Road maintenance planning model based on neural networks
Abstract Geographically distributed defects of roads, as well as machines used to maintain them are represented as a set of defects and a set of repair mechanisms for road network infrastructure, respectively. Each element of the set of defects has a certain rate of loss in the case of its realizati...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Brovarnyi, D. P. [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2011 |
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| Schlagwörter: |
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| Anmerkung: |
© Pleiades Publishing, Ltd. 2011 |
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| Übergeordnetes Werk: |
Enthalten in: Automation and remote control - SP MAIK Nauka/Interperiodica, 1957, 72(2011), 6 vom: Juni, Seite 1333-1337 |
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| Übergeordnetes Werk: |
volume:72 ; year:2011 ; number:6 ; month:06 ; pages:1333-1337 |
| Links: |
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| DOI / URN: |
10.1134/S000511791106021X |
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OLC2060900476 |
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| 520 | |a Abstract Geographically distributed defects of roads, as well as machines used to maintain them are represented as a set of defects and a set of repair mechanisms for road network infrastructure, respectively. Each element of the set of defects has a certain rate of loss in the case of its realization. On the other hand, every element of the set of repair mechanisms possesses certain value and efficiency with respect to subset of the covered defects. An algorithm to define the subset of elements belonging to the set of repair mechanisms (which ensures the minimum of uncovered loss under given value of repair mechanisms) is developed. The problem is solved involving neural network basis. | ||
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| 650 | 4 | |a Road Network | |
| 650 | 4 | |a Repair Mechanism | |
| 650 | 4 | |a Covered Defect | |
| 650 | 4 | |a Road Maintenance | |
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10.1134/S000511791106021X doi (DE-627)OLC2060900476 (DE-He213)S000511791106021X-p DE-627 ger DE-627 rakwb eng 000 620 VZ Brovarnyi, D. P. verfasserin aut Road maintenance planning model based on neural networks 2011 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Pleiades Publishing, Ltd. 2011 Abstract Geographically distributed defects of roads, as well as machines used to maintain them are represented as a set of defects and a set of repair mechanisms for road network infrastructure, respectively. Each element of the set of defects has a certain rate of loss in the case of its realization. On the other hand, every element of the set of repair mechanisms possesses certain value and efficiency with respect to subset of the covered defects. An algorithm to define the subset of elements belonging to the set of repair mechanisms (which ensures the minimum of uncovered loss under given value of repair mechanisms) is developed. The problem is solved involving neural network basis. Remote Control Road Network Repair Mechanism Covered Defect Road Maintenance Enthalten in Automation and remote control SP MAIK Nauka/Interperiodica, 1957 72(2011), 6 vom: Juni, Seite 1333-1337 (DE-627)129603481 (DE-600)241725-X (DE-576)015097315 0005-1179 nnns volume:72 year:2011 number:6 month:06 pages:1333-1337 https://doi.org/10.1134/S000511791106021X lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT GBV_ILN_70 AR 72 2011 6 06 1333-1337 |
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10.1134/S000511791106021X doi (DE-627)OLC2060900476 (DE-He213)S000511791106021X-p DE-627 ger DE-627 rakwb eng 000 620 VZ Brovarnyi, D. P. verfasserin aut Road maintenance planning model based on neural networks 2011 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Pleiades Publishing, Ltd. 2011 Abstract Geographically distributed defects of roads, as well as machines used to maintain them are represented as a set of defects and a set of repair mechanisms for road network infrastructure, respectively. Each element of the set of defects has a certain rate of loss in the case of its realization. On the other hand, every element of the set of repair mechanisms possesses certain value and efficiency with respect to subset of the covered defects. An algorithm to define the subset of elements belonging to the set of repair mechanisms (which ensures the minimum of uncovered loss under given value of repair mechanisms) is developed. The problem is solved involving neural network basis. Remote Control Road Network Repair Mechanism Covered Defect Road Maintenance Enthalten in Automation and remote control SP MAIK Nauka/Interperiodica, 1957 72(2011), 6 vom: Juni, Seite 1333-1337 (DE-627)129603481 (DE-600)241725-X (DE-576)015097315 0005-1179 nnns volume:72 year:2011 number:6 month:06 pages:1333-1337 https://doi.org/10.1134/S000511791106021X lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT GBV_ILN_70 AR 72 2011 6 06 1333-1337 |
