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
Autor*in: |
Liu, Guisong [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2015transfer abstract |
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Schlagwörter: |
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Umfang: |
15 |
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Übergeordnetes Werk: |
Enthalten in: The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast - Liu, Yang ELSEVIER, 2018, an international journal, Amsterdam |
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Übergeordnetes Werk: |
volume:149 ; year:2015 ; day:3 ; month:02 ; pages:1162-1176 ; extent:15 |
Links: |
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DOI / URN: |
10.1016/j.neucom.2014.09.012 |
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Katalog-ID: |
ELV018590845 |
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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. | ||
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2015 |
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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 |
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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 |
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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 |
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The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast |
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author |
Liu, Guisong |
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The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast |
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The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast |
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The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast |
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computing k shortest paths using modified pulse-coupled neural network |
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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. |
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Computing k shortest paths using modified pulse-coupled neural network |
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https://doi.org/10.1016/j.neucom.2014.09.012 |
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Qiu, Zhao Qu, Hong Ji, Luping |
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