1. STORRE
  2. Faculty of Natural Sciences
  3. Computing Science and Mathematics
  4. Computing Science and Mathematics Journal Articles
Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/16536
Full metadata record
DC FieldValueLanguage
dc.contributor.authorJaudet, Mohammaden_UK
dc.contributor.authorIqbal, Naeemen_UK
dc.contributor.authorMirza, Nasir Men_UK
dc.contributor.authorMirza, Sikander Men_UK
dc.contributor.authorHussain, Amiren_UK
dc.date.accessioned2013-08-28T23:16:30Z-
dc.date.available2013-08-28T23:16:30Zen_UK
dc.date.issued2007-04en_UK
dc.identifier.urihttp://hdl.handle.net/1893/16536-
dc.description.abstractModeling of network-faults based time-sequence data by piecewise constant intensity function has been carried out using a heuristic approach that employs both Markov Chain Monte Carlo approach (MCMC) and Dynamic Programming algorithm (DPA) methodologies. The results for synthetic as well as for real data show that both MCMC and DPA have close agreement between predicted and actual values. Remarkable speedup (4 to 5 times) has been observed by augmentation of the heuristic method. Due to higher efficiency the proposed approach is well suited for cases with larger data sets requiring near-optimal solution.en_UK
dc.language.isoenen_UK
dc.publisherInternational Journal of Computer Science and Network Securityen_UK
dc.relationJaudet M, Iqbal N, Mirza NM, Mirza SM & Hussain A (2007) Comparative Study of Heuristic Hybrid of Markov Chain Monte Carlo and Dynamic Programming Methodologies for Network Fault Analysis. International Journal of Computer Science and Network Security, 7 (4), pp. 32-41. http://paper.ijcsns.org/07_book/200704/20070405.pdfen_UK
dc.rightsThe publisher has not yet responded to our queries therefore this work cannot be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study.en_UK
dc.rights.urihttp://www.rioxx.net/licenses/under-embargo-all-rights-reserveden_UK
dc.subjectData miningen_UK
dc.subjectDynamic programmingen_UK
dc.subjectEvent sequenceen_UK
dc.subjectChange-pointsen_UK
dc.subjectMaximum likelihooden_UK
dc.subjectMCMCen_UK
dc.titleComparative Study of Heuristic Hybrid of Markov Chain Monte Carlo and Dynamic Programming Methodologies for Network Fault Analysisen_UK
dc.typeJournal Articleen_UK
dc.rights.embargodate2999-12-31en_UK
dc.rights.embargoreason[Comparative Study of Heuristic Hybrid of Markov Chain Monte.pdf] The publisher has not yet responded to our queries. This work cannot be made publicly available in this Repository therefore there is an embargo on the full text of the work.en_UK
dc.citation.jtitleInternational Journal of Computer Science and Network Securityen_UK
dc.citation.issn1738-7906en_UK
dc.citation.volume7en_UK
dc.citation.issue4en_UK
dc.citation.spage32en_UK
dc.citation.epage41en_UK
dc.citation.publicationstatusPublisheden_UK
dc.citation.peerreviewedRefereeden_UK
dc.type.statusVoR - Version of Recorden_UK
dc.identifier.urlhttp://paper.ijcsns.org/07_book/200704/20070405.pdfen_UK
dc.author.emailamir.hussain@stir.ac.uken_UK
dc.contributor.affiliationPakistan Institute of Engineering and Applied Sciencesen_UK
dc.contributor.affiliationPakistan Institute of Engineering and Applied Sciencesen_UK
dc.contributor.affiliationPakistan Institute of Engineering and Applied Sciencesen_UK
dc.contributor.affiliationPakistan Institute of Engineering and Applied Sciencesen_UK
dc.contributor.affiliationComputing Scienceen_UK
dc.identifier.wtid681643en_UK
dc.contributor.orcid0000-0002-8080-082Xen_UK
dcterms.dateAccepted2007-04-30en_UK
dc.date.filedepositdate2013-08-27en_UK
rioxxterms.typeJournal Article/Reviewen_UK
rioxxterms.versionVoRen_UK
local.rioxx.authorJaudet, Mohammad|en_UK
local.rioxx.authorIqbal, Naeem|en_UK
local.rioxx.authorMirza, Nasir M|en_UK
local.rioxx.authorMirza, Sikander M|en_UK
local.rioxx.authorHussain, Amir|0000-0002-8080-082Xen_UK
local.rioxx.projectInternal Project|University of Stirling|https://isni.org/isni/0000000122484331en_UK
local.rioxx.freetoreaddate2999-12-31en_UK
local.rioxx.licencehttp://www.rioxx.net/licenses/under-embargo-all-rights-reserved||en_UK
local.rioxx.filenameComparative Study of Heuristic Hybrid of Markov Chain Monte.pdfen_UK
local.rioxx.filecount1en_UK
local.rioxx.source1738-7906en_UK
Appears in Collections:Computing Science and Mathematics Journal Articles

Files in This Item:
File Description SizeFormat 
Comparative Study of Heuristic Hybrid of Markov Chain Monte.pdfFulltext - Published Version849.8 kBAdobe PDFUnder Permanent Embargo    Request a copy


This item is protected by original copyright

View License
Show simple item record


Items in the Repository are protected by copyright, with all rights reserved, unless otherwise indicated.

The metadata of the records in the Repository are available under the CC0 public domain dedication: No Rights Reserved https://creativecommons.org/publicdomain/zero/1.0/

If you believe that any material held in STORRE infringes copyright, please contact library@stir.ac.uk providing details and we will remove the Work from public display in STORRE and investigate your claim.