Search Results - adaptive over different ((optimization algorithm) OR (pollination algorithm))

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  1. 1
    A modified flower pollination algorithm and carnivorous plant algorithm for solving engineering optimization problem

    A modified flower pollination algorithm and carnivorous plant algorithm for solving engineering optimization problem by Ong, Kok Meng

    Published 2021
    “…Flower pollination algorithm (FPA) is a biomimicry optimisation algorithm inspired by natural pollination. …”
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  2. 2
    Fractional chaos maps with flower pollination algorithm for chaotic systems� parameters identification

    Fractional chaos maps with flower pollination algorithm for chaotic systems� parameters identification by Yousri D., Allam D., Babu T.S., AbdelAty A.M., Radwan A.G., Ramachandaramurthy V.K., Eteiba M.B.

    Published 2023
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  3. 3
    An Optimal Design of Moving Objects Tracking Algorithm on FPGA

    An Optimal Design of Moving Objects Tracking Algorithm on FPGA by Elkhatib, Lina, Hussin, Fawnizu Azmadi, Xia, Likun, Sebastian , Patrick

    Published 2012
    “…The system implements a large amount of operations in order to apply a tracking algorithm called Adaptive Hybrid Difference. Two core units were built to implement the algorithm on FPGA, the adaptive threshold unit and the binary image builder unit. …”
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  4. 4
    An optimal design of moving objects tracking algorithm on FPGA

    An optimal design of moving objects tracking algorithm on FPGA by Elkhatib, Lina Noaman, Hussin, Fawnizu Azmadi, Xia, Likun, Sebastian , Patrick

    Published 2010
    “…The system implements a large amount of operations in order to apply a tracking algorithm called Adaptive Hybrid Difference. Two core units were built to implement the algorithm on FPGA, the adaptive threshold unit and the binary image builder unit. …”
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  5. 5
    An optimal design of moving objects tracking algorithm on FPGA

    An optimal design of moving objects tracking algorithm on FPGA by Elkhatib, Lina, Hussin, Fawnizu Azmadi, Xia, Likun, Sebastian , Patrick

    Published 2012
    “…The system implements a large amount of operations in order to apply a tracking algorithm called Adaptive Hybrid Difference. Two core units were built to implement the algorithm on FPGA, the adaptive threshold unit and the binary image builder unit. …”
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  6. 6
    Solving multi-objective dynamic vehicle routing problem with time windows using multi-objective algorithm

    Solving multi-objective dynamic vehicle routing problem with time windows using multi-objective algorithm by Khoo, Thau Soon

    Published 2022
    “…It is difficult and challenging to develop an algorithm that can produce consistent near-optimal solutions even after many runs, average near-optimal solutions that have the least difference in magnitude, broader Pareto set, and iii achieve near-optimal solutions but highly sought after if it is commercially viable. …”
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  7. 7
    Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh

    Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh by Rawaa Dawoud Hassan, Al-Dabbagh

    Published 2015
    “…The second taxonomy is a new taxonomy proposed to classify the adaptive DE algorithms in particular into two categories (DE with adaptive parameters and DE with adaptive parameters and strategies) considering the adaptive components used in this algorithm. …”
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  8. 8
    Performance improvement for infiltration rate prediction using hybridized Adaptive Neuro-Fuzzy Inferences System (ANFIS) with optimization algorithms

    Performance improvement for infiltration rate prediction using hybridized Adaptive Neuro-Fuzzy Inferences System (ANFIS) with optimization algorithms by Ehteram M., Yenn Teo F., Najah Ahmed A., Dashti Latif S., Feng Huang Y., Abozweita O., Al-Ansari N., El-Shafie A.

    Published 2023
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  9. 9
    Adapting And Hybridising Harmony Search With Metaheuristic Components For University Course Timetabling

    Adapting And Hybridising Harmony Search With Metaheuristic Components For University Course Timetabling by Al-Betar, Mohammed Azmi

    Published 2010
    “…Three hybridized versions are proposed which are incremental improvements over the preceding version: (i) Modified Harmony Search Algorithm (MHSA); (ii) Harmony Search Algorithm with Multi-Pitch Adjusting Rate (HSA-MPAR), and (iii) Hybrid Harmony Search Algorithm (HHSA). …”
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  10. 10
    Adaptive model predictive control based on wavelet network and online sequential extreme learning machine for nonlinear systems

    Adaptive model predictive control based on wavelet network and online sequential extreme learning machine for nonlinear systems by Salih, Dhiadeen Mohammed

