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Published in 2017 at "Soft Computing"
DOI: 10.1007/s00500-015-1956-2
Abstract: This paper proposes a hybrid improved quantum-behaved particle swarm optimization (LTQPSO) for autonomous mobile robot (AMR) trajectory planning in the environment with random obstacles. The algorithm combines the individual particle evolutionary rate and the swarm…
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Keywords:
mobile robot;
trajectory planning;
hybrid improved;
autonomous mobile ... See more keywords
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Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.3005247
Abstract: This study proposes a new classifying approach for identifying collected failure data of cluster head (CH) in wireless sensor networks (WSN) based on hybridizing improved multi-verse optimizer (MVO) and feedforward neural network (FNN). An improvement…
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Keywords:
fnn;
improved mvo;
identifying collected;
data failure ... See more keywords
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Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.3012838
Abstract: Feature selection, which eliminates irrelevant and redundant features, is one of the most efficient classification methods. However, searching for an optimal subset from the original set is still a challenging problem. This paper proposes a…
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Keywords:
improved dragonfly;
feature selection;
dragonfly algorithm;
hybrid improved ... See more keywords
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Published in 2022 at "Advances in Mechanical Engineering"
DOI: 10.1177/16878132221085125
Abstract: To advance the calculation performance of the battle royale optimization algorithm (BRO), a hybrid improved BRO algorithm (HBC) is proposed in this paper. The level mechanism of the chicken swarm optimization algorithm (CSO) is integrated…
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Keywords:
kinematics;
hbc algorithm;
improved bro;
algorithm ... See more keywords