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10.1134/S000511791106021X doi (DE-627)OLC2060900476 (DE-He213)S000511791106021X-p DE-627 ger DE-627 rakwb eng 000 620 VZ Brovarnyi, D. P. verfasserin aut Road maintenance planning model based on neural networks 2011 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Pleiades Publishing, Ltd. 2011 Abstract Geographically distributed defects of roads, as well as machines used to maintain them are represented as a set of defects and a set of repair mechanisms for road network infrastructure, respectively. Each element of the set of defects has a certain rate of loss in the case of its realization. On the other hand, every element of the set of repair mechanisms possesses certain value and efficiency with respect to subset of the covered defects. An algorithm to define the subset of elements belonging to the set of repair mechanisms (which ensures the minimum of uncovered loss under given value of repair mechanisms) is developed. The problem is solved involving neural network basis. Remote Control Road Network Repair Mechanism Covered Defect Road Maintenance Enthalten in Automation and remote control SP MAIK Nauka/Interperiodica, 1957 72(2011), 6 vom: Juni, Seite 1333-1337 (DE-627)129603481 (DE-600)241725-X (DE-576)015097315 0005-1179 nnns volume:72 year:2011 number:6 month:06 pages:1333-1337 https://doi.org/10.1134/S000511791106021X lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT GBV_ILN_70 AR 72 2011 6 06 1333-1337 |
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10.1134/S000511791106021X doi (DE-627)OLC2060900476 (DE-He213)S000511791106021X-p DE-627 ger DE-627 rakwb eng 000 620 VZ Brovarnyi, D. P. verfasserin aut Road maintenance planning model based on neural networks 2011 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Pleiades Publishing, Ltd. 2011 Abstract Geographically distributed defects of roads, as well as machines used to maintain them are represented as a set of defects and a set of repair mechanisms for road network infrastructure, respectively. Each element of the set of defects has a certain rate of loss in the case of its realization. On the other hand, every element of the set of repair mechanisms possesses certain value and efficiency with respect to subset of the covered defects. An algorithm to define the subset of elements belonging to the set of repair mechanisms (which ensures the minimum of uncovered loss under given value of repair mechanisms) is developed. The problem is solved involving neural network basis. Remote Control Road Network Repair Mechanism Covered Defect Road Maintenance Enthalten in Automation and remote control SP MAIK Nauka/Interperiodica, 1957 72(2011), 6 vom: Juni, Seite 1333-1337 (DE-627)129603481 (DE-600)241725-X (DE-576)015097315 0005-1179 nnns volume:72 year:2011 number:6 month:06 pages:1333-1337 https://doi.org/10.1134/S000511791106021X lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT GBV_ILN_70 AR 72 2011 6 06 1333-1337 |
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10.1134/S000511791106021X doi (DE-627)OLC2060900476 (DE-He213)S000511791106021X-p DE-627 ger DE-627 rakwb eng 000 620 VZ Brovarnyi, D. P. verfasserin aut Road maintenance planning model based on neural networks 2011 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Pleiades Publishing, Ltd. 2011 Abstract Geographically distributed defects of roads, as well as machines used to maintain them are represented as a set of defects and a set of repair mechanisms for road network infrastructure, respectively. Each element of the set of defects has a certain rate of loss in the case of its realization. On the other hand, every element of the set of repair mechanisms possesses certain value and efficiency with respect to subset of the covered defects. An algorithm to define the subset of elements belonging to the set of repair mechanisms (which ensures the minimum of uncovered loss under given value of repair mechanisms) is developed. The problem is solved involving neural network basis. Remote Control Road Network Repair Mechanism Covered Defect Road Maintenance Enthalten in Automation and remote control SP MAIK Nauka/Interperiodica, 1957 72(2011), 6 vom: Juni, Seite 1333-1337 (DE-627)129603481 (DE-600)241725-X (DE-576)015097315 0005-1179 nnns volume:72 year:2011 number:6 month:06 pages:1333-1337 https://doi.org/10.1134/S000511791106021X lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT GBV_ILN_70 AR 72 2011 6 06 1333-1337 |
