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  1. 1
    An energy-efficient spectrum-aware reinforcement learning-based clustering algorithm for cognitive radio sensor networks

    An energy-efficient spectrum-aware reinforcement learning-based clustering algorithm for cognitive radio sensor networks by Mustapha, Ibrahim, Mohd Ali, Borhanuddin, A. Rasid, Mohd Fadlee, Sali, Aduwati, Mohamad, Hafizal

    Published 2015
    “…We first model the network energy consumption and then determine the optimal number of clusters for the network. The problem of selecting an optimal cluster is formulated as a Markov Decision Process (MDP) in the algorithm and the obtained simulation results show convergence, learning and adaptability of the algorithm to dynamic environment towards achieving an optimal solution. …”
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  2. 2
    Optimizing Visual Sensors Placement with Risk Maps Using Dynamic Programming

    Optimizing Visual Sensors Placement with Risk Maps Using Dynamic Programming by Altahir, A.A., Asirvadam, V.S., Sebastian, P., Hamid, N.H.B., Ahmed, E.F.

    Published 2022
    “…Thus, related surveillance planning methods optimize the placement of visual sensors based on equally significance grids by not limiting to demand of coverage. …”
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  3. 3
    A reinforcement learning-based energy-efficient spectrum-aware clustering algorithm for cognitive radio wireless sensor network

    A reinforcement learning-based energy-efficient spectrum-aware clustering algorithm for cognitive radio wireless sensor network by Mustapha, Ibrahim

    Published 2016
    “…Simulation results show convergence, learning and adaptability of the RL based algorithms to dynamic environment toward achieving the optimal solutions. …”
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  4. 4
    A new routing mechanism for energy-efficient in bluetooth mesh-low power nodes based on wireless sensor network

    A new routing mechanism for energy-efficient in bluetooth mesh-low power nodes based on wireless sensor network by Almuslehi, Hussein Saad Mohammed

    Published 2023
    “…Compared to the Ant Colony Optimization-Genetic Algorithm (ACO-GA) and Ant Colony Optimization- Hierarchical Clustering Mechanism (ACOHCM), the ACO algorithm shows superior power savings and efficiency. …”
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  5. 5
    Modelling of multi-robot system for search and rescue

    Modelling of multi-robot system for search and rescue by Poy, Yi Ler

    Published 2023
    “…In this project, this sensor-based algorithm is known as the Obstacle Avoidance Algorithm. …”
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  6. 6
    A trust aware secure ant colony optimization based routing algorithm for Internet of Things

    A trust aware secure ant colony optimization based routing algorithm for Internet of Things by Sharmin, Afsah, Anwar, Farhat, Motakabber, S. M. A., Hassan Abdalla Hashim, Aisha

    Published 2023
    “…For wireless sensor network (WSN) integrated dynamic IoT networks, this paper presents a trust-aware secure Ant colony optimization (ACO)-based routing algorithm to provide security while searching for an energy-efficient optimal routing path. …”
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  7. 7
    Distributive and self-sustainable scheduling algorithm for wireless sensor networks

    Distributive and self-sustainable scheduling algorithm for wireless sensor networks by Sheikh, M.A., Ali, N.B.Z., Awang, A.

    Published 2013
    “…Thus, the design of optimal distributed scheduling algorithm has remained a challenge for the last few decades. …”
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  8. 8
    Distributive and self-sustainable scheduling algorithm for wireless sensor networks

    Distributive and self-sustainable scheduling algorithm for wireless sensor networks by Sheikh, M.A., Ali, N.B.Z., Awang, A.

    Published 2013
    “…Thus, the design of optimal distributed scheduling algorithm has remained a challenge for the last few decades. …”
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  9. 9
    Distributive and self-sustainable scheduling algorithm for wireless sensor networks

    Distributive and self-sustainable scheduling algorithm for wireless sensor networks by Sheikh, M.A., Ali, N.B.Z., Awang, A.

    Published 2013
    “…Thus, the design of optimal distributed scheduling algorithm has remained a challenge for the last few decades. …”
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  10. 10
    Trust-based enhanced ACO algorithm for secure routing in IoT

    Trust-based enhanced ACO algorithm for secure routing in IoT by Sharmin, Afsah, Motakabber, S M A, Hassan Abdalla Hashim, Aisha

    Published 2024
    “…In order to provide an energy-efficient and secure routing method for sensors deployed within a dynamic IoT network, this paper presents a trust-aware enhanced ant colony optimization (ACO)-based routing algorithm, incorporating a lightweight trust evaluation model. …”
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  11. 11
    Using the evolutionary mating algorithm for optimizing the user comfort and energy consumption in smart building

    Using the evolutionary mating algorithm for optimizing the user comfort and energy consumption in smart building by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

