Search Results - (( using function _ algorithm ) OR ( basic optimization model algorithm ))

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  1. 1

    Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems by Din, Fakhrud, Khalid, Shah, Fayaz, Muhammad, Gwak, Jeonghwan, Kamal Z., Zamli, Mashwani, Wali Khan

    Published 2022
    “…The performance of the fuzzy adaptive teaching learning-based optimization is evaluated against other metaheuristic algorithms including basic teaching learning-based optimization on 23 unconstrained global test functions. …”
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    Article
  2. 2

    Automated bilateral negotiation with incomplete information in the e-marketplace. by Jazayeriy, Hamid

    Published 2011
    “…The MGT algorithm is useful to explore the properties of the Pareto-optimal offers. …”
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    Thesis
  3. 3

    Modeling and control of a Pico-satellite attitude using Fuzzy Logic Controller by Zaridah, Mat Zain

    Published 2010
    “…The contribution of this work is to optimize the base of Fuzzy membership function of the APFLC by using GA technique. …”
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    Thesis
  4. 4

    Optimization of Upstream Offshore Oilfield Production Planning under Uncertainty and Downstream Crude Oil Scheduling at Refinery Front-End by Tan Yin Keong, Tan Yin

    Published 2012
    “…Having validated the model formulation and solution obtained, we believe that the model can be a useful basic tool to assist upper-level management in deciding on an optimal plan for crude oil production from an offshore operation. …”
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    Final Year Project
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    Backtracking search algorithm for optimal power dispatch in power system / Mostafa Modiri Delshad by Mostafa, Modiri Delshad

    Published 2016
    “…Backtracking search algorithm (BSA) as the new evolutionary technique of optimization is used for solving the problems. …”
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    Thesis
  7. 7

    Neural Network – A Black Box Model by Kuok, Kuok King, Chan, Chiu Po, Md. Rezaur, Rahman, Khairul Anwar, Mohamad Said, Chin Mei, Yun

    Published 2024
    “…A variety of metaheuristic algorithms have been used to train ANN, including Genetic Algorithms (GA), Particle Swarm Optimization (PSO), Simulated Annealing (SA), Ant Colony Optimization (ACO), Tabu Search (TS), and Harmony Search (HS). …”
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    Book Chapter
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    Intelligently tuned weights based robust H∞ controller design for pneumatic servo actuator system with parametric uncertainty by Ali, Hazem Ibrahim, Mohd Noor, Samsul Bahari, Bashi, Sinan Mahmod, Marhaban, Mohammad Hamiruce

    Published 2011
    “…The PSO algorithm is used to minimize the infinity norm of the transfer functions matrix of the nominal closed loop system to obtain the optimal parameters of the weighting function. …”
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    Article
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    Reproducing kernel Hilbert space method for cox proportional hazard model by Abdul Manaf, Nur'azah

    Published 2016
    “…Finally, we propose an algorithm of minimization of the loss function in the general Cox model. …”
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    Thesis
  12. 12

    Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling by Anuar, Nurul Izah

    Published 2022
    “…The experimentations of the proposed algorithm are conducted using existing benchmark instances and a published case study on an energy-efficient job-shop model. …”
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    Thesis
  13. 13

    Long-term optimal planning for renewable based distributed generators and battery energy storage systems toward enhancement of green energy penetration by ALAhmad A.K., Verayiah R., Shareef H.

    Published 2025
    “…The backward reduction method (BRM) is then applied to streamline the number of generated scenarios, reducing computational efforts. To solve the optimization planning model, a hybrid optimization algorithm is proposed, combining the non-dominating sorting genetic algorithm (NSGAII) and multi-objective particle swarm optimization (MOPSO). …”
    Article
  14. 14

    Improving neural networks training using experiment design approach by Chong, Wei Kean

    Published 2005
    “…There are several methods of selecting training data from input space for neural networks which include D-optimal and Max-min design approaches. Consider a function approximation problem (Neural Network using Radial Basic Function structure) and limit the amount of training data, say (m) from N amount of possible data. …”
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    Thesis
  15. 15

    EMG motion pattern classification through design and optimization of neural network by Ahsan, Md. Rezwanul, Ibrahimy, Muhammad Ibn, Khalifa, Othman Omran

    Published 2012
    “…The ANN models work in parallel thus providing higher computational performance than traditional classifiers which function sequentially. …”
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    Proceeding Paper
  16. 16

    Model Identification Using Neuro-Fuzzy Approach by Lemma, T.A.

    Published 2018
    “…Last section of the chapter deals with three different model training algorithms Least squares based, back-propagation and particle swarm optimization. …”
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    Article
  17. 17

    Model Identification Using Neuro-Fuzzy Approach by Lemma, T.A.

    Published 2018
    “…Last section of the chapter deals with three different model training algorithms Least squares based, back-propagation and particle swarm optimization. …”
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    Article
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    Power System State Estimation In Large-Scale Networks by NURSYARIZAL MOHD NOR, NURSYARIZAL

    Published 2010
    “…The gain and the Jacobian matrices associated with the basic algorithm require large storage and have to be evaluated at every iteration, resulting in more computation time. …”
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    Thesis