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  1. 1
    Network reconfiguration and control for loss reduction using genetic algorithm

    Network reconfiguration and control for loss reduction using genetic algorithm by Jawad, Mohamed Hassan Izzaldeen

    Published 2010
    “…While in the 49-bus system the existing 7 capacitors are rearrange using Genetic Algorithm in obtaining minimal total power losses. …”
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  2. 2
    Optimal location and size estimation of distributed generators by employing grouping particle swarm optimization and grouping genetic algorithm

    Optimal location and size estimation of distributed generators by employing grouping particle swarm optimization and grouping genetic algorithm by Mohammed, Zahraa Abdulkareem

    Published 2017
    “…These algorithms are used to obtain the optimal size of distributed generators units to be installed at optimal locations, which are obtained using loss sensitivity factor. …”
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  3. 3
    Offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm: article / Deezex Noor Ainizaa Abdullah

    Offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm: article / Deezex Noor Ainizaa Abdullah by Abdullah, Deezex Noor Ainizaa

    Published 2009
    “…This paper present offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm. …”
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  4. 4
    Offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm / Deezex Noor Ainizaa Abdullah

    Offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm / Deezex Noor Ainizaa Abdullah by Abdullah, Deezex Noor Ainizaa

    Published 2009
    “…This paper present offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm. …”
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  5. 5
    Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof

    Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof by Yusof, Yusman

    Published 2019
    “…In order to learn the optimized states-action policy the self-learning algorithm is developed using hybrid AI algorithm by combining unsupervised weightless neural network, which employs AUTOWiSARD and reinforcement learning algorithm, which employs Q-learning. …”
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  6. 6
    Power system network splitting and load frequency control optimization using ABC based algorithms / Kanendra Naidu a/l Vijyakumar

    Power system network splitting and load frequency control optimization using ABC based algorithms / Kanendra Naidu a/l Vijyakumar by Vijyakumar, Kanendra Naidu

    Published 2015
    “…This research presents a modified optimization program for the system splitting problem in large scale power system based on Artificial Bee Colony algorithm and graph theory. …”
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  7. 7
    Automated-tuned hyper-parameter deep neural network by using arithmetic optimization algorithm for Lorenz chaotic system

    Automated-tuned hyper-parameter deep neural network by using arithmetic optimization algorithm for Lorenz chaotic system by Nurnajmin Qasrina Ann, ., Pebrianti, Dwi, Mohammad Fadhil, Abas, Bayuaji, Luhur

    Published 2023
    “…This study proposes an automated-tuned hyper-parameter for DNN using a metaheuristic optimization algorithm, arithmetic optimization algorithm (AOA). …”
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  8. 8
    One day ahead daily peak hour load forecasting by using invasive weed optimization learning algorithm based Artificial Neural Network

    One day ahead daily peak hour load forecasting by using invasive weed optimization learning algorithm based Artificial Neural Network by Rahim, Muhammad Fitri

    Published 2012
    “…Hence, this indicates that Invasive Weed Optimization could be implemented as a new learning algorithm for an Artificial Neural Network.…”
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  9. 9
    A Study On The Application Of Gravitational Search Algorithm In Optimizing Stereo Matching Algorithm’s Parameters For Star Fruit Inspection System

    A Study On The Application Of Gravitational Search Algorithm In Optimizing Stereo Matching Algorithm’s Parameters For Star Fruit Inspection System by Zainal Abidin, Amar Faiz, Mohd Ali, Nursabillilah, Mat Zain, Norlina, Abdul Majid, Masmaria, Rifin, Rozi, Kadiran, Kamaru Adzha, Mohd Mokji, Ahmad Musa, Tan, Kok, Amirulah, Rahman

    Published 2018
    “…The implemented Stereo Matching Algorithm used on the system comes from the built-in Matlab library. …”
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  10. 10
    Route Optimization System

    Route Optimization System by Zulkifli, Abdul Hayy

    Published 2005
    “…It has been used in other networks beside roads, for instance, pipe networks or railway networks. …”
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  11. 11
    Enhancing Market-Based Scheduling Algorithm on Globally Distributed Web Servers Using Least Suitable Sealed Bid Technique

    Enhancing Market-Based Scheduling Algorithm on Globally Distributed Web Servers Using Least Suitable Sealed Bid Technique by Al-Ewiwi, Mahmoud

    Published 2006
    “…These agents work cooperatively with each other through the Internet using message exchanging.An improved algorithm was implemented to decrease the amount of message exchanging between agents, which increased the performance of the system.…”
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  12. 12
    Implementation of a new Preference Based Final Year Project title selection system for undergraduate engineering students in UNITEN

    Implementation of a new Preference Based Final Year Project title selection system for undergraduate engineering students in UNITEN by Hasan M.H., Mohamed Sahari K.S., Anuar A.

