Computing k shortest paths using modified pulse-coupled neural network
The K Shortest Paths (KSPs) problem with non-numerable applications has been researched widely, which aims to compute KSPs between two nodes in a non-decreasing order. However, less effort has been devoted to single-source KSP problem than to single-pair KSP computation, especially by using parallel...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Liu, Guisong [verfasserIn] |
|---|
| Format: |
E-Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2015transfer abstract |
|---|
| Schlagwörter: |
|---|
| Umfang: |
15 |
|---|
| Übergeordnetes Werk: |
Enthalten in: The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast - Liu, Yang ELSEVIER, 2018, an international journal, Amsterdam |
|---|---|
| Übergeordnetes Werk: |
volume:149 ; year:2015 ; day:3 ; month:02 ; pages:1162-1176 ; extent:15 |
| Links: |
|---|
| DOI / URN: |
10.1016/j.neucom.2014.09.012 |
|---|
| Katalog-ID: |
ELV018590845 |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | ELV018590845 | ||
| 003 | DE-627 | ||
| 005 | 20230625124310.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 180602s2015 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1016/j.neucom.2014.09.012 |2 doi | |
| 028 | 5 | 2 | |a GBVA2015014000023.pica |
| 035 | |a (DE-627)ELV018590845 | ||
| 035 | |a (ELSEVIER)S0925-2312(14)01168-0 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 082 | 0 | |a 610 | |
| 082 | 0 | 4 | |a 610 |q DE-600 |
| 082 | 0 | 4 | |a 570 |q VZ |
| 084 | |a BIODIV |q DE-30 |2 fid | ||
| 084 | |a 35.70 |2 bkl | ||
| 084 | |a 42.12 |2 bkl | ||
| 100 | 1 | |a Liu, Guisong |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Computing k shortest paths using modified pulse-coupled neural network |
| 264 | 1 | |c 2015transfer abstract | |
| 300 | |a 15 | ||
| 336 | |a nicht spezifiziert |b zzz |2 rdacontent | ||
| 337 | |a nicht spezifiziert |b z |2 rdamedia | ||
| 338 | |a nicht spezifiziert |b zu |2 rdacarrier | ||
| 520 | |a The K Shortest Paths (KSPs) problem with non-numerable applications has been researched widely, which aims to compute KSPs between two nodes in a non-decreasing order. However, less effort has been devoted to single-source KSP problem than to single-pair KSP computation, especially by using parallel methods. This paper proposes a Modified Continued Pulse Coupled Neural Network (MCPCNN) model to solve the two kinds of KSP problems. Theoretical analysis of MCPCNN and two algorithms for KSPs computation are presented. By using the parallel pulse transmission characteristic of pulse coupled neural networks, the method is able to find k shortest paths quickly. The computational complexity is only related to the length of the longest shortest path. Simulative results for route planning show that the proposed MCPCNN method for KSPs computation outperforms many other current efficient algorithms. | ||
| 520 | |a The K Shortest Paths (KSPs) problem with non-numerable applications has been researched widely, which aims to compute KSPs between two nodes in a non-decreasing order. However, less effort has been devoted to single-source KSP problem than to single-pair KSP computation, especially by using parallel methods. This paper proposes a Modified Continued Pulse Coupled Neural Network (MCPCNN) model to solve the two kinds of KSP problems. Theoretical analysis of MCPCNN and two algorithms for KSPs computation are presented. By using the parallel pulse transmission characteristic of pulse coupled neural networks, the method is able to find k shortest paths quickly. The computational complexity is only related to the length of the longest shortest path. Simulative results for route planning show that the proposed MCPCNN method for KSPs computation outperforms many other current efficient algorithms. | ||
| 650 | 7 | |a Pulse coupled neural network |2 Elsevier | |
| 650 | 7 | |a Single-pair KSP |2 Elsevier | |
| 650 | 7 | |a Single-source KSP |2 Elsevier | |
| 650 | 7 | |a k Shortest paths |2 Elsevier | |
| 700 | 1 | |a Qiu, Zhao |4 oth | |
| 700 | 1 | |a Qu, Hong |4 oth | |
| 700 | 1 | |a Ji, Luping |4 oth | |
| 773 | 0 | 8 | |i Enthalten in |n Elsevier |a Liu, Yang ELSEVIER |t The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast |d 2018 |d an international journal |g Amsterdam |w (DE-627)ELV002603926 |
| 773 | 1 | 8 | |g volume:149 |g year:2015 |g day:3 |g month:02 |g pages:1162-1176 |g extent:15 |
| 856 | 4 | 0 | |u https://doi.org/10.1016/j.neucom.2014.09.012 |3 Volltext |
| 912 | |a GBV_USEFLAG_U | ||
| 912 | |a GBV_ELV | ||
| 912 | |a SYSFLAG_U | ||