    Published 2023
    “…EMA belongs to the evolutionary computation group of nature-inspired metaheuristic algorithms and offers a promising solution. A comparative analysis is conducted with other well-known algorithms such as Particle Swarm Optimization (PSO), Differential Evolution (DE), Ant Colony Optimization (ACO), Biogeography-Based Optimization (BBO), Teaching-Learning Based Optimization (TLBO), and Beluga Whale Optimization (BWO). …”
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  12. 12
    A novel softsign fractional-order controller optimized by an intelligent nature-inspired algorithm for magnetic levitation control

    A novel softsign fractional-order controller optimized by an intelligent nature-inspired algorithm for magnetic levitation control by Ahmad, Mohd Ashraf, Izci, Davut, Ekinci, Serdar, Mohd Tumari, Mohd Zaidi

    Published 2025
    “…The performance of the proposed approach was extensively benchmarked against four modern metaheuristic algorithms (greater cane rat algorithm, catch fish optimization algorithm, RIME algorithm and artificial hummingbird algorithm) under identical conditions. …”
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  13. 13
    Dynamic positioning base station for wireless sensor network using particle swarm optimization (PSO)

    Dynamic positioning base station for wireless sensor network using particle swarm optimization (PSO) by Nurul Adilah Abdul Latiff

    Published 2012
    “…This creates unbalanced energy consumption among all sensor nodes and furthermore reduces the network energy efficiency. Since the optimal selection of base station location in a network belongs to nondeterministic polynomial (NP) hard problem, the use of approximation algorithms such as Particle Swarm Optimization (PSO) are generally more suitable due to its simplicity and outstanding search strength.…”
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  14. 14
    Modeling of static and dynamic components of bio-nanorobotic systems

    Modeling of static and dynamic components of bio-nanorobotic systems by Gavgani, Hamidreza Khataee

    Published 2012
    “…Then, these graph-based structural models of the fullerenes and graph algorithms based on dynamic programming are applied to compute a new set of optimal weighted physical properties of the components including Wiener, hyper-Wiener, Harary and reciprocal Wiener indices as well as Hosoya and hyper-Hosoya polynomials. …”
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  15. 15
    An energy efficient reinforcement learning based cooperative channel sensing for cognitive radio sensor networks

    An energy efficient reinforcement learning based cooperative channel sensing for cognitive radio sensor networks by Mustapha, Ibrahim, Mohd Ali, Borhanuddin, Sali, Aduwati, A. Rasid, Mohd Fadlee, Mohamad, Hafizal

    Published 2017
    “…Simulation results show convergence and adaptability of the algorithm to dynamic environment in achieving optimal solutions. …”
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  16. 16
    Dynamic area coverage algorithms for static and mobile wireless sensor network environments using voronoi techniques

    Dynamic area coverage algorithms for static and mobile wireless sensor network environments using voronoi techniques by Ceesay, Omar M.

    Published 2011
    “…This thesis focuses on developing Voronoi Tessellation-based Coverage Optimization Algorithms for Static and Mobile Wireless Sensor Networks, where a large number of static nodes are supported by few mobile nodes in carrying out the sensing task. …”
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  17. 17
    Development an accurate and stable range-free localization scheme for anisotropic wireless sensor networks

    Development an accurate and stable range-free localization scheme for anisotropic wireless sensor networks by Han, Fengrong

    Published 2022
    “…This study developed an optimized variation of the DV-Hop localization algorithm for anisotropic wireless sensor networks. …”
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  18. 18
    Maximum Power Point Tracking (MPPT) Based Particle Swarm Optimization (PSO) for hydrokinetic energy harnessing

    Maximum Power Point Tracking (MPPT) Based Particle Swarm Optimization (PSO) for hydrokinetic energy harnessing by Wan Ismail, Ibrahim, Mohd Rusllim, Mohamed, Raja Mohd Taufika, Raja Ismail, Mohd Riduwan, Ghazali, Ping, C. L. X.

    Published 2024
    “…This paper presents a design and modeling of the Particle Swarm Optimization (PSO)-based maximum power point tracking (MPPT) algorithm specifically tailored for variable-speed fixed-pitch vertical axis hydrokinetic turbines. …”
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  19. 19
    Efficient and scalable ant colony optimization based WSN routing protocol for IoT

    Efficient and scalable ant colony optimization based WSN routing protocol for IoT by Sharmin, Afsah, Anwar, Farhat, Motakabber, S. M. A.

    Published 2020
    “…For this reason, many intelligent systems have been utilized to design routing algorithms to handle the network's dynamic state. In this paper, an ant colony optimization (ACO) based WSN routing algorithm for IoT has been proposed and analyzed to enhance scalability, to accommodate node mobility and to minimize initialization delay for time critical applications in the context of IoT to find the optimal path of data transmission, improvising efficient IoT communications. …”
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  20. 20
    A wireless interference-aware internet-of-things gateway placement framework with genetic algorithm approach

    A wireless interference-aware internet-of-things gateway placement framework with genetic algorithm approach by Kong, Zan Wai

    Published 2022
    “…However, there is no existing gateway placement scheme that considers all the factors of number of gateways, sensor nodes coverage, lateral bound (inter-gateway) connections, redundancy for fault tolerance and dynamic changes of sensor nodes’ location. …”
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