Search Results - (( parameter optimization means algorithm ) OR ( property optimization method algorithm ))

Refine Results
  1. 1

    Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems by Zulkifli, Munierah, Abd Rahmin, Nor Aliza, Wah, June Leong

    Published 2023
    “…SGD uses random or batch data sets to compute gradient in solving optimization problems. It is an iterative algorithm with descent properties that reduces computational cost by using derivatives of random data points. …”
    Get full text
    Get full text
    Get full text
    Article
  2. 2

    Enhanced gravitational search algorithm for nano-process parameter optimization problem / Norlina Mohd Sabri by Mohd Sabri, Norlina

    Published 2020
    “…Based on the capabilities of the metaheuristic algorithms, this research is proposing the enhanced Gravitational Search Algorithm (eGSA) to solve the nano-process parameter optimization problem. …”
    Get full text
    Get full text
    Thesis
  3. 3

    Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed by Borujeni, Sattar Chavoshi

    Published 2012
    “…This approach was based on fuzzy expert system (FES) using Fuzzy Toolbox of MATLAB software. Genetic algorithm (GA) was employed to adjust parameters of FES and optimize the system. …”
    Get full text
    Get full text
    Thesis
  4. 4

    Parameter estimation of stochastic differential equation by Haliza Abd. Rahman, Arifah Bahar, Norhayati Rosli, Madihah Md. Salleh

    Published 2012
    “…To overcome the subjective and tedious process of selecting the optimal knot and order of spline, an algorithm was proposed. …”
    Get full text
    Get full text
    Get full text
    Article
  5. 5

    3D prediction of tunneling-induced ground movements based on a hybrid ANN and empirical methods by Hajihassani, M., Kalatehjari, R., Marto, A., Mohamad, H., Khosrotash, M.

    Published 2019
    “…To overcome these problems, the use of optimization algorithms to train ANNs is of advantage. …”
    Get full text
    Get full text
    Article
  6. 6

    3D prediction of tunneling-induced ground movements based on a hybrid ANN and empirical methods by Hajihassani, M., Kalatehjari, R., Marto, A., Mohamad, H., Khosrotash, M.

    Published 2020
    “…To overcome these problems, the use of optimization algorithms to train ANNs is of advantage. …”
    Get full text
    Get full text
    Article
  7. 7

    An optimized ensemble for predicting reservoir rock properties in petroleum industry by Kenari, Seyed Ali Jafari

    Published 2013
    “…In the present thesis, we proposed a new method named optimized ensembleto improve the prediction of these reservoirs parameters from well log data with the aid of available core data. …”
    Get full text
    Get full text
    Thesis
  8. 8

    Neural network-based prediction models for physical properties of oil palm medium density fiberboard / Faridah Sh. Ismail by Sh. Ismail, Faridah

    Published 2015
    “…This situation can be solved by embedding Genetic Algorithm (GA) in the network to replace back-propagation method. …”
    Get full text
    Get full text
    Thesis
  9. 9
  10. 10

    Effect of vibration analysis towards dynamic properties in dissimilar joining materials: A review by Rosmaliza, Mat Yaacob, Muhammad Zikri, Japri, N. A. Z., Abdullah, M. S. M., Sani

    Published 2025
    “…Despite computational challenges, these methods provide valuable tools for optimizing design and operational parameters in vibration analysis, advancing structural reliability and precision.…”
    Get full text
    Get full text
    Get full text
    Article
  11. 11

    Intelligent grading of agarwood essential oil quality using artificial neural network (ANN) / Noratikah Zawani Mahabob by Mahabob, Noratikah Zawani

    Published 2022
    “…The training and validation of the ANN was based on optimization of its training parameters and guided by the convergence of the mean squared errors (MSE). …”
    Get full text
    Get full text
    Thesis
  12. 12

    Development of compound clustering techniques using hybrid soft-computing algorithms by Salim, Naomie, Shamsuddin, Siti Mariyam, Salleh @ Sallehuddin, Roselina, Alwee, Razana

    Published 2006
    “…Initially, the heuristics needs user intervention to select optimal values, which give poor results. To overcome this problem, fuzzy memberships have been employed to find optimal parameters. …”
    Get full text
    Get full text
    Monograph
  13. 13

    High performance enzyme-catalyzed synthesis and characterization of a nonionic surfactant by Adnani, Atena, Chaibakhsh, Naz, Ahangar, Hossein Abbastabar, Basri, Mahiran, Raja Abdul Rahman, Raja Noor Zaliha, Salleh, Abu Bakar

    Published 2013
    “…Taguchi orthogonal array method based on three-level-six-variables (L27) and artificial neural network with Levenberg–Marquardt algorithm were applied to evaluate the effects of synthesis parameters and to optimize the reaction conditions. …”
    Get full text
    Get full text
    Get full text
    Article
  14. 14

    Impact of evolutionary algorithm on optimization of nonconventional machining process parameters by B V, Raghavendra, R Annigiri, Anandkumar, Srikatamurthy, JS

    Published 2025
    “…This paper presents the optimization of laser beam machining in additive manufacturing of polymer-based material parameters, specifically focusing on cutting speed, gas pressure of nitrogen, and focal point locations, to achieve optimal mean surface roughness. …”
    Get full text
    Get full text
    Get full text
    Article
  15. 15

    A Hybrid Least Squares Support Vector Machine with Bat and Cuckoo Search Algorithms for Time Series Forecasting by Mohammed, Athraa Jasim, Ghathwan, Khalil Ibrahim, Yusof, Yuhanis

    Published 2020
    “…However, its operation relies on two important parameters (regularization and kernel). Pre-determining the values of parameters will affect the results of the forecasting model; hence, to find the optimal value of these parameters, this study investigates the adaptation of Bat and Cuckoo Search algorithms to optimize LSSVM parameters. …”
    Get full text
    Get full text
    Article
  16. 16

    Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems by Kek, Sie Long

    Published 2011
    “…The main idea is the integration of optimal control and parameter estimation. In this work, a simplified model-based optimal control model with adjustable parameters is constructed. …”
    Get full text
    Get full text
    Thesis
  17. 17

    Efficient Time-Varying q-Parameter Design for q-Incremental Least Mean Square Algorithm with Noisy Links by Arif, M., Khan, S.S., Qadri, S.S.U., Naseem, I., Moinuddin, M.

    Published 2022
    “…Moreover, for the proposed NL-qILMS, we also devised various time-varying techniques for the selection of the optimal q-parameter to improve the performance. Furthermore, the closed-form solutions for the steady-state mean square deviation, excess mean square deviation and mean square error are derived. …”
    Get full text
    Get full text
    Article
  18. 18
  19. 19

    Stock price predictive analysis: An application of hybrid barnacles mating optimizer with artificial neural network by Zuriani, Mustaffa, Mohd Herwan, Sulaiman

    Published 2023
    “…In this study, the Barnacles Mating Optimizer (BMO) is employed as an optimization tool to automatically optimize these parameters. …”
    Get full text
    Get full text
    Get full text
    Article
  20. 20

    Bouc-Wen hysteresis parameter optimization for magnetorheological damper using Cuckoo search algorithm by Rosmazi, Rosli, Zamri, Mohamed, G., Priyandoko, M. F. F., Ab Rashid

    Published 2020
    “…Cuckoo search algorithm is used to optimize the parameters in phenomenological Bouc-Wen model. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item