| 912 | |a FID-BIODIV | ||
| 912 | |a SSG-OLC-PHA | ||
| 936 | b | k | |a 35.70 |j Biochemie: Allgemeines |q VZ |
| 936 | b | k | |a 42.12 |j Biophysik |q VZ |
| 951 | |a AR | ||
| 952 | |d 149 |j 2015 |b 3 |c 0203 |h 1162-1176 |g 15 | ||
| 953 | |2 045F |a 610 | ||
| author_variant |
g l gl |
|---|---|
| matchkey_str |
liuguisongqiuzhaoquhongjiluping:2015----:optnkhretahuigoiiduscu |
| hierarchy_sort_str |
2015transfer abstract |
| bklnumber |
35.70 42.12 |
| publishDate |
2015 |
| allfields |
10.1016/j.neucom.2014.09.012 doi GBVA2015014000023.pica (DE-627)ELV018590845 (ELSEVIER)S0925-2312(14)01168-0 DE-627 ger DE-627 rakwb eng 610 610 DE-600 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl Liu, Guisong verfasserin aut Computing k shortest paths using modified pulse-coupled neural network 2015transfer abstract 15 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The K Shortest Paths (KSPs) problem with non-numerable applications has been researched widely, which aims to compute KSPs between two nodes in a non-decreasing order. However, less effort has been devoted to single-source KSP problem than to single-pair KSP computation, especially by using parallel methods. This paper proposes a Modified Continued Pulse Coupled Neural Network (MCPCNN) model to solve the two kinds of KSP problems. Theoretical analysis of MCPCNN and two algorithms for KSPs computation are presented. By using the parallel pulse transmission characteristic of pulse coupled neural networks, the method is able to find k shortest paths quickly. The computational complexity is only related to the length of the longest shortest path. Simulative results for route planning show that the proposed MCPCNN method for KSPs computation outperforms many other current efficient algorithms. The K Shortest Paths (KSPs) problem with non-numerable applications has been researched widely, which aims to compute KSPs between two nodes in a non-decreasing order. However, less effort has been devoted to single-source KSP problem than to single-pair KSP computation, especially by using parallel methods. This paper proposes a Modified Continued Pulse Coupled Neural Network (MCPCNN) model to solve the two kinds of KSP problems. Theoretical analysis of MCPCNN and two algorithms for KSPs computation are presented. By using the parallel pulse transmission characteristic of pulse coupled neural networks, the method is able to find k shortest paths quickly. The computational complexity is only related to the length of the longest shortest path. Simulative results for route planning show that the proposed MCPCNN method for KSPs computation outperforms many other current efficient algorithms. Pulse coupled neural network Elsevier Single-pair KSP Elsevier Single-source KSP Elsevier k Shortest paths Elsevier Qiu, Zhao oth Qu, Hong oth Ji, Luping oth Enthalten in Elsevier Liu, Yang ELSEVIER The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast 2018 an international journal Amsterdam (DE-627)ELV002603926 volume:149 year:2015 day:3 month:02 pages:1162-1176 extent:15 https://doi.org/10.1016/j.neucom.2014.09.012 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 35.70 Biochemie: Allgemeines VZ 42.12 Biophysik VZ AR 149 2015 3 0203 1162-1176 15 045F 610 |
| spelling |
10.1016/j.neucom.2014.09.012 doi GBVA2015014000023.pica (DE-627)ELV018590845 (ELSEVIER)S0925-2312(14)01168-0 DE-627 ger DE-627 rakwb eng 610 610 DE-600 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl Liu, Guisong verfasserin aut Computing k shortest paths using modified pulse-coupled neural network 2015transfer abstract 15 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The K Shortest Paths (KSPs) problem with non-numerable applications has been researched widely, which aims to compute KSPs between two nodes in a non-decreasing order. However, less effort has been devoted to single-source KSP problem than to single-pair KSP computation, especially by using parallel methods. This paper proposes a Modified Continued Pulse Coupled Neural Network (MCPCNN) model to solve the two kinds of KSP problems. Theoretical analysis of MCPCNN and two algorithms for KSPs computation are presented. By using the parallel pulse transmission characteristic of pulse coupled neural networks, the method is able to find k shortest paths quickly. The computational complexity is only related to the length of the longest shortest path. Simulative results for route planning show that the proposed MCPCNN method for KSPs computation outperforms many other current efficient algorithms. The K Shortest Paths (KSPs) problem with non-numerable applications