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  1. 1

    Loss reduction in distribution networks using new network reconfiguration algorithm by Kashem, M.A., Moghavvemi, M., Mohamed, A., Jasmon, G.B.

    Published 1996
    “…The first stage of this solution algorithm finds a loop which gives the maximum loss reduction in the network. …”
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    Article
  2. 2

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

    Published 2010
    “…The proposed solution to this problem is based on a general combinatorial optimization algorithm known as Genetic Algorithm, and the load flow equations in distribution network. …”
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    Thesis
  3. 3

    Loss reduction in distribution networks by network reconfiguration: a two stage solution approach by Nallagownden, Perumal

    Published 2004
    “…The first stage of this solution algorithm finds a loop, which gives the maximum loss reduction in the network. …”
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    Conference or Workshop Item
  4. 4

    Enhanced Adaptive Confidence-Based Q Routing Algorithms For Network Traffic by Yap, Soon Teck

    Published 2004
    “…An integrated solution for the above problem is the ECQ Routing Algorithm. …”
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    Thesis
  5. 5

    Fine-tuning approach in metaheuristic algorithm to prolong wireless sensor networks nodes lifetime by Rahiman, Amir Rizaan, Williams, Temitope Betty, Zakaria, Muhammad D.

    Published 2022
    “…A set of simulations has been performed using MATLAB R2018b on the proposed solution, namely the energy efficient of genetic (EEG) algorithm and has revealed that the solution outperforms the network lifetime and cluster head load of the existing solution.…”
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    Article
  6. 6

    Comparison between Lamarckian Evolution and Baldwin Evolution of neural network by Taha, Imad, Inazy, Qabas

    Published 2006
    “…Baldwinian learning uses learning algorithm to change the fitness landscape, but the solution that is found is not encoded back into genetic string. …”
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    Article
  7. 7

    Decentralized traffic signal control for grid traffic network using genetic algorithm by Min Keng Tan, Helen Sin Ee Chuo, Kiam Beng Yeo, Renee Ka Yin Chin, Sha Huang, Kenneth Tze Kin Teo

    Published 2019
    “…Besides, the inherent deterministic behavior limits the algorithm to explore the solution space in searching for the optimum traffic solution. …”
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    Proceedings
  8. 8

    Development of a multi-objective optimization model for transport and environment in a closed-loop automotive supply chain by Sadrnia, Abdolhossein

    Published 2014
    “…In the last stage, an extended Gravitational Search Algorithm (GSA) as a parallel search algorithm and high convergence rate into high quality final solutions is used to solve the proposed mathematical model and to achieve the Pareto set of solution. …”
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    Thesis
  9. 9

    A survey of state of the art: hierarchical routing algorithms for wireless sensor networks by Kareem, Husam, Hashim, Shaiful Jahari, Sali, Aduwati, Subramaniam, Shamala

    Published 2014
    “…Many researches have been done to solve this problem or at least find a solution to decrease the energy consumption. One of those solutions is using efficient routing algorithm. …”
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    Article
  10. 10
  11. 11

    A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks / Salmah Fattah by Salmah , Fattah

    Published 2022
    “…The algorithm introduces the fuzzy Pareto dominance concept to compare two solutions and uses the scalar decomposition method when one solution cannot dominate the other in terms of the fuzzy dominance level. …”
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    Thesis
  12. 12

    A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks by Salmah Fattah

    Published 2022
    “…The algorithm introduces the fuzzy Pareto dominance concept to compare two solutions and uses the scalar decomposition method when one solution cannot dominate the other in terms of the fuzzy dominance level. …”
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    Thesis
  13. 13

    Hybrib NSGA-II optimization for improving the three-term BP network for multiclass classification problems by Ibrahim, Ashraf Osman, Shamsuddin, Siti Mariyam, Qasem, Sultan Noman

    Published 2015
    “…This paper presents a hybrid of the multiobjective evolutionary algorithm to gain a better accuracy of the fi nal solutions.The aim of using the hybrid algorithm is to improve the multiobjective evolutionary algorithm performance in terms of the enhancement of all the individuals in the population and increase the quality of the Pareto optimal solutions.The multiobjective evolutionary algorithm used in this study is a nondominated sorting genetic algorithm-II (NSGA-II) together with its hybrid, the backpropagation algorithm (BP), which is used as a local search algorithm to optimize the accuracy and complexity of the three-term backpropagation (TBP) network. …”
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    Article
  14. 14

    Hybrid NSGA-II Optimization for Improving the Three-Term BP Network for Multiclass Classification Problems by Ibrahim, Ashraf Osman, Shamsuddin, Siti Mariyam, Qasem, Sultan Noman

    Published 2015
    “…The multiobjective evolutionary algorithm used in this study is a nondominated sorting genetic algorithm-II (NSGA-II) together with its hybrid, the backpropagation algorithm (BP), which is used as a local search algorithm to optimize the accuracy and complexity of the three-term backpropagation (TBP) network. …”
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    Article
  15. 15

    Attack path selection optimization with adaptive genetic algorithms by Abd Rahman, A.S., Zakaria, M.N., Masrom, S.

    Published 2016
    “…This paper describes our project that has the ultimate goal of providing optimized solutions for enterprise network security. We describe our approach for implementing an optimized security assessment using Genetic Algorithm (GA). …”
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    Article
  16. 16

    Attack path selection optimization with adaptive genetic algorithms by Abd Rahman, A.S., Zakaria, M.N., Masrom, S.

    Published 2016
    “…This paper describes our project that has the ultimate goal of providing optimized solutions for enterprise network security. We describe our approach for implementing an optimized security assessment using Genetic Algorithm (GA). …”
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    Article
  17. 17

    Weight Optimization in Recurrent Neural Networks with Hybrid Metaheuristic Cuckoo Search Techniques for Data Classification by Nawi, N.M., Khan, A., Rehman, M.Z., Chiroma, H., Herawan, T.

    Published 2015
    “…The proposed CSERN and CSBPERN algorithms are compared with artificial bee colony using BP algorithm and other hybrid variants algorithms. …”
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    Article
  18. 18

    Efficient and secured compression and steganography technique in wireless sensor network by Tuama, Ammar Yaseen

    Published 2016
    “…The proposed solution comes with low complexity and is used to en- hance the security of the standard LSB algorithm by replacing an originally less secured sequential data hiding with a random pixel selection. …”
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    Thesis
  19. 19

    Improved cuckoo search based neural network learning algorithms for data classification by Abdullah, Abdullah

    Published 2014
    “…Specifically, 6 benchmark classification datasets are used for training the hybrid Artificial Neural Network algorithms. …”
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    Thesis
  20. 20

    Wavelet neural networks based solutions for elliptic partial differential equations with improved butterfly optimization algorithm training by Lee, Sen Tan, Zainuddin, Zarita, Ong, Pauline

    Published 2020
    “…Although the gradient information of the commonly used gradient descent training algorithm in WNNs may direct the search to optimal weight solutions that minimize the error function, the learning process is slow due to the complex calculation of the partial derivatives. …”
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    Article