-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022741203"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0009-2509(94)80061-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027977071"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jsc.2008.08.006", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031364908"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf00251225", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032254027", 
          "https://doi.org/10.1007/bf00251225"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf00251225", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032254027", 
          "https://doi.org/10.1007/bf00251225"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/14689367.2010.545812", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032672253"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10910-011-9804-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039596199", 
          "https://doi.org/10.1007/s10910-011-9804-9"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0098-1354(93)e0010-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041293982"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf00255665", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041541756", 
          "https://doi.org/10.1007/bf00255665"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf00255665", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041541756", 
          "https://doi.org/10.1007/bf00255665"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1006/jsco.2001.0512", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044710308"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10910-009-9525-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045140371", 
          "https://doi.org/10.1007/s10910-009-9525-5"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10910-008-9499-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045720341", 
          "https://doi.org/10.1007/s10910-008-9499-8"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/9.935056", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061246754"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1137/050634177", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062846335"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1137/070698282", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062851414"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1137/090760751", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062856381"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1137/090764098", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062856479"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1137/100812355", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062859575"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1137/s0036139904440278", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062874995"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/iscas.2010.5537543", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1095186194"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2012-01", 
    "datePublishedReg": "2012-01-01", 
    "description": "A numerically effective procedure for determining weakly reversible chemical reaction networks that are linearly conjugate to a known reaction network is proposed in this paper. The method is based on translating the structural and algebraic characteristics of weak reversibility to logical statements and solving the obtained set of linear (in)equalities in the framework of mixed integer linear programming. The unknowns in the problem are the reaction rate coefficients and the parameters of the linear conjugacy transformation. The efficacy of the approach is shown through numerical examples.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s10910-011-9911-7", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1026076", 
        "issn": [
          "0259-9791", 
          "1572-8897"
        ], 
        "name": "Journal of Mathematical Chemistry", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "50"
      }
    ], 
    "name": "A linear programming approach to weak reversibility and linear conjugacy of chemical reaction networks", 
    "pagination": "274-288", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "8f26cbf5482f9583c804c07fe4845a8de31137d4f62fb21c7090f6b0aa86d47c"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s10910-011-9911-7"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1030049136"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s10910-011-9911-7", 
      "https://app.dimensions.ai/details/publication/pub.1030049136"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-10T20:47", 
    "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/v90/0000000001_0000000264/records_8684_00000513.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1007%2Fs10910-011-9911-7"
  }
]
 

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.10.1007/s10910-011-9911-7'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s10910-011-9911-7'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s10910-011-9911-7'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s10910-011-9911-7'


 

