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  1. 1
    Dynamic smart grid communication parameters based cognitive radio network

    Dynamic smart grid communication parameters based cognitive radio network by Haider H.T., Muhsen D.H., Shahadi H.I., See O.H., Elmenreich W.

    Published 2023
    “…A differential evolution algorithm is used to select the optimal transmission parameters for given communication modes based on a fitness function that combines multiple objectives based on appropriate weights. …”
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  2. 2
    Exploring dynamic self-adaptive populations in differential evolution

    Exploring dynamic self-adaptive populations in differential evolution by Teo, Jason Tze Wi

    Published 2006
    “…In this paper, we present a first attempt at self-adapting the population size parameter in addition to self-adapting crossover and mutation rates. …”
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  3. 3
    An improvement of stochastic gradient descent approach for mean-variance portfolio optimization problem

    An improvement of stochastic gradient descent approach for mean-variance portfolio optimization problem by S. W. Su, Stephanie, Kek, Sie Long

    Published 2021
    “…,e results show that the rate of convergence of the Adam algorithm is significantly enhanced by using the AdamSE algorithm. …”
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  4. 4
    Optimising neural network training efficiency through spectral parameter-based multiple adaptive learning rates

    Optimising neural network training efficiency through spectral parameter-based multiple adaptive learning rates by Yeong, Lin Koay, Hong, Seng Sim, Yong, Kheng Goh, Sing, Yee Chua, Wah, June Leong

    Published 2024
    “…The process of training neural networks heavily involves solving optimization problems. Most optimization algorithms use a !…”
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  5. 5
    Adaptive route optimization for mobile robot navigation using evolutionary algorithm

    Adaptive route optimization for mobile robot navigation using evolutionary algorithm by Kit Guan Lim, Guan Lim, Yoong Hean Lee, Hean Lee, Min Keng Tan, Keng Tan, Hou, Pin Yoong, Tienlei, Wang, Tze, Kenneth Kin Teo

    Published 2021
    “…For example, Ant Colony Optimization (ACO) is an optimization algorithm based on swarm intelligence which is widely used to solve path planning problem. …”
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    Proceedings
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  6. 6
    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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  7. 7
    Fuzzy adaptive emperor penguin optimizer for global optimization problems

    Fuzzy adaptive emperor penguin optimizer for global optimization problems by Md Abdul, Kader

    Published 2023
    “…The Emperor Penguin Optimizer (EPO) is a recently developed population-based metaheuristic algorithm that simulates the huddling behaviour of emperor penguins. …”
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    Thesis
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  8. 8
    Differential evolution for neural networks learning enhancement

    Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

    Published 2008
    “…These algorithms can be used successfully in many applications requiring the optimization of a certain multi-dimensional function. …”
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  9. 9
    An experimental study of a fuzzy adaptive emperor penguin optimizer for global optimization problem

    An experimental study of a fuzzy adaptive emperor penguin optimizer for global optimization problem by Kader, Md. Abdul, Zamli, Kamal Z., Alkazemi, Basem Yousef

    Published 2022
    “…To alleviate these problems, an adaptive mechanism can be introduced in EPO. This paper proposes a fuzzy adaptive variant of EPO, namely Fuzzy Adaptive Emperor Penguin Optimizer (FAEPO), to solve this problem. …”
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  10. 10
    Optimizing Adaptive Neuro Fuzzy Inference System (Anfis) With Dragonfly Algorithm For Cardiovascular Disease

    Optimizing Adaptive Neuro Fuzzy Inference System (Anfis) With Dragonfly Algorithm For Cardiovascular Disease by Jinjiri, Wada Mohammed

    Published 2023
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  11. 11
    Attack path selection optimization with adaptive genetic algorithms

    Attack path selection optimization with adaptive genetic algorithms by Abd Rahman, A.S., Zakaria, M.N., Masrom, S.

    Published 2016
    “…We describe our approach for implementing an optimized security assessment using Genetic Algorithm (GA). …”
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  12. 12
    Attack path selection optimization with adaptive genetic algorithms

    Attack path selection optimization with adaptive genetic algorithms by Abd Rahman, A.S., Zakaria, M.N., Masrom, S.

    Published 2016
    “…We describe our approach for implementing an optimized security assessment using Genetic Algorithm (GA). …”
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  13. 13
    Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network

    Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network by Kang, Miew How

    Published 2016
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  14. 14
    Improving particle swarm optimization via adaptive switching asynchronous – synchronous update

    Improving particle swarm optimization via adaptive switching asynchronous – synchronous update by Nor Azlina, Ab. Aziz, Zuwairie, Ibrahim, Marizan, Mubin, Sophan Wahyudi, Nawawi, Mohd Saberi, Mohamad

    Published 2018
    “…Particle swarm optimization (PSO) is a population-based metaheuristic optimization algorithm that solves a problem through iterative operations. …”
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  15. 15
    Improving particle swarm optimization via adaptive switching asynchronous – synchronous update

    Improving particle swarm optimization via adaptive switching asynchronous – synchronous update by Abd Aziz, Nor Azlina, Ibrahim, Zuwairie, Mubin, Marizan, Nawawi, Sophan Wahyudi, Mohamad, Mohd Saberi

    Published 2018
    “…Particle swarm optimization (PSO) is a population-based metaheuristic optimization algorithm that solves a problem through iterative operations. …”
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  16. 16
    Intelligent web proxy cache replacement algorithm based on adaptive weight ranking policy via dynamic aging

    Intelligent web proxy cache replacement algorithm based on adaptive weight ranking policy via dynamic aging by Olanrewaju, Rashidah Funke, Al-Qudah, Dua'a Mahmoud Mohammad, Azman, Amelia Wong, Yaacob, Mashkuri

    Published 2016
    “…However, their performances are not well optimized. This work proposes a hybrid method that optimize cache replacement algorithm using Naïve Bayes (NB) based approach. …”
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  17. 17
    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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  18. 18
    Single Step Multivariate Solar Power Forecasting using Adaptive Learning Rate LSTM Model with Optimized Window Size

    Single Step Multivariate Solar Power Forecasting using Adaptive Learning Rate LSTM Model with Optimized Window Size by Kunalan D., Krishnan P.S., Permal N.

    Published 2024
    Subjects: “…Adaptive Learning Rate…”
    Conference Paper
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  19. 19
    OPTIMIZED ARCHITECTURE DESIGN AND IMPLEMENTATION OF OBJECT TRACKING ALGORITHM ON FPGA

    OPTIMIZED ARCHITECTURE DESIGN AND IMPLEMENTATION OF OBJECT TRACKING ALGORITHM ON FPGA by ABDELFATAH EL-KHATIB, LINA NOAMAN

    Published 2013
    “…The system need to be designed on a standard frame rate in such a way to achieve optimal performance in real time environment. …”
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  20. 20
    Improving particle swarm optimization via adaptive switching asynchronous – synchronous update

    Improving particle swarm optimization via adaptive switching asynchronous – synchronous update by Ab. Aziz, Nor Azlina, Ibrahim, Zuwairie, Mubin, Marizan, Nawawi, Sophan Wahyudi, Mohamad, Mohd Saberi

    Published 2018
    “…Particle swarm optimization (PSO) is a population-based metaheuristic optimization algorithm that solves a problem through iterative operations. …”
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