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  1. 1
    Evolutionary algorithm based network coding for optmization of intelligent vehicular ad hoc network

    Evolutionary algorithm based network coding for optmization of intelligent vehicular ad hoc network by Lee, Chun Hoe

    Published 2017
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  2. 2
    Intelligent energy systems using the barnacles mating optimizer and evolutionary mating algorithm: Foundations, methods, and applications

    Intelligent energy systems using the barnacles mating optimizer and evolutionary mating algorithm: Foundations, methods, and applications by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

    Published 2026
    “…Intelligent Energy Systems using the Barnacles Mating Optimizer and Evolutionary Mating Algorithm: Foundations, Methods, and Applications reveals the potential of innovative optimization algorithms to support sustainability in modern energy systems. …”
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  3. 3
    Evolutionary algorithm based network coding for optimization of intelligent vehicular ad hoc network

    Evolutionary algorithm based network coding for optimization of intelligent vehicular ad hoc network by Lee, Chun Hoe

    Published 2017
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  4. 4
    A hybrid ANN for output power prediction and online monitoring in grid-connected photovoltaic system / Puteri Nor Ashikin Megat Yunus

    A hybrid ANN for output power prediction and online monitoring in grid-connected photovoltaic system / Puteri Nor Ashikin Megat Yunus by Megat Yunus, Puteri Nor Ashikin

    Published 2023
    “…After that, a hybrid of MLFNN with other optimization methods was introduced, i.e. Improved Fast Evolutionary Programming (IFEP), Evolutionary Programming- Dolphin Echolocation Algorithm (EPDEA) and Evolutionary Programming-Firefly Algorithm (EPFA). …”
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  5. 5
    Autonomous Robot Navigation in Unknown Maze Environment

    Autonomous Robot Navigation in Unknown Maze Environment by Nur Aqilah binti Mustafa, Nur Aqilah

    Published 2012
    “…The objective of this project is to design and develop an autonomous robot navigation using a selected algorithm which is pledge algorithm by using the concept of obstacle avoidance besides studying its accuracy to solve the given environment. …”
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  6. 6
    A new islanding detection technique based on passive parameter using a combination of artificial neural network and evolutionary programming algorithm / Hasmaini Mohamad …[et al.]

    A new islanding detection technique based on passive parameter using a combination of artificial neural network and evolutionary programming algorithm / Hasmaini Mohamad …[et al.]... by Mohamad, Hasmaini, Ab Salam, Aimie Nadia, Md Razali, Norhasniza, Salim, Nur Ashida, Mat Yasin, Zuhaila

    Published 2021
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  7. 7
    Evolutionary tuning of modular fuzzy controller for two-wheeled wheelchair

    Evolutionary tuning of modular fuzzy controller for two-wheeled wheelchair by Ahmad, Salmiah, Siddique, Nazmul H., Tokhi, Mohammad Osman

    Published 2012
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  8. 8
    Computational intelligence technique for DG installation within contingency scenario / Muhamad Saifullah Mahmud Affandi

    Computational intelligence technique for DG installation within contingency scenario / Muhamad Saifullah Mahmud Affandi by Mahmud Affandi, Muhamad Saifullah

    Published 2014
    “…This operational coding was developed in MatLAB and conducted on the test system, that is IEEE 69-bus radial distribution system.…”
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  9. 9
    Evolutionary cost-cognizant regression test case prioritization for object-oriented programs

    Evolutionary cost-cognizant regression test case prioritization for object-oriented programs by Bello, AbdulKarim

    Published 2019
    “…Afterward evolutionary algorithm (EA) was employed to prioritize test cases based on the rate severity of fault detection per unit test cost. …”
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  10. 10
    Design of intelligent control system and its application on fabricated conveyor belt grain dryer

    Design of intelligent control system and its application on fabricated conveyor belt grain dryer by Lutfy, Omar F.

    Published 2011
    “…This controller has several advantages over its conventional ANFIS counterpart, particularly the reduction in processing time. Moreover, three evolutionary algorithms (EAs), in particular a real-coded genetic algorithm (GA), a particle swarm optimization (PSO), and a global-best harmony search (GHS), were separately used to train the proposed controller and to determine its scaling factors. …”
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