has been researched widely, which aims to compute KSPs between two nodes in a non-decreasing order. However, less effort has been devoted to single-source KSP problem than to single-pair KSP computation, especially by using parallel methods. This paper proposes a Modified Continued Pulse Coupled Neural Network (MCPCNN) model to solve the two kinds of KSP problems. Theoretical analysis of MCPCNN and two algorithms for KSPs computation are presented. By using the parallel pulse transmission characteristic of pulse coupled neural networks, the method is able to find k shortest paths quickly. The computational complexity is only related to the length of the longest shortest path. Simulative results for route planning show that the proposed MCPCNN method for KSPs computation outperforms many other current efficient algorithms. Pulse coupled neural network Elsevier Single-pair KSP Elsevier Single-source KSP Elsevier k Shortest paths Elsevier Qiu, Zhao oth Qu, Hong oth Ji, Luping oth Enthalten in Elsevier Liu, Yang ELSEVIER The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast 2018 an international journal Amsterdam (DE-627)ELV002603926 volume:149 year:2015 day:3 month:02 pages:1162-1176 extent:15 https://doi.org/10.1016/j.neucom.2014.09.012 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 35.70 Biochemie: Allgemeines VZ 42.12 Biophysik VZ AR 149 2015 3 0203 1162-1176 15 045F 610 |
| allfields_unstemmed |
10.1016/j.neucom.2014.09.012 doi GBVA2015014000023.pica (DE-627)ELV018590845 (ELSEVIER)S0925-2312(14)01168-0 DE-627 ger DE-627 rakwb eng 610 610 DE-600 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl Liu, Guisong verfasserin aut Computing k shortest paths using modified pulse-coupled neural network 2015transfer abstract 15 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The K Shortest Paths (KSPs) problem with non-numerable applications has been researched widely, which aims to compute KSPs between two nodes in a non-decreasing order. However, less effort has been devoted to single-source KSP problem than to single-pair KSP computation, especially by using parallel methods. This paper proposes a Modified Continued Pulse Coupled Neural Network (MCPCNN) model to solve the two kinds of KSP problems. Theoretical analysis of MCPCNN and two algorithms for KSPs computation are presented. By using the parallel pulse transmission characteristic of pulse coupled neural networks, the method is able to find k shortest paths quickly. The computational complexity is only related to the length of the longest shortest path. Simulative results for route planning show that the proposed MCPCNN method for KSPs computation outperforms many other current efficient algorithms. The K Shortest Paths (KSPs) problem with non-numerable applications has been researched widely, which aims to compute KSPs between two nodes in a non-decreasing order. However, less effort has been devoted to single-source KSP problem than to single-pair KSP computation, especially by using parallel methods. This paper proposes a Modified Continued Pulse Coupled Neural Network (MCPCNN) model to solve the two kinds of KSP problems. Theoretical analysis of MCPCNN and two algorithms for KSPs computation are presented. By using the parallel pulse transmission characteristic of pulse coupled neural networks, the method is able to find k shortest paths quickly. The computational complexity is only related to the length of the longest shortest path. Simulative results for route planning show that the proposed MCPCNN method for KSPs computation outperforms many other current efficient algorithms. Pulse coupled neural network Elsevier Single-pair KSP Elsevier Single-source KSP Elsevier k Shortest paths Elsevier Qiu, Zhao oth Qu, Hong oth Ji, Luping oth Enthalten in Elsevier Liu, Yang ELSEVIER The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast 2018 an international journal Amsterdam (DE-627)ELV002603926 volume:149 year:2015 day:3 month:02 pages:1162-1176 extent:15 https://doi.org/10.1016/j.neucom.2014.09.012 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 35.70 Biochemie: Allgemeines VZ 42.12 Biophysik VZ AR 149 2015 3 0203 1162-1176 15 045F 610 |
| allfieldsGer |
