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  1. 1
    A framework of rough cultural algorithms in optimizing mobile web caching performance

    A framework of rough cultural algorithms in optimizing mobile web caching performance by Sulaiman, Sarina, Shamsuddin, Siti Maryam, Abraham, Ajith, Sulaiman, Shahida

    Published 2007
    “…Consequently, The proposed caching scheme, Rough Cultural Algorithm (RCA) is developed to materialise the caching policies.…”
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  2. 2
    Reduction the Effect of Mobility in Link Transmitting Using Efficient DSR Route Cache for MANETs

    Reduction the Effect of Mobility in Link Transmitting Using Efficient DSR Route Cache for MANETs by Ayoob, Ayoob A., Norrozila, Sulaiman, Mohammed, Muamer N., Ghaida M., Abdilsahib

    Published 2014
    “…This paper presented a new algorithm using DSR routing cache technique to improve the routing between mobile nodes to reduction the effect of mobility in link transmitting that can solve link broken problem. …”
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  3. 3
    A design of redirect link failure protocol based on dynamic source routing for mobile ad hoc networks

    A design of redirect link failure protocol based on dynamic source routing for mobile ad hoc networks by Ghazali, Osman, Hassan, Suhaidi, M. Kadhum, Mohammed

    Published 2011
    “…The characteristics of ad hoc networks are that they are decentralized, self-organized, self-deployed, and they possess dynamic network topology.All mobile nodes in ad hoc network communicate with each other directly or through intermediate nodes by using routing protocols algorithm. …”
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  4. 4
    Reliable access control for mobile cloud computing (MCC) with cache-aware scheduling

    Reliable access control for mobile cloud computing (MCC) with cache-aware scheduling by Jamal, Fara, Abdullah, Mohd Taufik, Mohd Hanapi, Zurina, Abdullah, Azizol

    Published 2019
    “…Therefore, a new approach was proposed in this research to deal with the single point of failure in the authority. Furthermore, the cache-based scheduling algorithm was upgraded to improve the response time of user jobs. …”
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  5. 5
    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
    “…In this paper, Disparity Evolution-type Genetic Algorithm (DEGA) based on disparity theory of evolution is applied. …”
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  6. 6
    A refined differential evolution algorithm for improving the performance of optimization process

    A refined differential evolution algorithm for improving the performance of optimization process by A. R., Yusoff, Nafrizuan, Mat Yahya

    Published 2011
    “…DE is developed based on an improved Genetic Algorithm and come with different strategies for faster optimization. …”
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  7. 7
    A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising

    A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising by Al-Dabbagh, Mohanad Dawood, Al-Dabbagh, Rawaa Dawoud, Raja Abdullah, Raja Syamsul Azmir, Hashim, Fazirulhisyam

    Published 2015
    “…The main intention of this study was to investigate the development of a new optimization technique based on the differential evolution (DE) algorithm, for the purpose of linear frequency modulation radar signal de-noising. …”
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  8. 8
    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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  9. 9
    Broadening selection competitive constraint handling algorithm for faster convergence

    Broadening selection competitive constraint handling algorithm for faster convergence by Shaikh, T.A., Hussain, S.S., Tanweer, M.R., Hashmani, M.A.

    Published 2020
    “…In this study, the BSCCH algorithm has been coupled with Differential Evolution algorithm as a proof of concept because it is found to be an efficient algorithm in the literature for constrained optimization problems. …”
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  10. 10
    Differential evolution optimization algorithm based on generation systems reliability assessment integrated with wind energy

    Differential evolution optimization algorithm based on generation systems reliability assessment integrated with wind energy by Kadhem, Athraa Ali, Abdul Wahab, Noor Izzri, Abdalla, Ahmed N.