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Abstract Geographically distributed defects of roads, as well as machines used to maintain them are represented as a set of defects and a set of repair mechanisms for road network infrastructure, respectively. Each element of the set of defects has a certain rate of loss in the case of its realization. On the other hand, every element of the set of repair mechanisms possesses certain value and efficiency with respect to subset of the covered defects. An algorithm to define the subset of elements belonging to the set of repair mechanisms (which ensures the minimum of uncovered loss under given value of repair mechanisms) is developed. The problem is solved involving neural network basis. © Pleiades Publishing, Ltd. 2011 |
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Abstract Geographically distributed defects of roads, as well as machines used to maintain them are represented as a set of defects and a set of repair mechanisms for road network infrastructure, respectively. Each element of the set of defects has a certain rate of loss in the case of its realization. On the other hand, every element of the set of repair mechanisms possesses certain value and efficiency with respect to subset of the covered defects. An algorithm to define the subset of elements belonging to the set of repair mechanisms (which ensures the minimum of uncovered loss under given value of repair mechanisms) is developed. The problem is solved involving neural network basis. © Pleiades Publishing, Ltd. 2011 |
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Abstract Geographically distributed defects of roads, as well as machines used to maintain them are represented as a set of defects and a set of repair mechanisms for road network infrastructure, respectively. Each element of the set of defects has a certain rate of loss in the case of its realization. On the other hand, every element of the set of repair mechanisms possesses certain value and efficiency with respect to subset of the covered defects. An algorithm to define the subset of elements belonging to the set of repair mechanisms (which ensures the minimum of uncovered loss under given value of repair mechanisms) is developed. The problem is solved involving neural network basis. © Pleiades Publishing, Ltd. 2011 |
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P.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Road maintenance planning model based on neural networks</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2011</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Pleiades Publishing, Ltd. 2011</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Geographically distributed defects of roads, as well as machines used to maintain them are represented as a set of defects and a set of repair mechanisms for road network infrastructure, respectively. Each element of the set of defects has a certain rate of loss in the case of its realization. On the other hand, every element of the set of repair mechanisms possesses certain value and efficiency with respect to subset of the covered defects. An algorithm to define the subset of elements belonging to the set of repair mechanisms (which ensures the minimum of uncovered loss under given value of repair mechanisms) is developed. The problem is solved involving neural network basis.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Remote Control</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Road Network</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Repair Mechanism</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Covered Defect</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Road Maintenance</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Automation and remote control</subfield><subfield code="d">SP MAIK Nauka/Interperiodica, 1957</subfield><subfield code="g">72(2011), 6 vom: Juni, Seite 1333-1337</subfield><subfield code="w">(DE-627)129603481</subfield><subfield code="w">(DE-600)241725-X</subfield><subfield code="w">(DE-576)015097315</subfield><subfield code="x">0005-1179</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:72</subfield><subfield code="g">year:2011</subfield><subfield code="g">number:6</subfield><subfield code="g">month:06</subfield><subfield code="g">pages:1333-1337</subfield></datafield><datafield tag="856" ind1="4" ind2="1"><subfield code="u">https://doi.org/10.1134/S000511791106021X</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_OLC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-TEC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-MAT</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">72</subfield><subfield code="j">2011</subfield><subfield code="e">6</subfield><subfield code="c">06</subfield><subfield code="h">1333-1337</subfield></datafield></record></collection>
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