10.1016/j.neucom.2014.09.012 doi GBVA2015014000023.pica (DE-627)ELV018590845 (ELSEVIER)S0925-2312(14)01168-0 DE-627 ger DE-627 rakwb eng 610 610 DE-600 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl Liu, Guisong verfasserin aut Computing k shortest paths using modified pulse-coupled neural network 2015transfer abstract 15 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The K Shortest Paths (KSPs) problem with non-numerable applications has been researched widely, which aims to compute KSPs between two nodes in a non-decreasing order. However, less effort has been devoted to single-source KSP problem than to single-pair KSP computation, especially by using parallel methods. This paper proposes a Modified Continued Pulse Coupled Neural Network (MCPCNN) model to solve the two kinds of KSP problems. Theoretical analysis of MCPCNN and two algorithms for KSPs computation are presented. By using the parallel pulse transmission characteristic of pulse coupled neural networks, the method is able to find k shortest paths quickly. The computational complexity is only related to the length of the longest shortest path. Simulative results for route planning show that the proposed MCPCNN method for KSPs computation outperforms many other current efficient algorithms. The K Shortest Paths (KSPs) problem with non-numerable applications has been researched widely, which aims to compute KSPs between two nodes in a non-decreasing order. However, less effort has been devoted to single-source KSP problem than to single-pair KSP computation, especially by using parallel methods. This paper proposes a Modified Continued Pulse Coupled Neural Network (MCPCNN) model to solve the two kinds of KSP problems. Theoretical analysis of MCPCNN and two algorithms for KSPs computation are presented. By using the parallel pulse transmission characteristic of pulse coupled neural networks, the method is able to find k shortest paths quickly. The computational complexity is only related to the length of the longest shortest path. Simulative results for route planning show that the proposed MCPCNN method for KSPs computation outperforms many other current efficient algorithms. Pulse coupled neural network Elsevier Single-pair KSP Elsevier Single-source KSP Elsevier k Shortest paths Elsevier Qiu, Zhao oth Qu, Hong oth Ji, Luping oth Enthalten in Elsevier Liu, Yang ELSEVIER The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast 2018 an international journal Amsterdam (DE-627)ELV002603926 volume:149 year:2015 day:3 month:02 pages:1162-1176 extent:15 https://doi.org/10.1016/j.neucom.2014.09.012 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 35.70 Biochemie: Allgemeines VZ 42.12 Biophysik VZ AR 149 2015 3 0203 1162-1176 15 045F 610 |
| allfieldsSound |
10.1016/j.neucom.2014.09.012 doi GBVA2015014000023.pica (DE-627)ELV018590845 (ELSEVIER)S0925-2312(14)01168-0 DE-627 ger DE-627 rakwb eng 610 610 DE-600 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl Liu, Guisong verfasserin aut Computing k shortest paths using modified pulse-coupled neural network 2015transfer abstract 15 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The K Shortest Paths (KSPs) problem with non-numerable applications has been researched widely, which aims to compute KSPs between two nodes in a non-decreasing order. However, less effort has been devoted to single-source KSP problem than to single-pair KSP computation, especially by using parallel methods. This paper proposes a Modified Continued Pulse Coupled Neural Network (MCPCNN) model to solve the two kinds of KSP problems. Theoretical analysis of MCPCNN and two algorithms for KSPs computation are presented. By using the parallel pulse transmission characteristic of pulse coupled neural networks, the method is able to find k shortest paths quickly. The computational complexity is only related to the length of the longest shortest path. Simulative results for route planning show that the proposed MCPCNN method for KSPs computation outperforms many other current efficient algorithms. The K Shortest Paths (KSPs) problem with non-numerable applications has been researched widely, which aims to compute KSPs between two nodes in a non-decreasing order. However, less effort has been devoted to single-source KSP problem than to single-pair KSP computation, especially by using parallel methods. This paper proposes a Modified Continued Pulse Coupled Neural Network (MCPCNN) model to solve the two kinds of KSP problems. Theoretical analysis of MCPCNN and two algorithms for KSPs computation are presented. By using the parallel pulse transmission characteristic of pulse coupled neural networks, the method is able to find k shortest paths quickly. The computational complexity is only related to the length of the longest shortest path. Simulative results for route planning show that the proposed MCPCNN method for KSPs computation outperforms many other current efficient algorithms. Pulse coupled neural network Elsevier Single-pair KSP Elsevier Single-source KSP Elsevier k Shortest paths Elsevier Qiu, Zhao oth Qu, Hong oth Ji, Luping oth Enthalten in Elsevier Liu, Yang ELSEVIER The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast 2018 an international journal Amsterdam (DE-627)ELV002603926 volume:149 year:2015 day:3 month:02 pages:1162-1176 extent:15 https://doi.org/10.1016/j.neucom.2014.09.012 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 35.70 Biochemie: Allgemeines VZ 42.12 Biophysik VZ AR 149 2015 3 0203 1162-1176 15 045F 610 |
