Search Results - addition _ different evolutionary algorithm

Search alternatives:

Refine Results
  1. 1
  2. 2

    Evolutionary Fuzzy ARTMAP Neural Networks for Classification of Semiconductor Defects by Zuwairie, Ibrahim, Tan, Shing Chiang, Watada, Junzo, Marzuki, Khalid

    Published 2014
    “…In addition, one of the proposed EANNs incorporates a facility to learn overlapping samples of different classes from the imbalanced data environment. …”
    Get full text
    Get full text
    Get full text
    Article
  3. 3

    Artificial Neural Controller Synthesis in Autonomous Mobile Cognition by Kim On Chin, Jason Teo

    Published 2009
    “…Furthermore, three additional testing results have been incorporated from the robustness perspective: different robot localizations, inclusion of two obstacles, and moving signal source experiments, respectively. …”
    Get full text
    Get full text
    Article
  4. 4

    Artificial Neural Controller Synthesis in Autonomous Mobile Cognition by Chin Kim On, Jason Teo

    Published 2009
    “…Furthermore, three additional testing results have been incorporated from the robustness perspective: different robot localizations, inclusion of two obstacles, and moving signal source experiments, respectively. …”
    Get full text
    Get full text
    Get full text
    Article
  5. 5
  6. 6

    Investigation of evolutionary multi-objective algorithms in solving view selection problem / Seyed Hamid Talebian by Talebian, Seyed Hamid

    Published 2013
    “…In addition to the normal metrics, the computational time for executing each algorithm was also measured and compared. …”
    Get full text
    Get full text
    Thesis
  7. 7

    Optimized Cover Selection for Audio Steganography Using Multi-Objective Evolutionary Algorithm by Noor Azam, Muhammad Harith, Ridzuan, Farida, Mohd Sayuti, M Norazizi Sham

    Published 2023
    “…One of the search methods commonly used to find solutions for the trade-off problem in various fields is the Multi-Objective Evolutionary Algorithm (MOEA). Therefore, this research proposed a new method for optimising cover audio selection for audio steganography using the Non-dominated Sorting Genetic Algorithm-II (NSGA-II), which falls under the MOEA Pareto dominance paradigm. …”
    Get full text
    Get full text
    Get full text
    Article
  8. 8

    Identifying movement of object in multiple images via particle swarm optimization algorithm / Mohd Haidhar Iqbal Hassan by Iqbal Hassan, Mohd Haidhar

    Published 2016
    “…This project used one of algorithm from category Evolutionary Computing (EC) and that algorithm is Particle Swarm Optimization (PSO). …”
    Get full text
    Get full text
    Student Project
  9. 9

    Impact of genetic operators on energy-efficient wireless sensor network by Vincent Chung, Norah Tuah, Lim, Kit Guan, Tan, Min Keng, Huang, Hui, Teo, Kenneth Tze Kin

    Published 2019
    “…The metaheuristic genetic algorithm is an evolutionary algorithm which means that it will always evolve to get an optimum solution. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Proceedings
  10. 10
  11. 11
  12. 12

    Multi-Objective Portfolio Optimization Strategy using the SPEA-II Algorithm by Azarberahman, Alireza, Tohidinia, Malihe, Aliakbarzadeh, Hossein

    Published 2025
    “…In addition, the SPEA- II algorithm showed significant efficiency and stability across different frequencies and time periods. …”
    Get full text
    Get full text
    Get full text
    Article
  13. 13
  14. 14

    Hybrid flow shop scheduling problem with energy utilization using non-dominated sorting genetic algorithm-III (NSGA-III) optimization by Muhammad Ammar, Nik Mu’tasim, Mohd Fadzil Faisae, Ab Rashid

    Published 2023
    “…The model was compared with the most sought algorithm and latest multi-objective algorithms, Strength Pareto Evolutionary Algorithm 2 (SPEA -II), Multi-Objective Algorithm Particle Swarm Optimization (MOPSO), Pareto Envelope-based Selection Algorithm II (PESA-II) and Multi-objective Evolutionary Algorithm based on Decomposition (MOEA/D). …”
    Get full text
    Get full text
    Get full text
    Article
  15. 15

    Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms by Koh, Johnny Siaw Paw

    Published 2008
    “…Comparison results of different combinatorial operators, and tests with different probability factors are shown. …”
    Get full text
    Get full text
    Thesis
  16. 16

    A hybrid bat–swarm algorithm for optimizing dam and reservoir operation by Yaseen, Zaher Mundher, Allawi, Mohammed Falah, Karami, Hojat, Ehteram, Mohammad, Farzin, Saeed, Ahmed, Ali Najah, Koting, Suhana, Mohd, Nuruol Syuhadaa, Jaafar, Wan Zurina Wan, Afan, Haitham Abdulmohsin, El-Shafie, Ahmed

    Published 2019
    “…The proposed HB-SA is validated by minimizing irrigation deficits using a multireservoir system consisting of the Golestan and Voshmgir dams in Iran. In addition, different optimization algorithms from previous studies are investigated to compare the performance of the proposed algorithm with existing algorithms for the same case study. …”
    Get full text
    Get full text
    Article
  17. 17

    A novel clustering based genetic algorithm for route optimization by Aibinu, Abiodun Musa, Salau, Habeeb Bello, Najeeb, Athaur Rahman, Nwohu, Mark Ndubuka, Akachukwu, Chichebe

    Published 2016
    “…Genetic Algorithm (GA), a random universal evolutionary search technique that imitates the principle of biological evolution has been applied in solving various problems in different fields of human endeavor. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  18. 18
  19. 19

    A high-performance democratic political algorithm for solving multi-objective optimal power flow problem by Ahmadipour, Masoud, Ali, Zaipatimah, Othman, Muhammad Murtadha, Bo, Rui, Javadi, Mohammad Sadegh, Ridha, Hussein Mohammed, Alrifaey, Moath

    Published 2024
    “…The proposed approach is tested and validated on IEEE 57-bus and IEEE 118-bus systems with different case studies. Simulation results are analyzed and compared with two popular and commonly used multi-objective-evolutionary algorithms namely, non-dominated sorting genetic algorithm II (NSGA-II) and the multi-objective particle swarm optimization (MOPSO) on the problem. …”
    Get full text
    Get full text
    Article
  20. 20

    A high-performance democratic political algorithm for solving multi-objective optimal power flow problem by Ahmadipour M., Ali Z., Othman M.M., Bo R., Javadi M.S., Ridha H.M., Alrifaey M.

    Published 2025
    “…The proposed approach is tested and validated on IEEE 57-bus and IEEE 118-bus systems with different case studies. Simulation results are analyzed and compared with two popular and commonly used multi-objective-evolutionary algorithms namely, non-dominated sorting genetic algorithm II (NSGA-II) and the multi-objective particle swarm optimization (MOPSO) on the problem. …”
    Article