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dc.contributor.authorSingh A.-
dc.contributor.authorDeep, K.-
dc.contributor.editorBansal J.C.-
dc.contributor.editorNagar A.-
dc.contributor.editorOjha A.K.-
dc.contributor.editorDas K.N.-
dc.contributor.editorDeep K.-
dc.identifier.citationProceedings of Advances in Intelligent Systems and Computing, (2019), 185- 197-
dc.description.abstractGravitational Search Algorithm (GSA) is a memory-less, nature-inspired algorithm for nonlinear continuous optimization problems. In Singh et al. (a new Improved Gravitational Search Algorithm for function optimization using a novel “best-so-far†update mechanism. IEEE, pp. 35–39 (2015) [21]), Singh and Deep proposed an Improved GSA using best-so-far mechanism. In this paper, the problem of 3D reconstruction is modelled as a nonlinear optimization problem. GSA and Improved GSA are used to solve three reconstruction problems. Based on the several computational experiments and analysis, it is concluded that the performance of improved GSA is better than original GSA in terms of convergence and solution quality. © Springer Nature Singapore Pte Ltd. 2019.-
dc.publisherSpringer Verlag-
dc.relation.ispartofProceedings of Advances in Intelligent Systems and Computing-
dc.subjectContinuous function optimization-
dc.subjectGravitational search algorithm-
dc.subjectHeuristic technique-
dc.subjectHeuristic methods-
dc.subjectImage reconstruction-
dc.subjectLearning algorithms-
dc.subjectNonlinear programming-
dc.subjectSoft computing-
dc.subjectContinuous function optimization-
dc.subjectContinuous optimization problems-
dc.subjectGravitational search algorithm (GSA)-
dc.subjectGravitational search algorithms-
dc.subjectHeuristic techniques-
dc.subjectNature inspired algorithms-
dc.subjectNon-linear optimization problems-
dc.subjectProblem solving-
dc.titleUse of improved gravitational search algorithm for 3D reconstruction of space curves using NURBS-
dc.typeConference Paper-
dc.affiliationSingh, A., Department of Mathematics, Janki Devi Memorial College, University of Delhi, New Delhi, 110060, India-
dc.affiliationDeep, K., Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, Uttrakhand 247667, India-
dc.description.correspondingauthorSingh, A.; Department of Mathematics, Janki Devi Memorial College, University of DelhiIndia; email:
dc.identifier.conferencedetails7th International Conference on Soft Computing for Problem Solving, SocProS 2017, 23-24 December 2017-
Appears in Collections:Conference Publications [MA]

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