| language |
English |
| source |
Enthalten in The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast Amsterdam volume:149 year:2015 day:3 month:02 pages:1162-1176 extent:15 |
| sourceStr |
Enthalten in The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast Amsterdam volume:149 year:2015 day:3 month:02 pages:1162-1176 extent:15 |
| format_phy_str_mv |
Article |
| bklname |
Biochemie: Allgemeines Biophysik |
| institution |
findex.gbv.de |
| topic_facet |
Pulse coupled neural network Single-pair KSP Single-source KSP k Shortest paths |
| dewey-raw |
610 |
| isfreeaccess_bool |
false |
| container_title |
The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast |
| authorswithroles_txt_mv |
Liu, Guisong @@aut@@ Qiu, Zhao @@oth@@ Qu, Hong @@oth@@ Ji, Luping @@oth@@ |
| publishDateDaySort_date |
2015-01-03T00:00:00Z |
| hierarchy_top_id |
ELV002603926 |
| dewey-sort |
3610 |
| id |
ELV018590845 |
| language_de |
englisch |
| fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV018590845</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230625124310.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">180602s2015 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.neucom.2014.09.012</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">GBVA2015014000023.pica</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV018590845</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S0925-2312(14)01168-0</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">610</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">610</subfield><subfield code="q">DE-600</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">570</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">BIODIV</subfield><subfield code="q">DE-30</subfield><subfield code="2">fid</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">35.70</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">42.12</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Liu, Guisong</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Computing k shortest paths using modified pulse-coupled neural network</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2015transfer abstract</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">15</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">z</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zu</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">The K Shortest Paths (KSPs) problem with non-numerable applications has been researched widely, which aims to compute KSPs between two nodes in a non-decreasing order. However, less effort has been devoted to single-source KSP problem than to single-pair KSP computation, especially by using parallel methods. This paper proposes a Modified Continued Pulse Coupled Neural Network (MCPCNN) model to solve the two kinds of KSP problems. Theoretical analysis of MCPCNN and two algorithms for KSPs computation are presented. By using the parallel pulse transmission characteristic of pulse coupled neural networks, the method is able to find k shortest paths quickly. The computational complexity is only related to the length of the longest shortest path. Simulative results for route planning show that the proposed MCPCNN method for KSPs computation outperforms many other current efficient algorithms.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">The K Shortest Paths (KSPs) problem with non-numerable applications has been researched widely, which aims to compute KSPs between two nodes in a non-decreasing order. However, less effort has been devoted to single-source KSP problem than to single-pair KSP computation, especially by using parallel methods. This paper proposes a Modified Continued Pulse Coupled Neural Network (MCPCNN) model to solve the two kinds of KSP problems. Theoretical analysis of MCPCNN and two algorithms for KSPs computation are presented. By using the parallel pulse transmission characteristic of pulse coupled neural networks, the method is able to find k shortest paths quickly. The computational complexity is only related to the length of the longest shortest path. Simulative results for route planning show that the proposed MCPCNN method for KSPs computation outperforms many other current efficient algorithms.