    Published 2015
    “…The WNMPC is developed by a proposed algorithm named adaptive updating rule (AUR) used with gradient descent optimization method to minimize a constrained cost function over the prediction and control horizons and to offer a robust control performances. …”
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  11. 11
    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
    “…Unlike the existing optimization algorithm, VL-WIDE features the capability of searching different lengths of solutions to cover the variable number of cloudlets for deployment. …”
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  12. 12
    Particle swarm optimization in multi-user orthogonal frequency-division multiplexing systems

    Particle swarm optimization in multi-user orthogonal frequency-division multiplexing systems by Lye, Scott Carr Ken

    Published 2013
    “…While maintaining a target Bit Error Rate (BER), adaptive modulation optimizes the selection of modulation scheme and transmit power for each sub-carrier so that spectral efficiency is maximized. …”
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  13. 13
    OPTIMIZING HYBRID ELECTRIC VEHICLE ENERGY UTILIZATION BASED ON PARTICLE SWARM OPTIMIZATION ALGORITHM

    OPTIMIZING HYBRID ELECTRIC VEHICLE ENERGY UTILIZATION BASED ON PARTICLE SWARM OPTIMIZATION ALGORITHM by Abang Ahmad Latif, Abang Sarbini

    Published 2023
    “…Hybrid electric technology has been adapted in automobiles for over a few decades with the introduction of the Toyota Prius in 1997. …”
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    Final Year Project Report / IMRAD
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  14. 14
    Adaptive Traffic Prioritization Algorithm Over Ad Hoc Network Using IEEE 802.11e

    Adaptive Traffic Prioritization Algorithm Over Ad Hoc Network Using IEEE 802.11e by Anuar, Ammar

    Published 2016
    “…This thesis proposes an adaptive traffic prioritization algorithm over ad hoc network using IEEE 802.11e standard that defines a set of Quality of Service enhancements for wireless LAN applications through modifications to the Media Access Control (MAC) layer. …”
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  15. 15
    Adaptive genetic algorithm to improve negotiation process by agents e-commerce

    Adaptive genetic algorithm to improve negotiation process by agents e-commerce by Ebadi, Sahar

    Published 2011
    “…The proposed adaptive negotiation model is named Aspirated Genetic Algorithm (AGA) negotiation model which is a hybrid negotiation system composed of different negotiation strategies, Aspiration concept,genetic algorithm and Bayesian learning. …”
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  16. 16
    Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection

    Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection by Tubishat, Mohammad, Idris, Norisma, Shuib, Liyana, Abushariah, Mohammad A.M., Mirjalili, Seyedali

    Published 2020
    “…In addition, ISSA was compared with four well-known optimization algorithms such as Genetic Algorithm, Particle Swarm Optimization, Grasshopper Optimization Algorithm, and Ant Lion Optimizer. …”
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  17. 17
    Simulated real-time controller for tuning algorithm using modified hill climbing approach

    Simulated real-time controller for tuning algorithm using modified hill climbing approach by Ahmed, Ahmed Abdulelah

    Published 2014
    “…Often, it is necessary to calibrate a certain parameters of a control system due to plant parameters fluctuation over time.In this research, an intelligent algorithmic tuning technique suitable for realtime system tuning based on hill climbing optimization algorithm and model reference adaptive control system (MRAC) technique is proposed. …”
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  18. 18
    Speed sensorless control of permanent magnet synchronous motor using model reference adaptive system and artificial neural network / Abdul Mu’iz Nazelan

    Speed sensorless control of permanent magnet synchronous motor using model reference adaptive system and artificial neural network / Abdul Mu’iz Nazelan by Nazelan, Abdul Mu’iz

    Published 2019
    “…Then, the MRAS is modelled and HMLP network is used for its adaptation scheme. This study introduced a new method to train the HMLP network using PSO algorithm. …”
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  19. 19
    Performance evaluation of hybrid adaptive neuro-fuzzy inference system models for predicting monthly global solar radiation

    Performance evaluation of hybrid adaptive neuro-fuzzy inference system models for predicting monthly global solar radiation by Halabi, Laith M., Mekhilef, Saad, Hossain, Monowar

    Published 2018
    “…The proposed hybrid models include particle swarm optimization, genetic algorithm and differential evolution. …”
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  20. 20
    Mobility management for seamless handover in carrier aggregation heterogeneous networks deployment scenario of long term evolution-advanced

    Mobility management for seamless handover in carrier aggregation heterogeneous networks deployment scenario of long term evolution-advanced by Ahmed-Abdulazeez, Mariam Ovayioza

    Published 2018
    “…Secondly, a Hybrid Handover Parameters Optimization algorithm based on Enhanced Weight Performance (HHPO) is introduced to optimize, select suitable Handover Control Parameters (HCP) and to manage the conflict that may occur among self-optimization functions. …”
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