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  1. 1
    Self-configured link adaptation using channel quality indicator-modulation and coding scheme mapping with partial feedback for green long-term evolution cellular systems

    Self-configured link adaptation using channel quality indicator-modulation and coding scheme mapping with partial feedback for green long-term evolution cellular systems by Salman, Mustafa Ismael

    Published 2015
    “…To achieve this objective, an iterative approach based on swarm intelligence is used to find the optimal CQI threshold at which the competing criteria are optimized. …”
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  2. 2
    Adapting perturbation voltage in PV array with power point tracking and differential evolution

    Adapting perturbation voltage in PV array with power point tracking and differential evolution by Nurul Izyan Kamaruddin, Ahmad Razani Haron, Min Keng Tan, Soo Siang Yang, Hui Hwang Goh, Kenneth Tze Kin Teo

    Published 2019
    “…Thus, the proposed algorithm that used to track the maximum power is differential evolution (DE) in order to improve the power output of the PV array. …”
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  3. 3
    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
    “…A dynamic user-wise algorithm is proposed to resolve this problem. In depth comparison among these schemes using different metrics like average sum-rate per cell, data rate and feedback rate demonstrates the better performance of centralized cooperation over partial cooperation with higher backhaul load. …”
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  4. 4
    Parameter extraction of solar photovoltaic modules using penalty-based differential evolution

    Parameter extraction of solar photovoltaic modules using penalty-based differential evolution by Ishaque, K., Salam, Z., Mekhilef, Saad, Shamsudin, A.

    Published 2012
    “…The analyses carried out using synthetic current-voltage (I-V) data set showed that the proposed P-DE outperforms other Evolutionary Algorithm methods, namely the simulated annealing (SA), genetic algorithm (GA), and particle swarm optimization (PSO). …”
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  5. 5
    Application of the Hybrid Artificial Neural Network Coupled with Rolling Mechanism and Grey Model Algorithms for Streamflow Forecasting Over Multiple Time Horizons

    Application of the Hybrid Artificial Neural Network Coupled with Rolling Mechanism and Grey Model Algorithms for Streamflow Forecasting Over Multiple Time Horizons by Yaseen, Zaher Mundher, Fu, Minglei, Wang, Chen, Mohtar, Wan Hanna Melini Wan, Deo, Ravinesh C., El-Shafie, Ahmed

    Published 2018
    “…The optimization of the input datasets selection was performed using auto-correlation (ACF) and partial auto-correlation (PACF) functions. …”
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  6. 6
    Two level Differential Evolution algorithms for ARMA parameters estimatio

    Two level Differential Evolution algorithms for ARMA parameters estimatio by Salami, Momoh Jimoh Emiyoka, Tijani, Ismaila, Aibinu, Abiodun Musa

    Published 2013
    “…An Evolutionary Algorithm (EA) comprising two-level Differential Evolution (DE) optimization scheme is proposed. …”
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  7. 7
    Reliably optimal PMU placement using disparity evolution-based genetic algorithm

    Reliably optimal PMU placement using disparity evolution-based genetic algorithm by Matsukawa, Yoshiaki, Othman, Mohammad Lutfi, Watanabe, Masayuki, Mitani, Yasunori

    Published 2017
    “…The optimization model is solved for IEEE 118 standard bus system. …”
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  8. 8
    Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse)

    Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse) by Jia, Xing Yeoh, Chuii, Khim Chong, Mohd Saberi, Mohamad, Yee, Wen Choon, Lian, En Chai, Safaai, Deris, Zuwairie, Ibrahim

    Published 2015
    “…Global optimisation method includes differential evolution algorithm, which will be used in this research. …”
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  9. 9
    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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  10. 10
    Nonlinear identification of a small scale unmanned helicopter using optimized NARX network with multiobjective differential evolution

    Nonlinear identification of a small scale unmanned helicopter using optimized NARX network with multiobjective differential evolution by Tijani, Ismaila B., Akmeliawati, Rini, Legowo, Ari, Budiyono, Agus

    Published 2014
    “…This study proposes a hybrid of conventional back propagation training algorithm for the NARX network and multiobjective differential evolution (MODE) algorithm for identification of a nonlinear model of an unmanned small scale helicopter from experimental flight data.The proposed hybrid algorithm was able to produce models with Pareto-optimal compromise between the design objectives. …”
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  11. 11
    Optimization Of Fractional-Slot Permanent Magnet Synchronous Machine Using Analytical Sub-Domain Model And Differential Evolution

