Search Results - (( problem implementation using algorithm ) OR ( parameter optimization strategy algorithm ))

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  1. 1

    The design and applications of the african buffalo algorithm for general optimization problems by Odili, Julius Beneoluchi

    Published 2017
    “…A critical look at these ‘efficient’ stochastic algorithms reveals the need for improvements in the areas of effectiveness, the number of several parameters used, premature convergence, ability to search diverse landscapes and complex implementation strategies. …”
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  2. 2

    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
    “…ARDE algorithm makes use of JADE strategy and the MDE_pBX parameters adaptive schemes as frameworks. …”
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  3. 3

    Improved flower pollination optimization algorithm based on swap operator and dynamic switch probability selection by Iqbal, Muhammad

    Published 2023
    “…Meta-heuristic algorithms have become popular in finding optimal solutions for nonlinear complex problems. …”
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  4. 4

    PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM by ABDALLA, OSMAN AHMED

    Published 2011
    “…This research focuses on the use of binaryencoded genetic algorithm (GA) to implement efficient search strategies for the optimal architecture and training parameters of a multilayer feed-forward ANN. …”
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  5. 5

    The effect of job satisfaction on the relationship between organizational culture and organizational performance by Imran, Muhammad

    Published 2023
    “…Meta-heuristic algorithms have become popular in finding optimal solutions for nonlinear complex problems. …”
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  6. 6

    Power generation allocation in smart grid using Dwarf Mongoose Optimization / Mohamad Irfan Shamani by Shamani, Mohamad Irfan

    Published 2025
    “…A real-word problem where DMO could be used is optimization energy allocation within power generation system. …”
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  7. 7

    Hybrid evolutionary optimization algorithms: A case study in manufacturing industry by Vasant, P.

    Published 2014
    “…This membership function is applied for its useful performance through industrial production problems by employing hybrid evolutionary optimization algorithms. …”
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    Book
  8. 8

    Genetic Algorithms In Optimizing Membership Function For Fuzzy Logic Controller by Ismail, H. Muh Yusuf

    Published 2010
    “…This study investigates the use of Genetic Algorithms (GA) to design and implement of Fuzzy Logic Controllers (FLC). …”
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  9. 9

    Algorithmic design issues in adaptive differential evolution schemes: Review and taxonomy by Al-Dabbagh, Rawaa Dawoud, Neri, Ferrante, Idris, Norisma, Baba, Mohd Sapiyan

    Published 2018
    “…A trend that has emerged recently is to make the algorithm parameters automatically adapt to different problems during optimization, thereby liberating the user from the tedious and time-consuming task of manual setting. …”
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    Article
  10. 10

    Optimal design of a 3D-printed scaffold using intelligent evolutionary algorithms by Asadi-Eydivand, M., Solati-Hashjin, M., Fathi, A., Padashi, M., Abu Osman, Noor Azuan

    Published 2016
    “…First, particle swarm optimization algorithm was implemented to obtain the optimum topology of the AANN. …”
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    Article
  11. 11

    Nomadic people optimizer (NPO) for large-scale optimization problems by Mohamd Salih, Sinan Qahtan

    Published 2019
    “…Three major problems are encountered when designing metaheuristics; the first problem is balancing exploration with exploitation capabilities (which leads to premature convergence or trapping in the local minima), while the second problem is the dependency of the algorithm on the controlling parameters, which are parameters with unknown optimal values. …”
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  12. 12

    Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems by Nor Sakinah, Abdul Shukor

    Published 2019
    “…SED offers memory-based features and effectiveness to perform with lesser computation time to overcome a range of optimization problems, even for high-dimensional parameter tuning. …”
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  13. 13

    Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems by Nor Sakinah, Abdul Shukor

    Published 2019
    “…SED offers memory-based features and effectiveness to perform with lesser computation time to overcome a range of optimization problems, even for high-dimensional parameter tuning. …”
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    Development of efficient t-way test data generation algorithm and execution strategies by Khandakar Fazley, Rabbi

    Published 2012
    “…This strategy is able to reduce the number of test data, but the execution time is not optimized. …”
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    Discrete-time system identification using genetic algorithm with single parent-based mating technique by Zainuddin, Farah Ayiesya

    Published 2024
    “…The introduction of the SPM technique represents a significant enhancement in the performance of GA, particularly in terms of improving genetic diversity and search optimization . The findings provide a robust framework for applying GAs to complex modeling problems, emphasizing the importance of effective crossover strategies and genetic diversity . …”
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  19. 19

    Structural health monitoring using adaptive wavelet functions / Seyed Hossein Mahdavi by Seyed Hossein, Mahdavi

    Published 2016
    “…For this purpose, a wavelet-based GAs strategy is improved by using free-scaled adaptive wavelets to optimally identify unknown structural parameters. …”
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  20. 20

    Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach by Wan Solehah, Wan Ahmad

    Published 2022
    “…The other one is the network training’s environment optimization that is done through hyperparameter optimization by selecting and fine-tuning high impact parameters which include Optimizer, Learning Rate and Dropout to reduce error rate (loss function). …”
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