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  1. 1
    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection

    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

    Published 2022
    “…Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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  2. 2
    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing

    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

    Published 2011
    “…A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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  3. 3
    Features selection for intrusion detection system using hybridize PSO-SVM

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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  4. 4
    An ensemble learning method for spam email detection system based on metaheuristic algorithms

    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…In order to address the challenges that mentioned above in this study, in the first phase, a novel architecture based on ensemble feature selection techniques include Modified Binary Bat Algorithm (NBBA), Binary Quantum Particle Swarm Optimization (QBPSO) Algorithm and Binary Quantum Gravita tional Search Algorithm (QBGSA) is hybridized with the Multi-layer Perceptron (MLP) classifier in order to select relevant feature subsets and improve classification accuracy. …”
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  5. 5
    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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  6. 6
    Nature-Inspired cognitive evolution to play Ms. Pac-Man

    Nature-Inspired cognitive evolution to play Ms. Pac-Man by Tse, Guan Tan, Jason Teo, Patricia Anthony

    Published 2011
    “…Some approaches have reported that it is able to solve dynamic problems and very useful for improving the performance of various complex systems. …”
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  7. 7
    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
    “…An improved version of Differential Evolution (DE) namely Backtracking Search Algorithm (BSA) is applied to several fed batch fermentation problems and its performance is compared with recent emerging metaheuristics such as Artificial Algae Algorithm (AAA), Artificial Bee Colony (ABC), Covariance Matrix Adaptation Evolution Strategy (CMAES) and DE. …”
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  8. 8
    A filtering algorithm for efficient retrieving of DNA sequence

    A filtering algorithm for efficient retrieving of DNA sequence by Abdul Rahman, Mohd Nordin, Mohd. Saman, Md. Yazid, Ahmad, Aziz, Md. Tap, Abu Osman

    Published 2009
    “…An automaton-based algorithm is used to develop the filtering process proposed. …”
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  9. 9
    Hybrid DE-PEM algorithm for identification of UAV helicopter

    Hybrid DE-PEM algorithm for identification of UAV helicopter by Tijani, Ismaila, Akmeliawati, Rini, Legowo, Ari, Budiyono, Agus, Abdul Muthalif, Asan Gani

    Published 2014
    “…Design/methodology/approach – In this study, flight data were collected and analyzed; MATLAB-based system identification algorithm was developed using DE and PEM; parameterized state-space model parameters were estimated using the developed algorithm and model dynamic analysis. …”
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  10. 10
    A Bayesian parameter learning procedure for nonlinear dynamical systems via the ensemble Kalman filter

    A Bayesian parameter learning procedure for nonlinear dynamical systems via the ensemble Kalman filter by Ur Rehman, M.J., Dass, S.C., Asirvadam, V.S.

    Published 2018
    “…Dynamical systems are a natural and convenient way to model the evolution of processes observed in practice. …”
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  11. 11
    Application of dynamic mesh to model surface evolution under solid particles erosion in positive choke geometries

    Application of dynamic mesh to model surface evolution under solid particles erosion in positive choke geometries by Baghdadi, Faical, Hrairi, Meftah, Asrar, Waqar

    Published 2026
    “…These findings contribute to the development of transient erosion models, addressing the limitations of steady-state models in capturing the dynamic evolution of choke geometry under erosion.…”
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  12. 12
    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
    “…Apart from the effectiveness of the optimized model, the proposed design algorithm is expected to facilitate timely development of the nonparametric model of the helicopter system.…”
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  13. 13
    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
    “…VL-WIDE was also integrated with the solution selection model based on the Analytical Hierarchical Process (AHP) that considers decision-maker preference for the optimized objectives. Comparing this developed algorithm with other algorithms shows its superiority in multi-objective optimization (MOO) evaluation metrics. …”
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  14. 14
    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
    “…Differential evolution (DE) is a simple yet powerful evolutionary algorithm (EA). …”
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  15. 15
    Performance analyses of adaptive handover decision algorithm using spectrum aggregation in long term evolution - advanced network

    Performance analyses of adaptive handover decision algorithm using spectrum aggregation in long term evolution - advanced network by Usman, I. H., Nordin, N. K., Omizegba, E. E., Sali, A., Rasid, M. F. A., Hashim, F.

    Published 2021
    “…This implied that the network operating under the proposed TVWS algorithm presented low radio link decoding errors when compared with the validation algorithms MIF and CONV. …”
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  16. 16
    Automating commercial video game development using computational intelligence

    Automating commercial video game development using computational intelligence by Tse, Guan Tan, Teo, Jason Tze Wi, Patricia Anthony

    Published 2011
    “…Pac-man. The resulting algorithm is referred to as an Evolution Strategies Neural Network or ESNet. …”
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  17. 17
    An FPGA implementation of exp-bet scheduling algorithm in LTE networks / Yusmardiah Yusuf

    An FPGA implementation of exp-bet scheduling algorithm in LTE networks / Yusmardiah Yusuf by Yusuf, Yusmardiah

    Published 2017
    “…It is performed by the scheduling algorithm implemented in the Long Term Evolution (LTE) base station, Evolved Node B. …”
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  18. 18
    Identification and predictive control of spray tower system using artificial neural network and differential evolution algorithm

    Identification and predictive control of spray tower system using artificial neural network and differential evolution algorithm by Danzomo, Bashir A., Salami, Momoh Jimoh Eyiomika, Khan, Md. Raisuddin

    Published 2015
    “…This includes the use of an artificial neural network (ANN) based predictive control strategy and differential evolution (DE) optimization algorithm to determines the optimal control signal, uk (liquid droplet size, dD) by minimizing the cost function such that the output is set below the allowable PM concentration. …”
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    Proceeding Paper
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  19. 19
    Agro-ento bioinformation: towards the edge of reality

    Agro-ento bioinformation: towards the edge of reality by Syed Hassan, Syed Tajuddin

    Published 2002
    “…The protocols range from the molecular levels to domains of larger dimensions such as those encompassing fraternities of politics and policies, and societal applications. These protocols, algorithms, and visualisations undergo dynamic incubation processes to produce the end product, which is bioinformation. …”
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  20. 20
    Nonlinear modeling and control of a spark ignition engine idle speed / Hazem Mohamed

    Nonlinear modeling and control of a spark ignition engine idle speed / Hazem Mohamed by Hazem, Mohamed

    Published 1998
    “…The input output data was collected from an experimental four cylinder spark ignition engine, then this data is fitted to a NARMAX model using a radial basis function network trained by the orthogonal least squares algorithm. After that the developed model is validated using nonlinear correlation tests and it could efficiently reproduce the plant dynamics. …”
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