Search Results - (( based optimization approach algorithm ) OR ( variable optimization method algorithm ))

Refine Results
  1. 1

    Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

    Published 2018
    “…The optimized GEP as a recent extension of GEP approach is superior to other AI-based methods in giving an optimized explicit equation, which clearly shows the relationship between input historical data and EEC in different countries without prior knowledge about the nature of the relationships between independent and dependent variables. …”
    Get full text
    Get full text
    Get full text
    Thesis
  2. 2

    Optimizing Decentralized Exam Timetabling with a Discrete Whale Optimization Algorithm by Emily Siew, Sing Kiang, Sze, San Nah, Goh, Say Leng

    Published 2025
    “…This paper presents a novel discrete Whale Optimization Algorithm approach, integrating the strengths of population-based and local-search algorithms for addressing the examination timetabling problem, a significant challenge many educational institutions face. …”
    Get full text
    Get full text
    Get full text
    Article
  3. 3

    Optimizing decentralized exam timetabling with a discrete whale optimization algorithm by Emily Sing Kiang Siew, San nah sze, Say leng goh

    Published 2025
    “…This paper presents a novel discrete Whale Optimization Algorithm approach, integrating the strengths of population-based and local-search algorithms for addressing the examination timetabling problem, a significant challenge many educational institutions face. …”
    Get full text
    Get full text
    Get full text
    Article
  4. 4

    Harmony search-based robust optimal controller with prior defined structure by Rafieishahemabadi, Ali

    Published 2013
    “…In the first level, a new method for analytical formulation of integral square error cost function based on controller variables is elaborated for performance evaluation purposes by the proposed optimization algorithm. …”
    Get full text
    Get full text
    Thesis
  5. 5

    Optimizing the placement of fire department in Kulim using greedy heuristic and simplex method / Muhammad Abu Syah Mohd Suzaly by Mohd Suzaly, Muhammad Abu Syah

    Published 2023
    “…The first method is greedy heuristic method. Greedy heuristics is a type of optimization algorithm that makes decisions based on locally optimal solutions. …”
    Get full text
    Get full text
    Thesis
  6. 6
  7. 7
  8. 8

    Data-driven continuous-time Hammerstein modeling with missing data using improved Archimedes optimization algorithm by Islam, Muhammad Shafiqul, Mohd Ashraf, Ahmad

    Published 2024
    “…Across all experiments, the IAOA-based method demonstrated superior performance compared to AOA and other methods, including a hybrid approach combining the average multi-verse optimizer and sine cosine algorithm, particle swarm optimizer, the sine cosine algorithm, multi-verse optimizer and grey wolf optimizer. …”
    Get full text
    Get full text
    Get full text
    Article
  9. 9

    The performance of Taguchi�s T-method with binary bat algorithm based on great value priority binarization for prediction by Marlan Z.M., Ramlie F., Jamaludin K.R., Harudin N.

    Published 2023
    “…This paper proposes an optimization algorithm based on the Binary Bat algorithm methodology for replacing the conventional orthogonal array approach. …”
    Article
  10. 10

    Metaheuristic Algorithm for Wellbore Trajectory Optimization by Biswas, K., Vasant, P.M., Vintaned, J.A.G., Watada, J.

    Published 2019
    “…From those methods in this study, we have focused on metaheuristic approaches based on PSO (particle swarm optimization) which will be used to optimize wellbore trajectory. …”
    Get full text
    Get full text
    Conference or Workshop Item
  11. 11

    Taguchi?s T-method with Normalization-Based Binary Bat Algorithm by Marlan Z.M., Jamaludin K.R., Harudin N.

    Published 2025
    “…s orthogonal array is used as a variable selection approach in optimizing the predictive model. …”
    Conference paper
  12. 12

    Design optimization of valve timing at various engine speeds using Multi-Objective Genetic Algorithm (MOGA) by Mohiuddin, A. K. M., Ashour, Ahmed Aly Ibrahim Shaaban, Yap, Haw Shin

    Published 2008
    “…The paper conducts design optimization of CAMPRO 1.6L (S4PH) engine valve timing at various engine speeds using multi-objective genetic algorithm (MOGA) for the future variable valve timing (VVT) system research and development. …”
    Get full text
    Get full text
    Proceeding Paper
  13. 13

    A new algorithm for normal and large-scale optimization problems: Nomadic People Optimizer by Alsewari, Abdul Rahman Ahmed, Sinan, Q. Salih

    Published 2019
    “…The proposed and the benchmark algorithms are tested for large-scale optimization problems which are associated with high-dimensional variability. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  14. 14

    A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

    Published 2024
    “…To summarise, metaheuristic algorithms can give a superior optimization approach than the traditional artificial neural network method, providing the computing time is within an acceptable range. …”
    Get full text
    Get full text
    Get full text
    Thesis
  15. 15

    Systematic design of chemical reactors with multiple stages via multi-objective optimization approach by Mohd Fuad, Mohd Nazri, Hussain, Mohd Azlan

    Published 2015
    “…By using reference-point based multi-objective evolutionary algorithm (R-NSGA-II), Pareto-optimal solutions are successfully generated within the region of user-specified reference points, thus facilitating in the selection of final optimal designs. …”
    Get full text
    Get full text
    Conference or Workshop Item
  16. 16

    Process Planning Optimization In Reconfigurable Manufacturing Systems by Musharavati, Farayi

    Published 2008
    “…Therefore, this study has revealed that extending manufacturing optimization concepts through a decoupled optimization method is an effective modeling approach that is capable of handling complex decision scenarios in reconfigurable manufacturing activities. …”
    Get full text
    Get full text
    Thesis
  17. 17

    Sediment load forecasting from a biomimetic optimization perspective: Firefly and Artificial Bee Colony algorithms empowered neural network modeling in �oruh River by Katipo?lu O.M., Kartal V., Pande C.B.

    Published 2025
    “…The hybrid model is a novel approach for estimating sediment load based on various input variables. …”
    Article
  18. 18

    Genetic algorithm for material cost minimization of external strengthening system with fiber reinforced polymer by Rahman, M.M., Jumaat, Mohd Zamin, Hosen, M.A.

    Published 2012
    “…Genetic algorithm based approach is utilized to solve the optimization task. …”
    Get full text
    Get full text
    Conference or Workshop Item
  19. 19

    Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques by Hammid, Ali Thaeer

    Published 2018
    “…To deal with these problems, this thesis introduces three approved intelligent controllers for hydropower generation. Firstly, a hybrid algorithm namely firefly particle swarm optimization (FPSO) and series division method (SDM) based on the practical swarm optimization and the firefly algorithm is proposed. …”
    Get full text
    Get full text
    Thesis
  20. 20

    Image-based air quality estimation using convolutional neural network optimized by genetic algorithms: A multi-dataset approach by Khan, Arshad Ali, Mazlina, Abdul Majid, Dandoush, Abdulhalim

    Published 2025
    “…For instance, the model achieved a precision of 0.97, a recall of 0.97, and an overall accuracy of 0.9544 percent, outperforming baseline methods significantly in all metrics. These improvements underscore the effectiveness of Genetic Algorithms in optimizing the model.…”
    Get full text
    Get full text
    Get full text
    Article