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Pulse coupled neural network</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Single-pair KSP</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Single-source KSP</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">k Shortest paths</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Qiu, Zhao</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Qu, Hong</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Ji, Luping</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Elsevier</subfield><subfield code="a">Liu, Yang ELSEVIER</subfield><subfield code="t">The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast</subfield><subfield code="d">2018</subfield><subfield code="d">an international journal</subfield><subfield code="g">Amsterdam</subfield><subfield code="w">(DE-627)ELV002603926</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:149</subfield><subfield code="g">year:2015</subfield><subfield code="g">day:3</subfield><subfield code="g">month:02</subfield><subfield code="g">pages:1162-1176</subfield><subfield code="g">extent:15</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.neucom.2014.09.012</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">FID-BIODIV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHA</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">35.70</subfield><subfield code="j">Biochemie: Allgemeines</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">42.12</subfield><subfield code="j">Biophysik</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">149</subfield><subfield code="j">2015</subfield><subfield code="b">3</subfield><subfield code="c">0203</subfield><subfield code="h">1162-1176</subfield><subfield code="g">15</subfield></datafield><datafield tag="953" ind1=" " ind2=" "><subfield code="2">045F</subfield><subfield code="a">610</subfield></datafield></record></collection>
|
| author |
Liu, Guisong |
| spellingShingle |
Liu, Guisong ddc 610 ddc 570 fid BIODIV bkl 35.70 bkl 42.12 Elsevier Pulse coupled neural network Elsevier Single-pair KSP Elsevier Single-source KSP Elsevier k Shortest paths Computing k shortest paths using modified pulse-coupled neural network |
| authorStr |
Liu, Guisong |
| ppnlink_with_tag_str_mv |
@@773@@(DE-627)ELV002603926 |
| format |
electronic Article |
| dewey-ones |
610 - Medicine & health 570 - Life sciences; biology |
| delete_txt_mv |
keep |
| author_role |
aut |
| collection |
elsevier |
| remote_str |
true |
| illustrated |
Not Illustrated |
| topic_title |
610 610 DE-600 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl Computing k shortest paths using modified pulse-coupled neural network Pulse coupled neural network Elsevier Single-pair KSP Elsevier Single-source KSP Elsevier k Shortest paths Elsevier |
| topic |
ddc 610 ddc 570 fid BIODIV bkl 35.70 bkl 42.12 Elsevier Pulse coupled neural network Elsevier Single-pair KSP Elsevier Single-source KSP Elsevier k Shortest paths |
| topic_unstemmed |
ddc 610 ddc 570 fid BIODIV bkl 35.70 bkl 42.12 Elsevier Pulse coupled neural network Elsevier Single-pair KSP Elsevier Single-source KSP Elsevier k Shortest paths |
| topic_browse |
ddc 610 ddc 570 fid BIODIV bkl 35.70 bkl 42.12 Elsevier Pulse coupled neural network Elsevier Single-pair KSP Elsevier Single-source KSP Elsevier k Shortest paths |
| format_facet |
Elektronische Aufsätze Aufsätze Elektronische Ressource |
| format_main_str_mv |
Text Zeitschrift/Artikel |
| carriertype_str_mv |
zu |
| author2_variant |
z q zq h q hq l j lj |
| hierarchy_parent_title |
The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast |
| hierarchy_parent_id |
ELV002603926 |
| dewey-tens |
610 - Medicine & health 570 - Life sciences; biology |
| hierarchy_top_title |
The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast |
| isfreeaccess_txt |
false |
| familylinks_str_mv |
(DE-627)ELV002603926 |
| title |
Computing k shortest paths using modified pulse-coupled neural network |
| ctrlnum |
(DE-627)ELV018590845 (ELSEVIER)S0925-2312(14)01168-0 |
| title_full |
Computing k shortest paths using modified pulse-coupled neural network |
| author_sort |
Liu, Guisong |
| journal |
The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast |
| journalStr |
The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast |
| lang_code |
eng |
| isOA_bool |
false |
| dewey-hundreds |
600 - Technology 500 - Science |
