Simulated Kalman Filter optimization algorithm for maximization of wireless sensor networks coverage
Simulated Kalman Filter (SKF) is a population based optimization algorithm inspired by the Kalman filtering method. It had been successfully used for optimization of many engineering problems. In this work SKF is applied for wireless sensor networks (WSN) coverage optimization problem, where the obj...
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IEEE
2019
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| Online Access: | http://umpir.ump.edu.my/id/eprint/24943/ http://umpir.ump.edu.my/id/eprint/24943/ http://umpir.ump.edu.my/id/eprint/24943/1/40.1%20Simulated%20kalman%20filter%20optimization%20algorithm%20for%20maximization.pdf |
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ump-249432019-10-23T08:13:59Z http://umpir.ump.edu.my/id/eprint/24943/ Simulated Kalman Filter optimization algorithm for maximization of wireless sensor networks coverage Nor Azlina, Ab. Aziz Zuwairie, Ibrahim Kamarulzaman, Ab Aziz Nor Hidayati, Abdul Aziz TJ Mechanical engineering and machinery Simulated Kalman Filter (SKF) is a population based optimization algorithm inspired by the Kalman filtering method. It had been successfully used for optimization of many engineering problems. In this work SKF is applied for wireless sensor networks (WSN) coverage optimization problem, where the objective is to maximize the area covered by the sensors in a region of interest. Coverage is an important issue in WSN. It is used as one of the measurement metric for a WSN’s quality of service. Many metaheuristics algorithms had been applied to solve this problem. Here, SKF is tested over several WSN and found to be able to perform better than particle swarm optimization (PSO) and genetic algorithm (GA) in improving WSN coverage. IEEE 2019-05 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/24943/1/40.1%20Simulated%20kalman%20filter%20optimization%20algorithm%20for%20maximization.pdf Nor Azlina, Ab. Aziz and Zuwairie, Ibrahim and Kamarulzaman, Ab Aziz and Nor Hidayati, Abdul Aziz (2019) Simulated Kalman Filter optimization algorithm for maximization of wireless sensor networks coverage. In: International Conference on Computer and Information Sciences, ICCIS 2019, 3 - 4 April 2019 , Jouf University, Aljouf, Kingdom of Saudi Arabia. pp. 1-5.. ISBN 978-153868125-1 https://doi.org/10.1109/ICCISci.2019.8716387 |
| repository_type |
Digital Repository |
| institution_category |
Local University |
| institution |
Universiti Malaysia Pahang |
| building |
UMP Institutional Repository |
| collection |
Online Access |
| language |
English |
| topic |
TJ Mechanical engineering and machinery |
| spellingShingle |
TJ Mechanical engineering and machinery Nor Azlina, Ab. Aziz Zuwairie, Ibrahim Kamarulzaman, Ab Aziz Nor Hidayati, Abdul Aziz Simulated Kalman Filter optimization algorithm for maximization of wireless sensor networks coverage |
| description |
Simulated Kalman Filter (SKF) is a population based optimization algorithm inspired by the Kalman filtering method. It had been successfully used for optimization of many engineering problems. In this work SKF is applied for wireless sensor networks (WSN) coverage optimization problem, where the objective is to maximize the area covered by the sensors in a region of interest. Coverage is an important issue in WSN. It is used as one of the measurement metric for a WSN’s quality of service. Many metaheuristics algorithms had been applied to solve this problem. Here, SKF is tested over several WSN and found to be able to perform better than particle swarm optimization (PSO) and genetic algorithm (GA) in improving
WSN coverage. |
| format |
Conference or Workshop Item |
| author |
Nor Azlina, Ab. Aziz Zuwairie, Ibrahim Kamarulzaman, Ab Aziz Nor Hidayati, Abdul Aziz |
| author_facet |
Nor Azlina, Ab. Aziz Zuwairie, Ibrahim Kamarulzaman, Ab Aziz Nor Hidayati, Abdul Aziz |
| author_sort |
Nor Azlina, Ab. Aziz |
| title |
Simulated Kalman Filter optimization algorithm for maximization of wireless sensor networks coverage |
| title_short |
Simulated Kalman Filter optimization algorithm for maximization of wireless sensor networks coverage |
| title_full |
Simulated Kalman Filter optimization algorithm for maximization of wireless sensor networks coverage |
| title_fullStr |
Simulated Kalman Filter optimization algorithm for maximization of wireless sensor networks coverage |
| title_full_unstemmed |
Simulated Kalman Filter optimization algorithm for maximization of wireless sensor networks coverage |
| title_sort |
simulated kalman filter optimization algorithm for maximization of wireless sensor networks coverage |
| publisher |
IEEE |
| publishDate |
2019 |
| url |
http://umpir.ump.edu.my/id/eprint/24943/ http://umpir.ump.edu.my/id/eprint/24943/ http://umpir.ump.edu.my/id/eprint/24943/1/40.1%20Simulated%20kalman%20filter%20optimization%20algorithm%20for%20maximization.pdf |
| first_indexed |
2023-09-18T22:38:01Z |
| last_indexed |
2023-09-18T22:38:01Z |
| _version_ |
1777416726746497024 |