Search Results - (( parallel optimization path algorithm ) OR ( changes optimization sensor algorithm ))

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  1. 1
    Tool path generation of contour parallel based on ant colony optimisation

    Tool path generation of contour parallel based on ant colony optimisation by Abdullah, Haslina, Ramli, Rizauddin, Abd Wahab, Dzuraidah, Abu Qudeiri, Jaber

    Published 2016
    “…An Ant Colony Optimisation (ACO) method is used to optimize the tool path length because of its capability to find the shortest tool path length. …”
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  2. 2
    Minimizing machining airtime motion with an ant colony algorithm

    Minimizing machining airtime motion with an ant colony algorithm by Abdullah, Haslina, Ramli, Rizauddin, Abd Wahab, Dzuraidah, Abu Qudeiri, Jaber

    Published 2016
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  3. 3
    OPTIMAL DATAPATH DESIGN FOR A CRYPTOGRAPHIC PROCESSOR: THE BLOWFISH ALGORITHM

    OPTIMAL DATAPATH DESIGN FOR A CRYPTOGRAPHIC PROCESSOR: THE BLOWFISH ALGORITHM by Zain Ali, Noohul Basheer, Noras, James

    Published 2001
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  4. 4
    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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  5. 5
    Coverage and connectivity maximization for wireless sensor networks using improved chaotic grey wolf optimization

    Coverage and connectivity maximization for wireless sensor networks using improved chaotic grey wolf optimization by Shaikh, Muhammad Suhail, Wang, Chang, Xie, Senlin, Zheng, Gengzhong, Dong, Xiaoqing, Qiu, Shuwei, Mohd Ashraf, Ahmad, Raj, Saurav

    Published 2025
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  6. 6
    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
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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
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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
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  9. 9
    Search algorithms for path planning problems in harsh wireless sensor network environment

    Search algorithms for path planning problems in harsh wireless sensor network environment by Hong, Siaw Swin

    Published 2017
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  10. 10
    Restoration planning strategy of transmission system based on optimal energizing time of sectionalizing islands / Dian Najihah Abu Talib

    Restoration planning strategy of transmission system based on optimal energizing time of sectionalizing islands / Dian Najihah Abu Talib by Dian Najihah , Abu Talib

    Published 2019
    “…There are two discrete optimization techniques used in this work, which are the Artificial Bee Colony algorithm and Evolutionary Programming. …”
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  11. 11
    A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks / Salmah Fattah

    A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks / Salmah Fattah by Salmah , Fattah

    Published 2022
    “…The results obtained are then analysed to assess the proposed solution’s performance in obtaining each deployment objective’s optimal value. Finally, the proposed algorithm’s effectiveness regarding node coverage, energy consumption, Pareto-optimal value, and algorithm execution time is validated using three Pareto-optimal metrics: including inverted generation distance (IGD), hypervolume, and diversity. …”
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  12. 12
    A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks

    A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks by Salmah Fattah

    Published 2022
    “…The results obtained are then analysed to assess the proposed solution's performance in obtaining each deployment objective's optimal value. Finally, the proposed algorithm's effectiveness regarding node coverage, energy consumption, Pareto-optimal value, and algorithm execution time is validated using three Pareto-optimal metrics: including inverted generation distance (IGD), hypervolume, and diversity. …”
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  13. 13
    Deployment of Optimized Algorithm for MPEG-4 Data Over Wireless Multimedia Sensor Network

    Deployment of Optimized Algorithm for MPEG-4 Data Over Wireless Multimedia Sensor Network by Hashim, Norlezah, Idris, Fakrulradzi, Syed Ariffin, Dr Sharifah Hafizah, Yunus, Farizah, Fisal, Norsheila

    Published 2014
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  14. 14
    A real-time algorithm of optical tactile sensor for surface characterization / Nurul Fathiah Mohamed Rosli

    A real-time algorithm of optical tactile sensor for surface characterization / Nurul Fathiah Mohamed Rosli by Mohamed Rosli, Nurul Fathiah

    Published 2016
    “…Many advances have been made in terms of sensor technology for sensitivity optimization. Mostly available optical tactile sensors are bulky, inflexible and lack dexterity for applications with limited or space constraint. …”
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  15. 15
    On Clustering Algorithm Of Coverage Area Problems In Wireless Sensor Networks

    On Clustering Algorithm Of Coverage Area Problems In Wireless Sensor Networks by Ismail Abdullah, Kalid Abdlkader Marsal

    Published 2024
    “…In the following paper, the effect that changing the fitness cap used in the genetic algorithm has, on a WSN, in terms of lifespan and the quality of lifespan, is documented. …”
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  16. 16
    A Survey Of Supervised Machine Learning In Wireless Sensor Network: A Power Management Perspective

    A Survey Of Supervised Machine Learning In Wireless Sensor Network: A Power Management Perspective by Ul haq, Riaz, Norrozila, Sulaiman, Muhammad, Alam

    Published 2013
    “…This survey paper is focused on the discussion of best optimal path routing algorithms in wireless sensor networks by using supervised machine learning approaches. …”
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  17. 17
    An Improved Distributed Scheduling Algorithm for Wireless Sensor Networks

    An Improved Distributed Scheduling Algorithm for Wireless Sensor Networks by Sheikh, Muhammad Aman, Drieberg , Micheal, Zain Ali, Noohul Basheer

    Published 2012
    “…In contrast to earlier traditional scheduling algorithms of medium access control (MAC), which are generally designed for sequential slot assignments, this paper presents an improved algorithm for distributed scheduling. …”
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  18. 18
    HDRA: A Haybird Data Reduction and Routing Algorithm

    HDRA: A Haybird Data Reduction and Routing Algorithm by Hussein, M. K., Marghescu, Ion, A. M. Alduais, Nayef

    Published 2024
    “…It strives to decrease the packet transmission by sensor nodes, especially when there's minimal change in sensor readings. …”
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  19. 19
    HDRA: A Haybird Data Reduction and Routing Algorithm

    HDRA: A Haybird Data Reduction and Routing Algorithm by M. K. Hussein, M. K. Hussein, Ion Marghescu, Ion Marghescu, Nayef A. M. Alduais, Nayef A. M. Alduais

    Published 2024
    “…It strives to decrease the packet transmission by sensor nodes, especially when there's minimal change in sensor readings. …”
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  20. 20
    Dealing with Routing Hole Problem in Multi-hop Hierarchical Routing Protocol in Wireless Sensor Network

    Dealing with Routing Hole Problem in Multi-hop Hierarchical Routing Protocol in Wireless Sensor Network by Sama, Najm Us

    Published 2019
    “…A Wireless Sensor Network (WSN) consists of spatially distributed autonomous sensors which produces a measurable response to a change in a physical or chemical condition, e.g. temperature and ground composition. …”
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