| recordtype |
marc |
| publishDateSort |
2015 |
| contenttype_str_mv |
zzz |
| container_start_page |
1162 |
| author_browse |
Liu, Guisong |
| container_volume |
149 |
| physical |
15 |
| class |
610 610 DE-600 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl |
| format_se |
Elektronische Aufsätze |
| author-letter |
Liu, Guisong |
| doi_str_mv |
10.1016/j.neucom.2014.09.012 |
| dewey-full |
610 570 |
| title_sort |
computing k shortest paths using modified pulse-coupled neural network |
| title_auth |
Computing k shortest paths using modified pulse-coupled neural network |
| abstract |
The K Shortest Paths (KSPs) problem with non-numerable applications has been researched widely, which aims to compute KSPs between two nodes in a non-decreasing order. However, less effort has been devoted to single-source KSP problem than to single-pair KSP computation, especially by using parallel methods. This paper proposes a Modified Continued Pulse Coupled Neural Network (MCPCNN) model to solve the two kinds of KSP problems. Theoretical analysis of MCPCNN and two algorithms for KSPs computation are presented. By using the parallel pulse transmission characteristic of pulse coupled neural networks, the method is able to find k shortest paths quickly. The computational complexity is only related to the length of the longest shortest path. Simulative results for route planning show that the proposed MCPCNN method for KSPs computation outperforms many other current efficient algorithms. |
| abstractGer |
The K Shortest Paths (KSPs) problem with non-numerable applications has been researched widely, which aims to compute KSPs between two nodes in a non-decreasing order. However, less effort has been devoted to single-source KSP problem than to single-pair KSP computation, especially by using parallel methods. This paper proposes a Modified Continued Pulse Coupled Neural Network (MCPCNN) model to solve the two kinds of KSP problems. Theoretical analysis of MCPCNN and two algorithms for KSPs computation are presented. By using the parallel pulse transmission characteristic of pulse coupled neural networks, the method is able to find k shortest paths quickly. The computational complexity is only related to the length of the longest shortest path. Simulative results for route planning show that the proposed MCPCNN method for KSPs computation outperforms many other current efficient algorithms. |
| abstract_unstemmed |
The K Shortest Paths (KSPs) problem with non-numerable applications has been researched widely, which aims to compute KSPs between two nodes in a non-decreasing order. However, less effort has been devoted to single-source KSP problem than to single-pair KSP computation, especially by using parallel methods. This paper proposes a Modified Continued Pulse Coupled Neural Network (MCPCNN) model to solve the two kinds of KSP problems. Theoretical analysis of MCPCNN and two algorithms for KSPs computation are presented. By using the parallel pulse transmission characteristic of pulse coupled neural networks, the method is able to find k shortest paths quickly. The computational complexity is only related to the length of the longest shortest path. Simulative results for route planning show that the proposed MCPCNN method for KSPs computation outperforms many other current efficient algorithms. |
| collection_details |
GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA |
| title_short |
Computing k shortest paths using modified pulse-coupled neural network |
| url |
https://doi.org/10.1016/j.neucom.2014.09.012 |
| remote_bool |
true |
| author2 |
Qiu, Zhao Qu, Hong Ji, Luping |
| author2Str |
Qiu, Zhao Qu, Hong Ji, Luping |
| ppnlink |
ELV002603926 |
| mediatype_str_mv |
z |
| isOA_txt |
false |
| hochschulschrift_bool |
false |
| author2_role |
oth oth oth |
| doi_str |
10.1016/j.neucom.2014.09.012 |
| up_date |
2024-07-06T19:12:24.167Z |
| _version_ |
1803858103938056192 |
| fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV018590845</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230625124310.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">180602s2015 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.neucom.2014.09.012</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">GBVA2015014000023.pica</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV018590845</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S0925-2312(14)01168-0</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">610</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">610</subfield><subfield code="q">DE-600</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">570</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">BIODIV</subfield><subfield code="q">DE-30</subfield><subfield code="2">fid</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">35.70</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">42.12</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Liu, Guisong</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Computing k shortest paths using modified pulse-coupled neural network</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2015transfer abstract</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">15</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">z</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zu</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">The K Shortest Paths (KSPs) problem with non-numerable applications has been researched widely, which aims to compute KSPs between two nodes in a non-decreasing order. However, less effort has been devoted to single-source KSP problem than to single-pair KSP computation, especially by using parallel methods. This paper proposes a Modified Continued Pulse Coupled Neural Network (MCPCNN) model to solve the two kinds of KSP problems. Theoretical analysis of MCPCNN and two algorithms for KSPs computation are presented. By using the parallel pulse transmission characteristic of pulse coupled neural networks, the method is able to find k shortest paths quickly. The computational complexity is only related to the length of the longest shortest path. Simulative results for route planning show that the proposed MCPCNN method for KSPs computation outperforms many other current efficient algorithms.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">The K Shortest Paths (KSPs) problem with non-numerable applications has been researched widely, which aims to compute KSPs between two nodes in a non-decreasing order. However, less effort has been devoted to single-source KSP problem than to single-pair KSP computation, especially by using parallel methods. This paper proposes a Modified Continued Pulse Coupled Neural Network (MCPCNN) model to solve the two kinds of KSP problems. Theoretical analysis of MCPCNN and two algorithms for KSPs computation are presented. By using the parallel pulse transmission characteristic of pulse coupled neural networks, the method is able to find k shortest paths quickly. The computational complexity is only related to the length of the longest shortest path. Simulative results for route planning show that the proposed MCPCNN method for KSPs computation outperforms many other current efficient algorithms.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Pulse coupled neural network</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Single-pair KSP</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Single-source KSP</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">k Shortest paths</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Qiu, Zhao</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Qu, Hong</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Ji, Luping</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Elsevier</subfield><subfield code="a">Liu, Yang ELSEVIER</subfield><subfield code="t">The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast</subfield><subfield code="d">2018</subfield><subfield code="d">an international journal</subfield><subfield code="g">Amsterdam</subfield><subfield code="w">(DE-627)ELV002603926</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:149</subfield><subfield code="g">year:2015</subfield><subfield code="g">day:3</subfield><subfield code="g">month:02</subfield><subfield code="g">pages:1162-1176</subfield><subfield code="g">extent:15</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.neucom.2014.09.012</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">FID-BIODIV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHA</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">35.70</subfield><subfield code="j">Biochemie: Allgemeines</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">42.12</subfield><subfield code="j">Biophysik</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">149</subfield><subfield code="j">2015</subfield><subfield code="b">3</subfield><subfield code="c">0203</subfield><subfield code="h">1162-1176</subfield><subfield code="g">15</subfield></datafield><datafield tag="953" ind1=" " ind2=" "><subfield code="2">045F</subfield><subfield code="a">610</subfield></datafield></record></collection>
|
| score |
7.401247 |