A Novel Hybrid Bacteria-chemotaxis Spiral-dynamic Algorithm with Application to Modelling of Flexible Systems
This paper presents a novel hybrid optimisation algorithm namely HBCSD, which synergises a bacterial foraging algorithm (BFA) and spiral dynamics algorithm (SDA). The main objective of this strategy is to develop an algorithm that is capable to reach a global optimum point at the end of the final so...
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ump-77912018-03-19T05:56:04Z http://umpir.ump.edu.my/id/eprint/7791/ A Novel Hybrid Bacteria-chemotaxis Spiral-dynamic Algorithm with Application to Modelling of Flexible Systems Ahmad Nor Kasruddin, Nasir Tokhi, M. O. Q Science (General) This paper presents a novel hybrid optimisation algorithm namely HBCSD, which synergises a bacterial foraging algorithm (BFA) and spiral dynamics algorithm (SDA). The main objective of this strategy is to develop an algorithm that is capable to reach a global optimum point at the end of the final solution with a faster convergence speed compared to its predecessor algorithms. The BFA is incorporated into the algorithm to act as a global search or exploration phase. The solutions from the exploration phase then feed into SDA, which acts as a local search or exploitation phase. The proposed algorithm is used in dynamic modelling of two types of flexible systems, namely a flexible robot manipulator and a twin rotor system. The results obtained show that the proposed algorithm outperforms its predecessor algorithms in terms of fitness accuracy, convergence speed, and time-domain and frequency-domain dynamic characterisation of the two flexible systems. Elsevier 2014-05-04 Article PeerReviewed Ahmad Nor Kasruddin, Nasir and Tokhi, M. O. (2014) A Novel Hybrid Bacteria-chemotaxis Spiral-dynamic Algorithm with Application to Modelling of Flexible Systems. Engineering Applications of Artificial Intelligence, 33. pp. 31-46. ISSN 0952-1976 http://dx.doi.org/10.1016/j.engappai.2014.04.001 DOI: 10.1016/j.engappai.2014.04.001 |
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Q Science (General) Ahmad Nor Kasruddin, Nasir Tokhi, M. O. A Novel Hybrid Bacteria-chemotaxis Spiral-dynamic Algorithm with Application to Modelling of Flexible Systems |
description |
This paper presents a novel hybrid optimisation algorithm namely HBCSD, which synergises a bacterial foraging algorithm (BFA) and spiral dynamics algorithm (SDA). The main objective of this strategy is to develop an algorithm that is capable to reach a global optimum point at the end of the final solution with a faster convergence speed compared to its predecessor algorithms. The BFA is incorporated into the algorithm to act as a global search or exploration phase. The solutions from the exploration phase then feed into SDA, which acts as a local search or exploitation phase. The proposed algorithm is used in dynamic modelling of two types of flexible systems, namely a flexible robot manipulator and a twin rotor system. The results obtained show that the proposed algorithm outperforms its predecessor algorithms in terms of fitness accuracy, convergence speed, and time-domain and frequency-domain dynamic characterisation of the two flexible systems. |
format |
Article |
author |
Ahmad Nor Kasruddin, Nasir Tokhi, M. O. |
author_facet |
Ahmad Nor Kasruddin, Nasir Tokhi, M. O. |
author_sort |
Ahmad Nor Kasruddin, Nasir |
title |
A Novel Hybrid Bacteria-chemotaxis Spiral-dynamic Algorithm with Application to Modelling of Flexible Systems |
title_short |
A Novel Hybrid Bacteria-chemotaxis Spiral-dynamic Algorithm with Application to Modelling of Flexible Systems |
title_full |
A Novel Hybrid Bacteria-chemotaxis Spiral-dynamic Algorithm with Application to Modelling of Flexible Systems |
title_fullStr |
A Novel Hybrid Bacteria-chemotaxis Spiral-dynamic Algorithm with Application to Modelling of Flexible Systems |
title_full_unstemmed |
A Novel Hybrid Bacteria-chemotaxis Spiral-dynamic Algorithm with Application to Modelling of Flexible Systems |
title_sort |
novel hybrid bacteria-chemotaxis spiral-dynamic algorithm with application to modelling of flexible systems |
publisher |
Elsevier |
publishDate |
2014 |
url |
http://umpir.ump.edu.my/id/eprint/7791/ http://umpir.ump.edu.my/id/eprint/7791/ http://umpir.ump.edu.my/id/eprint/7791/ |
first_indexed |
2023-09-18T22:04:47Z |
last_indexed |
2023-09-18T22:04:47Z |
_version_ |
1777414635377393664 |