    Published 2023
    “…The Network Flow Optimization algorithm, which was able to produce a selection with the lowest cost, was selected and used to allocate titles for students from Semester 1 of the 2009/2010 academic year. …”
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  13. 13
    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
    “…However, going by a first principle approach based on physical laws governing the dynamics of the system, this task is noted to be highly challenging due to the complex nonlinear characteristics of the helicopter system.On the other hand, the problem of determining network architecture for optimal/sub-optimal performances has been one of the major challenges in the use of the non parametric approach based on Nonlinear AutoRegressive with eXogenous inputs Network(NARX-network). …”
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  14. 14
    Efficient radio resource management algorithms for downlink long term evolution networks

    Efficient radio resource management algorithms for downlink long term evolution networks by Mamman, Maharazu

    Published 2018
    “…Optimal priority algorithm uses minimum data rate to guarantees resource allocation to users but increases the average delay and deteriorate the network performance. …”
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  15. 15
    Optimal vehicle to grid planning and scheduling using double layer multi-objective algorithm

    Optimal vehicle to grid planning and scheduling using double layer multi-objective algorithm by Tan K.M., Ramachandaramurthy V.K., Yong J.Y.

    Published 2023
    “…Algorithms; Charging (batteries); Curve fitting; Electric load flow; Electric power systems; Electric vehicles; Energy management systems; Optimization; Reactive power; Real time control; Scheduling; Vehicles; Voltage control; Voltage regulators; Battery chargers; Bidirectional power flow; Multi objective algorithm; Optimization algorithms; Reactive power compensation; Real-time implementations; Revolutionary technology; Vehicle to grids; Electric power transmission networks; algorithm; electric vehicle; electricity supply; energy flow; energy planning; energy use; optimization; technological development…”
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  16. 16
    Automated-tuned hyper-parameter deep neural network by using arithmetic optimization algorithm for Lorenz chaotic system

    Automated-tuned hyper-parameter deep neural network by using arithmetic optimization algorithm for Lorenz chaotic system by Ayop Azmi, Nurnajmin Qasrina Ann, Pebrianti, Dwi, Abas, Mohammad Fadhil, Bayuaji, Luhur

    Published 2023
    “…This study proposes an automated-tuned hyper�parameter for DNN using a metaheuristic optimization algorithm, arithmetic optimization algorithm (AOA). …”
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  17. 17
    Optimization of overcurrent relays coordination using Artificial Hummingbird Algorithm (AHA)

    Optimization of overcurrent relays coordination using Artificial Hummingbird Algorithm (AHA) by Noor Zaihah, Jamal, Arfan Haziq, Fathul Azmi

    Published 2023
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  18. 18
    Coordinated and optimal voltage control for voltage regulation using firefly algorithm

    Coordinated and optimal voltage control for voltage regulation using firefly algorithm by Kamarudin M.N., Hashim T.J.T.

    Published 2023
    “…Firefly Algorithm (FA) which is a known heuristic optimization technique for finding the optimal solution is used in this work. …”
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  19. 19
    Hierarchical multi-agent system in traffic network signalization with improved genetic algorithm

    Hierarchical multi-agent system in traffic network signalization with improved genetic algorithm by Tan, Min Keng, Chuo, Helen Sin Ee, Chin, Renee Ka Yin, Yeo, Kiam Beng, Teo, Kenneth Tze Kin

    Published 2019
    “…Instead of using classical offline data-driven optimization technique in traffic network signal control, this work aims to explore the potential of implementing an online data-driven optimization technique. …”
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  20. 20
    Multi-objective service restoration in distribution networks using genetic algorithm

    Multi-objective service restoration in distribution networks using genetic algorithm by Moazami, Ehsan

    Published 2013
    “…This thesis presents a new approach of supply restoration service using the Genetic Algorithm. The GA is robust in searching a global optimal solution for the large-scale combinatorial optimization problems. …”
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