    Optimization Of Fractional-Slot Permanent Magnet Synchronous Machine Using Analytical Sub-Domain Model And Differential Evolution by Mohamed, Mohd Rezal

    Published 2019
    “…From the results obtained, the Analytical Sub-Domain Differential Evolution Algorithm (ASDEA) has better optimization technique capability compared with Analytical Sub-Domain Particle Swarm Optimization (ASPSO). …”
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  12. 12
    Hybrid algorithm for NARX network parameters' determination using differential evolution and genetic algorithm

    Hybrid algorithm for NARX network parameters' determination using differential evolution and genetic algorithm by Salami, Momoh Jimoh Eyiomika, Tijani, Ismaila, Isqeel , Abdullateef Ayodele, Aibinu, Abiodun Musa

    Published 2013
    “…The proposed algorithm involves a two level optimization scheme to search for both optimal network architecture and weights. …”
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  13. 13
    Developing a hybrid model for accurate short-term water demand prediction under extreme weather conditions: a case study in Melbourne, Australia

    Developing a hybrid model for accurate short-term water demand prediction under extreme weather conditions: a case study in Melbourne, Australia by Zubaidi S.L., Kumar P., Al-Bugharbee H., Ahmed A.N., Ridha H.M., Mo K.H., El-Shafie A.

    Published 2024
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  14. 14
    An implementation of differential evolution algorithm for a single product and single period multi-echelon supply chain network model

    An implementation of differential evolution algorithm for a single product and single period multi-echelon supply chain network model by Ayda, Emdadian, Ponnambalam, S. G., Kanagaraj, G.

    Published 2018
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  15. 15
    Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain

    Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain by Mohamad Zihin , Mohd Zain

    Published 2018
    “…BSA gave the best overall performance by showing improved solutions and more robust convergence in comparison with various metaheuristics used in this work. Multi-objective optimization problems are also addressed by proposing a modified multi-criterion optimization algorithm based on a Pareto-based Particle Swarm Optimization (PSO) algorithm called Multi-Objective Particle Swarm Optimization (MOPSO). …”
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  16. 16
    A holistic review on artificial intelligence techniques for well placement optimization problem

    A holistic review on artificial intelligence techniques for well placement optimization problem by Islam, J., Vasant, P.M., Negash, B.M., Laruccia, M.B., Myint, M., Watada, J.

    Published 2020
    “…Nature-inspired gradient-free optimization algorithms like particle swarm optimization, genetic algorithm, covariance matrix adaptation evolution strategy and differential evolution have been utilized in this area. …”
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  17. 17
    Optimization of handover algorithms in 3GPP long term evolution system

    Optimization of handover algorithms in 3GPP long term evolution system by Lin, Cheng-Chung, Sandrasegaran, Kumbesan, Mohd. Ramli, Huda Adibah, Basukala, Riyaj, Patachaianand, Rachod, Chen, Lu, Afrin, Toyoba Sohana

    Published 2011
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  18. 18
    Parameter extraction of photovoltaic module using hybrid evolutionary algorithm

    Parameter extraction of photovoltaic module using hybrid evolutionary algorithm by Muhsen D.H., Ghazali A.B., Khatib T.

    Published 2023
    “…Algorithms; Diodes; Extraction; Iterative methods; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Different evolutions; Differential Evolution; Diode modeling; Electromagnetism-like algorithm; Extracting parameter; Hybrid evolutionary algorithm; Photovoltaic model; Photovoltaic modules; Evolutionary algorithms…”
    Conference Paper
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  19. 19
    Mixed Unscented Kalman Filter and differential evolution for parameter identification

    Mixed Unscented Kalman Filter and differential evolution for parameter identification by Legowo, Ari, Mohamad, Zahratu H., Park, HoonCheol

    Published 2013
    “…DE algorithm is integrated into the UKF algorithm to optimize the Kalman gain obtained. …”
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  20. 20
    Dual optimization approach in discrete Hopfield neural network

    Dual optimization approach in discrete Hopfield neural network by Guo, Yueling, Zamri, Nur Ezlin, Mohd Kasihmuddin, Mohd Shareduwan, Alway, Alyaa, Mansor, Mohd. Asyraf, Li, Jia, Zhang, Qianhong

    Published 2024
    “…Quantitative evaluations show that the proposed model successfully enhances the optimization of both phases, ranking first compared to 10 recent algorithms for all metrics. …”
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