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

166 TRIPLES      21 PREDICATES      53 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s10910-011-9911-7 schema:about anzsrc-for:03
2 anzsrc-for:0306
3 schema:author Nad3aa097bc134d70a972620f9116b9a4
4 schema:citation sg:pub.10.1007/978-1-4757-4067-7
5 sg:pub.10.1007/bf00251225
6 sg:pub.10.1007/bf00251527
7 sg:pub.10.1007/bf00255664
8 sg:pub.10.1007/bf00255665
9 sg:pub.10.1007/s10910-007-9307-x
10 sg:pub.10.1007/s10910-008-9499-8
11 sg:pub.10.1007/s10910-009-9525-5
12 sg:pub.10.1007/s10910-011-9804-9
13 https://doi.org/10.1006/jsco.2001.0512
14 https://doi.org/10.1016/0009-2509(94)80061-8
15 https://doi.org/10.1016/0020-0190(94)90047-7
16 https://doi.org/10.1016/0098-1354(93)e0010-7
17 https://doi.org/10.1016/j.jsc.2008.08.006
18 https://doi.org/10.1016/j.mbs.2007.07.003
19 https://doi.org/10.1073/pnas.0602767103
20 https://doi.org/10.1080/14689360802243813
21 https://doi.org/10.1080/14689367.2010.545812
22 https://doi.org/10.1109/9.935056
23 https://doi.org/10.1109/iscas.2010.5537543
24 https://doi.org/10.1137/050634177
25 https://doi.org/10.1137/070698282
26 https://doi.org/10.1137/090760751
27 https://doi.org/10.1137/090764098
28 https://doi.org/10.1137/100812355
29 https://doi.org/10.1137/s0036139904440278
30 schema:datePublished 2012-01
31 schema:datePublishedReg 2012-01-01
32 schema:description A numerically effective procedure for determining weakly reversible chemical reaction networks that are linearly conjugate to a known reaction network is proposed in this paper. The method is based on translating the structural and algebraic characteristics of weak reversibility to logical statements and solving the obtained set of linear (in)equalities in the framework of mixed integer linear programming. The unknowns in the problem are the reaction rate coefficients and the parameters of the linear conjugacy transformation. The efficacy of the approach is shown through numerical examples.
33 schema:genre research_article
34 schema:inLanguage en
35 schema:isAccessibleForFree true
36 schema:isPartOf N1d57d20a65cb451d98ad4b0689936533
37 Ndb551edd09d14db7905d6d06bbb85e06
38 sg:journal.1026076
39 schema:name A linear programming approach to weak reversibility and linear conjugacy of chemical reaction networks
40 schema:pagination 274-288
41 schema:productId N306de0d2da264542b82cacb34ae0e3a4
42 N4ab47a71e24746488d271377fb888220
43 N92d845eb70544e1f9dae781224b54916
44 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030049136
45 https://doi.org/10.1007/s10910-011-9911-7
46 schema:sdDatePublished 2019-04-10T20:47
47 schema:sdLicense https://scigraph.springernature.com/explorer/license/
48 schema:sdPublisher N1146f11f022349f3a4516f323adcc002
49 schema:url http://link.springer.com/10.1007%2Fs10910-011-9911-7
50 sgo:license sg:explorer/license/
51 sgo:sdDataset articles
52 rdf:type schema:ScholarlyArticle
53 N1146f11f022349f3a4516f323adcc002 schema:name Springer Nature - SN SciGraph project
54 rdf:type schema:Organization
55 N1d57d20a65cb451d98ad4b0689936533 schema:issueNumber 1
56 rdf:type schema:PublicationIssue
57 N306de0d2da264542b82cacb34ae0e3a4 schema:name doi
58 schema:value 10.1007/s10910-011-9911-7
59 rdf:type schema:PropertyValue
60 N4ab47a71e24746488d271377fb888220 schema:name readcube_id
61 schema:value 8f26cbf5482f9583c804c07fe4845a8de31137d4f62fb21c7090f6b0aa86d47c
62 rdf:type schema:PropertyValue
63 N92d845eb70544e1f9dae781224b54916 schema:name dimensions_id
64 schema:value pub.1030049136
65 rdf:type schema:PropertyValue
66 Naa6824e4ba68488b9060c0ea21aa600f rdf:first sg:person.012760224621.12
67 rdf:rest rdf:nil
68 Nad3aa097bc134d70a972620f9116b9a4 rdf:first sg:person.01174250571.19
69 rdf:rest Nfc703880f4574d769146187262d51914
70 Ndb551edd09d14db7905d6d06bbb85e06 schema:volumeNumber 50
71 rdf:type schema:PublicationVolume
72 Nfc703880f4574d769146187262d51914 rdf:first sg:person.01242363771.96
73 rdf:rest Naa6824e4ba68488b9060c0ea21aa600f
74 anzsrc-for:03 schema:inDefinedTermSet anzsrc-for:
75 schema:name Chemical Sciences
76 rdf:type schema:DefinedTerm
77 anzsrc-for:0306 schema:inDefinedTermSet anzsrc-for:
78 schema:name Physical Chemistry (incl. Structural)
79 rdf:type schema:DefinedTerm
80 sg:journal.1026076 schema:issn 0259-9791
81 1572-8897
82 schema:name Journal of Mathematical Chemistry
83 rdf:type schema:Periodical
84 sg:person.01174250571.19 schema:affiliation https://www.grid.ac/institutes/grid.46078.3d
85 schema:familyName Johnston
86 schema:givenName Matthew D.
87 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01174250571.19
88 rdf:type schema:Person
89 sg:person.01242363771.96 schema:affiliation https://www.grid.ac/institutes/grid.46078.3d
90 schema:familyName Siegel
91 schema:givenName David
92 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01242363771.96
93 rdf:type schema:Person
