Search Results - (( storage optimization path algorithm ) OR ( wave optimisation based algorithm ))
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Robotic indoor path planning using dijkstra's algorithm with multi-layer dictionaries
Published 2016“…The adjacency matrix is the naive storage structure of the algorithm. This storage structure has limited the use of the algorithm as it expands large storage space. …”
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2
RFID data reliability optimiser based on two dimensions bloom filter
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3
Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms
Published 2020“…The IEM algorithm uses the attraction-repulsion mechanism to change the positions of solutions towards the optimality. …”
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4
Comprehensive review of drones collision avoidance schemes: challenges and open issues
Published 2024“…We explore collision avoidance methods for UAVs from various perspectives, categorizing them into four main groups: obstacle detection and avoidance, collision avoidance algorithms, drone swarm, and path optimization. Additionally, our analysis delves into machine learning techniques, discusses metrics and simulation tools to validate collision avoidance systems, and delineates local and global algorithmic perspectives. …”
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5
A smart handover strategy for 5G mmWave dual connectivity networks
Published 2023“…The developed algorithm underwent testing using a 5G mmWave statistical channel model that emulates a dynamic channel matrix, including fading and the Doppler effect. …”
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6
Active intelligent control of vibration of flexible plate structures
Published 2011“…However, the non-model based AVC algorithms are faster than their model-based AVC counterparts.…”
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7
Handover Parameter for Self-optimisation in 6g Mobile Networks: A Survey
Published 2024journal::journal article -
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Factors with retirement behaviour among retirees and pre-retirees identified with a machine learning method / Muhammad Aizat Zainal Alam
Published 2023“…The Malaysian Ageing and Retirement Survey (MARS) Data Wave 1 is used for this study where the data was sampled via multiple-stage sampling framework where each region is stratified by urban and rural areas called enumeration blocks (EBs) which are proportionate to the population size of each region across 3,384 households. …”
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