2012
DOI: 10.3923/jas.2012.822.830
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A Novel Quantum-inspired Binary Gravitational Search Algorithm in Obtaining Optimal Power Quality Monitor Placement

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Cited by 31 publications
(16 citation statements)
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“…In this section we apply the BIGSA for feature selection to various datasets, in comparison with other methods including GA [16], BPSO [15], QBPSO [18], and BGSA [19] for simultaneous feature selection and classification.…”
Section: Experimental Results For Feature Selection Based On Bigsamentioning
confidence: 99%
See 1 more Smart Citation
“…In this section we apply the BIGSA for feature selection to various datasets, in comparison with other methods including GA [16], BPSO [15], QBPSO [18], and BGSA [19] for simultaneous feature selection and classification.…”
Section: Experimental Results For Feature Selection Based On Bigsamentioning
confidence: 99%
“…A probability function is restricted within 0 to 1 interval such that as x d i increases, probability increases too, which is defined as Eq. (19).…”
Section: Binary Improved Gravitational Search Algorithmmentioning
confidence: 95%
“…Also, to improve the conventional rotation gate for updating the Q-bit individual, a new rotation gate has been proposed including a coordinate rotation gate for updating Q-bits, and a dynamic rotation angle approach for determining the magnitude of rotation angle. Inspired by BQIPSO and BGSA a version of the quantum binary GSA (BQGSA) has been proposed (Ibrahim et al, 2012). This algorithm is proposed based on the rotation gate where the rotation angle is used to determine the new position of the agent.…”
Section: Related Workmentioning
confidence: 99%
“…29 The second weakness was the best agent is still exploring the global space even it was at the best position. 30 To tackle these weaknesses, we propose an IGSA, which aims to improve the quality of the solution and to get the fastest convergence. In the proposed IGSA, the chaotic dynamics is applied for the purpose of improvement in the searching behavior and to avoid the premature convergence.…”
Section: Proposed Algorithmmentioning
confidence: 99%
“…27,28 There are some weaknesses in the GSA process for searching the best solution. 29,30 This paper proposes a new and improved GSA (IGSA) for determining the optimal placement and sizing of DG in a radial distribution system by minimizing the losses, THD v , and voltage deviation. The assumption has been made in this simulation where the distribution system is a balanced system due to the installation of single-phase renewable DG units (rooftop PVs solar) are similar for each phases.…”
Section: Introductionmentioning
confidence: 99%