94 sg:person.012760224621.12 schema:affiliation https://www.grid.ac/institutes/grid.4836.9
95 schema:familyName Szederkényi
96 schema:givenName Gábor
97 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012760224621.12
98 rdf:type schema:Person
99 sg:pub.10.1007/978-1-4757-4067-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000039730
100 https://doi.org/10.1007/978-1-4757-4067-7
101 rdf:type schema:CreativeWork
102 sg:pub.10.1007/bf00251225 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032254027
103 https://doi.org/10.1007/bf00251225
104 rdf:type schema:CreativeWork
105 sg:pub.10.1007/bf00251527 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009390404
106 https://doi.org/10.1007/bf00251527
107 rdf:type schema:CreativeWork
108 sg:pub.10.1007/bf00255664 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001728211
109 https://doi.org/10.1007/bf00255664
110 rdf:type schema:CreativeWork
111 sg:pub.10.1007/bf00255665 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041541756
112 https://doi.org/10.1007/bf00255665
113 rdf:type schema:CreativeWork
114 sg:pub.10.1007/s10910-007-9307-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1021306492
115 https://doi.org/10.1007/s10910-007-9307-x
116 rdf:type schema:CreativeWork
117 sg:pub.10.1007/s10910-008-9499-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045720341
118 https://doi.org/10.1007/s10910-008-9499-8
119 rdf:type schema:CreativeWork
120 sg:pub.10.1007/s10910-009-9525-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045140371
121 https://doi.org/10.1007/s10910-009-9525-5
122 rdf:type schema:CreativeWork
123 sg:pub.10.1007/s10910-011-9804-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039596199
124 https://doi.org/10.1007/s10910-011-9804-9
125 rdf:type schema:CreativeWork
126 https://doi.org/10.1006/jsco.2001.0512 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044710308
127 rdf:type schema:CreativeWork
128 https://doi.org/10.1016/0009-2509(94)80061-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027977071
129 rdf:type schema:CreativeWork
130 https://doi.org/10.1016/0020-0190(94)90047-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022741203
131 rdf:type schema:CreativeWork
132 https://doi.org/10.1016/0098-1354(93)e0010-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041293982
133 rdf:type schema:CreativeWork
134 https://doi.org/10.1016/j.jsc.2008.08.006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031364908
135 rdf:type schema:CreativeWork
136 https://doi.org/10.1016/j.mbs.2007.07.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015550957
137 rdf:type schema:CreativeWork
138 https://doi.org/10.1073/pnas.0602767103 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002189124
139 rdf:type schema:CreativeWork
140 https://doi.org/10.1080/14689360802243813 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015258538
141 rdf:type schema:CreativeWork
142 https://doi.org/10.1080/14689367.2010.545812 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032672253
143 rdf:type schema:CreativeWork
144 https://doi.org/10.1109/9.935056 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061246754
145 rdf:type schema:CreativeWork
146 https://doi.org/10.1109/iscas.2010.5537543 schema:sameAs https://app.dimensions.ai/details/publication/pub.1095186194
147 rdf:type schema:CreativeWork
148 https://doi.org/10.1137/050634177 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062846335
149 rdf:type schema:CreativeWork
150 https://doi.org/10.1137/070698282 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062851414
151 rdf:type schema:CreativeWork
152 https://doi.org/10.1137/090760751 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062856381
153 rdf:type schema:CreativeWork
154 https://doi.org/10.1137/090764098 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062856479
155 rdf:type schema:CreativeWork
156 https://doi.org/10.1137/100812355 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062859575
157 rdf:type schema:CreativeWork
158 https://doi.org/10.1137/s0036139904440278 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062874995
159 rdf:type schema:CreativeWork
160 https://www.grid.ac/institutes/grid.46078.3d schema:alternateName University of Waterloo
161 schema:name Department of Applied Mathematics, University of Waterloo, N2L 3G1, Waterloo, ON, Canada
162 rdf:type schema:Organization
163 https://www.grid.ac/institutes/grid.4836.9 schema:alternateName MTA Institute for Computer Science and Control
164 schema:name (Bio)Process Engineering Group, IIM-CSIC, Spanish National Research Council, C/Eduardo Cabello, 6, 36208, Vigo, Spain
165 Computer and Automation Research Institute, Hungarian Academy of Sciences, P.O. Box 63, 1518, Budapest, Hungary
166 rdf:type schema:Organization
 




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


...