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A Hybrid Swarm Evolution Optimization for Solving Sensornet Node Localization
- Source :
- Intelligent Systems and Networks ISBN: 9789811620935
- Publication Year :
- 2021
- Publisher :
- Springer Singapore, 2021.
-
Abstract
- A new approach to node localization is proposed by using the combined localization model in Wireless sensor nets (WSN) with a hybridized swarm evolution algorithm (HSEA). Mathematically, based on the distances of the localizing model and Pareto, the fitness function is determined. To achieve better efficiency, the HSEA is implemented by combining the particle swarm optimizer (PSO) with the differential-evolution (DE) algorithms. Applied HSEA deals with the node location situation in WSN. The simulation compares the results of the proposed scheme with the others schemes to demonstrate that the suggested task using HSEA achieves better performance than the competitors.
- Subjects :
- Scheme (programming language)
Fitness function
Computer science
business.industry
Node (networking)
Particle swarm optimizer
Pareto principle
Swarm behaviour
020206 networking & telecommunications
02 engineering and technology
Swarm computing
0202 electrical engineering, electronic engineering, information engineering
Wireless
020201 artificial intelligence & image processing
business
Algorithm
computer
computer.programming_language
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- Intelligent Systems and Networks ISBN: 9789811620935
- Accession number :
- edsair.doi...........24e4c1fe38158d78e5ccd2cc6fc8d1c8
- Full Text :
- https://doi.org/10.1007/978-981-16-2094-2_13