Search Results - adapting location differences evolution algorithm

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  1. 1
    Evolution strategy for collaborative beamforming in wireless sensor networks

    Evolution strategy for collaborative beamforming in wireless sensor networks by Wong, Chen How

    Published 2013
    “…It becomes a vital problem to achieve CB as the distributed sensor nodes are unaware of their phase relationship. An iterative algorithm using evolution strategy (ES) is proposed to achieve phase alignment at the intended location in static channels, which require one-bit feedback from the receiver destination. …”
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  2. 2
    Cloudlet deployment and task offloading in mobile edge computing using variable-length whale and differential evolution optimization and analytical hierarchical process for decision-making

    Cloudlet deployment and task offloading in mobile edge computing using variable-length whale and differential evolution optimization and analytical hierarchical process for decisio... by Daba, Layth Muwafaq Abdulhussein

    Published 2023
    “…Furthermore, assuming the fixed location of the cloudlets will limit the dynamic adaptability of the problem. …”
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  3. 3
    Evoluation strategy for collaborative beamforming in wireless sensor networks

    Evoluation strategy for collaborative beamforming in wireless sensor networks by Wong, Chen How

    Published 2013
    “…It becomes a vital problem to achieve CB as the distributed sensor nodes are unaware of their phase relationship. An iterative algorithm using evolution strategy (ES) is proposed to achieve phase alignment at the intended location in static channels, which require one-bit feedback from the receiver destination. …”
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  4. 4
    Application of the hybrid ANFIS models for long term wind power density prediction with extrapolation capability

    Application of the hybrid ANFIS models for long term wind power density prediction with extrapolation capability by Hossain, Monowar, Mekhilef, Saad, Afifi, Firdaus, Halabi, Laith M., Olatomiwa, Lanre, Seyedmahmoudian, Mehdi, Horan, Ben, Stojcevski, Alex

    Published 2018
    “…In this paper, the suitability and performance of ANFIS (adaptive neuro-fuzzy inference system), ANFIS-PSO (particle swarm optimization), ANFIS-GA (genetic algorithm) and ANFIS-DE (differential evolution) has been investigated for the prediction of monthly and weekly wind power density (WPD) of four different locations named Mersing, Kuala Terengganu, Pulau Langkawi and Bayan Lepas all in Malaysia. …”
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  5. 5
    Backhaul load and performance optimality of partial joint processing schemes in LTE-A networks

    Backhaul load and performance optimality of partial joint processing schemes in LTE-A networks by Kousha, Mohammad

    Published 2014
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  6. 6
    Techno-economic evaluation of off-grid hybrid renewable energy system for rural resort electrification in Malaysia / Monowar Hossain

    Techno-economic evaluation of off-grid hybrid renewable energy system for rural resort electrification in Malaysia / Monowar Hossain by Monowar, Hossain

    Published 2017
    “…For these purposes, the standalone ANFIS, ANFIS-PSO (particle swarm optimization),ANFIS-GA (genetic algorithm) and ANFIS-DE (differential evolution) prediction algorithms have been developed in MATLAB platform. …”
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  7. 7
    Performance analysis of hybrid renewable energy systems used for rural electrification in Malaysia / Laith Mahmoud Mohammad Halabi

    Performance analysis of hybrid renewable energy systems used for rural electrification in Malaysia / Laith Mahmoud Mohammad Halabi by Laith Mahmoud, Mohammad Halabi

    Published 2017
    “…Accordingly, the results of predicting monthly global solar radiation showed a very good agreement between the predicted and measured data sets besides it demonstrated the high prediction capability of the developed hybrid models using standalone Adaptive Neuro-Fuzzy Inference System (ANFIS) and hybrid ANFIS models which include ANFIS-PSO (Particle Swarm Optimization), ANFIS-GA (Genetic Algorithm), and ANFIS-DE (Differential Evolution). …”
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