Critical analysis of hopfield's neural network model and heuristic algorithm for shortest path computation for routing in computer networks

dc.contributor.authorFarah Sarwar
dc.contributor.authorAbdul Aziz Bhatti
dc.date.accessioned2012-12-05T13:33:16Z
dc.date.available2012-12-05T13:33:16Z
dc.date.issued2012
dc.description.abstractShortest path routing and its computation is a crucial point in computer networks, and has significant impact on overall network's performance. Being an issue of salient importance, many algorithms were proposed for shortest path computation and are still under research for more enhancements. Hopfield proposed a neural network based architecture for such optimization problems. Mehmet and Park Keum suggested improved energy functions for this neural network to implement it for routing in computer networks. A * search algorithm is a heuristic based approach, with the properties of Dijikstra algorithm and is used for same purpose. Performances of both approaches are compared and results are analyzed.en_US
dc.identifier.citationProceedings of 2012 9th International Bhurban Conference on Applied Sciences & Technology (IBCAST) Islamabad, Pakistan, 9th - 12th January, 2012en_US
dc.identifier.isbn978-1-4577-1929-5
dc.identifier.urihttps://escholar.umt.edu.pk/handle/123456789/651
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectElectrical Engineeringen_US
dc.subjectApplied Sciencesen_US
dc.subjectShortest Path Computationen_US
dc.titleCritical analysis of hopfield's neural network model and heuristic algorithm for shortest path computation for routing in computer networksen_US
dc.typeConference Paperen_US
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