Node location algorithm based on improved grasshopper optimization in wireless sensor network
Publication details: Chennai ICT Academy 2022Edition: Vol.13(3), SepDescription: 2767-2773pSubject(s): Online resources: In: ICTACT journal on communication technologySummary: As the use of swarm intelligence algorithms grows, so does the interest in placing nodes in a Wireless Sensor network. For this reason, the RSSI range model positioning algorithm has been replaced by a more accurate one. With the help of this paper, you can solve complex structural optimization problems with the Grasshopper Optimization Algorithm (GOA). Optimization problems can be solved using this algorithm, which was inspired by the behaviour of grasshopper colonies. CEC2005 is used to test the GOA algorithm quality and quantitative performance. Trusses with a total of 53 and 3 cantilever beams are used to demonstrate the design practicality. It appears that the proposed algorithm outperforms well-known and recently developed algorithms in this area. GOA ability to solve real-world problems with unknown search spaces is demonstrated by its use in the real world.| Item type | Current library | Status | Barcode | |
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School of Engineering & Technology Archieval Section | Not for loan | 2023-0542 |
As the use of swarm intelligence algorithms grows, so does the interest
in placing nodes in a Wireless Sensor network. For this reason, the
RSSI range model positioning algorithm has been replaced by a more
accurate one. With the help of this paper, you can solve complex
structural optimization problems with the Grasshopper Optimization
Algorithm (GOA). Optimization problems can be solved using this
algorithm, which was inspired by the behaviour of grasshopper
colonies. CEC2005 is used to test the GOA algorithm quality and
quantitative performance. Trusses with a total of 53 and 3 cantilever
beams are used to demonstrate the design practicality. It appears that
the proposed algorithm outperforms well-known and recently
developed algorithms in this area. GOA ability to solve real-world
problems with unknown search spaces is demonstrated by its use in the
real world.
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