    Published 2019
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  11. 11
    Location-Based Approach for Route Maintenance in Dynamic Source Routing Protocol

    Location-Based Approach for Route Maintenance in Dynamic Source Routing Protocol by Sjaugi, Muhammad Farhan

    Published 2008
    “…DSR is based on the concept of source routing. For this protocol, mobile nodes are required to maintain route caches that contain the source routes of which the mobile is aware. …”
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  12. 12
    Secure multi-authority attribute-based encryption access control with cache-aware scheduling in mobile cloud computing

    Secure multi-authority attribute-based encryption access control with cache-aware scheduling in mobile cloud computing by Jamal, Fara

    Published 2021
    “…For the proposed scheme, the MTTD was very low which is 4.89 minutes, because of the consensus algorithm. Furthermore, by using the cache-aware scheduling, the proposed scheme managed to save 2.18% reads more than those of the existing work solution; this could reduce the time taken to access required data. …”
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  13. 13
    Crossover-first differential evolution for improved global optimization in non-uniform search landscapes

    Crossover-first differential evolution for improved global optimization in non-uniform search landscapes by Teo, Jason Tze Wi, Mohd Hanafi Ahmad Hijazi, Hui, Keng Lau, Salmah Fattah, Aslina Baharum

    Published 2015
    “…The differential evolution (DE) algorithm is currently one of the most widely used evolutionary-based optimizers for global optimization due to its simplicity, robustness and efficiency. …”
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  14. 14
    Multiobjective differential evolution algorithm-based sizing of a standalone photovoltaic water pumping system

    Multiobjective differential evolution algorithm-based sizing of a standalone photovoltaic water pumping system by Muhsen D.H., Ghazali A.B., Khatib T.

    Published 2023
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  15. 15
    Optimal placement, sizing and power factor of distributed generation: A comprehensive study spanning from the planning stage to the operation stage

    Optimal placement, sizing and power factor of distributed generation: A comprehensive study spanning from the planning stage to the operation stage by Huy P.D., Ramachandaramurthy V.K., Yong J.Y., Tan K.M., Ekanayake J.B.

    Published 2023
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  16. 16
    Hybrid differential evolution-particle swarm optimization algorithm for multi objective urban transit network design problem with homogeneous buses

    Hybrid differential evolution-particle swarm optimization algorithm for multi objective urban transit network design problem with homogeneous buses by Tarajo, Buba Ahmed, Lee, Lai Soon

    Published 2019
    “…This paper proposes a hybrid differential evolution with particle swarm optimization (DE-PSO) algorithm to solve the UTNDP, aiming to simultaneously optimize route configuration and service frequency with specific objectives in minimizing both the passengers’ and operators’ costs. …”
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  17. 17
    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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  18. 18
    Robust multi-user detection based on hybrid grey wolf optimization

    Robust multi-user detection based on hybrid grey wolf optimization by Ji, Yuanfa, Fan, Z ., Sun, X., Wang, S., Yan, S., Wu, S., Fu, Q., Kamarul Hawari, Ghazali

    Published 2020
    “…The simulation results show that the iteration times of the multi-user detector based on the proposed algorithm is less than that of genetic algorithm, differential evolution algorithm and Grey wolf optimization algorithm, and has the lower BER.…”
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  19. 19
    Investigation and validation of an eleven level symmetric modular multilevel inverter using grey wolf optimization and differential evolution control algorithm for solar PV applications

    Investigation and validation of an eleven level symmetric modular multilevel inverter using grey wolf optimization and differential evolution control algorithm for solar PV applica... by Stonier, A.A., Chinnaraj, G., Kannan, R., Mani, G.

    Published 2021
    “…Purpose: This paper aims to examine the design and control of a symmetric multilevel inverter (MLI) using grey wolf optimization and differential evolution algorithms. Design/methodology/approach: The optimal modulation index along with the switching angles are calculated for an 11 level inverter. …”
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  20. 20
    Differential evolution for neural networks learning enhancement

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

    Published 2008
    “…Evolutionary computation is the name given to a collection of algorithms based on the evolution of a population toward a solution of a certain problem. …”
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