Search Results - (( new estimation method algorithm ) OR ( using optimization method algorithm ))

Refine Results
  1. 1

    Finite impulse response optimizers for solving optimization problems by Ab Rahman, Tasiransurini

    Published 2019
    “…The classification of estimation-based metaheuristic algorithms has been introduced for solving optimization problems. …”
    Get full text
    Get full text
    Thesis
  2. 2

    Finite impulse response optimizers for solving optimization problems by Tasiransurini, Ab Rahman

    Published 2019
    “…The classification of estimation-based metaheuristic algorithms has been introduced for solving optimization problems. …”
    Get full text
    Get full text
    Thesis
  3. 3

    Development of optimization Alghorithm for uncertain non-linear dynamical system by Abdul Aziz, Mohd. Ismail, Yaacob, Nazeeruddin, Mohd. Said, Norfarizan, Hamzah, Nor Hazadura

    Published 2004
    “…An algorithm that definitely can satisfy the objectives is the Dynamic Integrated Systems Optimization and Parameter Estimation (DISOPE) algorithm. …”
    Get full text
    Get full text
    Monograph
  4. 4

    A New Hybrid Image Encryption Technique Using Lorenz Chaotic System and Simulated Kalman Filter (SKF) Algorithm by Nurnajmin Qasrina Ann, ., Pebrianti, Dwi, Mohammad Fadhil, Abas, Bayuaji, Luhur

    Published 2022
    “…Nowadays, encryption is one of the most popular and effective security methods used by company and organizations. A new hybrid technique, Lorenz chaotic system and an optimization algorithm, Simulated Kalman Filter (SKF) had been proposed to solve image encryption problem. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  5. 5

    Novel chewing cycle approach for peak detection algorithm of chew count estimation by Selamat, Nur Asmiza, Md Ali, Sawal Hamid, Ismail, Ahmad Ghadafi, Ahmad, Siti Anom, Minhad, Khairun Nisa'

    Published 2025
    “…This work proposes a novel approach to chew count estimation using particle swarm optimization (PSO) combined with a peak detection algorithm. …”
    Get full text
    Get full text
    Article
  6. 6

    Novel chewing cycle approach for peak detection algorithm of chew count estimation by Selamat, Nur Asmiza, Md Ali, Sawal Hamid, Ismail, Ahmad Ghadafi, Ahmad, Siti Anom, Minhad, Khairun Nisa’

    Published 2025
    “…This work proposes a novel approach to chew count estimation using particle swarm optimization (PSO) combined with a peak detection algorithm. …”
    Get full text
    Get full text
    Get full text
    Article
  7. 7

    Multilevel optimization for dense motion estimation by Saaban, Azizan, Kalmoun, El Mostafa, Ibrahim, Haslinda, Ramli, Razamin, Omar, Zurni

    Published 2011
    “…We evaluated the performance of different optimization techniques developed in the context of optical flow computation with different variational models.In particular, based on truncated Newton methods (TN) that have been an effective approach for large-scale unconstrained optimization, we developed the use of efficient multilevel schemes for computing the optical flow.More precisely, we evaluated the performance of a standard unidirectional multilevel algorithm - called multiresolution optimization (MR/Opt), to a bidrectional multilevel algorithm - called full multigrid optimization (FMG/Opt).The FMG/Opt algorithm treats the coarse grid correction as an optimization search direction and eventually scales it using a line search. …”
    Get full text
    Get full text
    Get full text
    Monograph
  8. 8
  9. 9

    Modified multi-verse optimizer for nonlinear system identification of a double pendulum overhead crane by Julakha, Jahan Jui, Mohd Ashraf, Ahmad, Muhammad Ikram, Mohd Rashid

    Published 2021
    “…The efficiency of the proposed HMVOSCA algorithm is evaluated using the convergence curve, parameter estimation error, bode plot, function plot, and Wilcoxon's test method. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  10. 10

    Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm by Dalatu, Paul Inuwa

    Published 2018
    “…We introduced two new approaches to normalization techniques to enhance the K-Means algorithms. …”
    Get full text
    Get full text
    Get full text
    Thesis
  11. 11
  12. 12

    A hybrid metaheuristic algorithm for identification of continuous-time Hammerstein systems by Jui, Julakha Jahan, Mohd Ashraf, Ahmad

    Published 2021
    “…The proposed hybrid method also achieved better performance in modeling of the twin-rotor system as well as the flexible manipulator system and provided better solutions compared to other optimization methods including Particle Swarm Optimizer, Grey Wolf Optimizer, Multi-Verse Optimizer and Sine Cosine Algorithm.…”
    Get full text
    Get full text
    Article
  13. 13

    LEMABE: a novel framework to Improve analogy-based software cost estimation using learnable evolution model by Dashti, Maedeh, Gandoman, Taghi Javdani, Adeh, Dariush Hasanpoor, Zulzalil, Hazura, Md Sultan, Abu Bakar

    Published 2021
    “…To improve software development cost estimation, the current study has investigated the effect of the LEM algorithm on optimization of features weighting and proposed a new method as well. …”
    Get full text
    Get full text
    Article
  14. 14

    Performance Analysis of ARMA based Magnetic Resonance Imaging (MRI) Reconstruction Algorithm by Salami, Momoh Jimoh Emiyoka, Najeeb, Athaur Rahman

    Published 2012
    “…Despite this success, two problems lessen the use of this technique, these are: non availability of optimal method of estimating model order and the model coefficients determination. …”
    Get full text
    Get full text
    Monograph
  15. 15

    Multi-objective optimization of stand-alone hybrid renewable energy system by genetic algorithm by Nejad, Mohsen Fadaee

    Published 2013
    “…HOGA, as a new effective tool for multi-objective optimization by evolutionary algorithm is used in this research. …”
    Get full text
    Get full text
    Thesis
  16. 16

    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
    “…This paper proposes a new approach using convolutional neural networks with genetic algorithms for estimating air quality directly from images. …”
    Get full text
    Get full text
    Get full text
    Article
  17. 17

    Optimization of power system stabilizers using participation factor and genetic algorithm by Hassan, L.H., Moghavvemi, M., Almurib, H.A.F., Muttaqi, K.M., Ganapathy, V.G.

    Published 2014
    “…This paper describes a method to determine the optimal location and the number of multi-machine power system stabilizers (PSSs) using participation factor (PF) and genetic algorithm (GA). …”
    Get full text
    Get full text
    Article
  18. 18

    A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

    Published 2023
    “…In addition, the hyperparameter tuning problem is considered in this research to improve the developed hybrid model by using the AOA algorithm. Lastly, a new hybrid technique suggests tackling the current image encryption application problem by using the estimated parameters of chaotic systems with an optimization algorithm, the SKF algorithm. …”
    Get full text
    Get full text
    Thesis
  19. 19

    Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms by Ridha, Hussein Mohammed

    Published 2020
    “…The IEM algorithm uses the attraction-repulsion mechanism to change the positions of solutions towards the optimality. …”
    Get full text
    Get full text
    Thesis
  20. 20

    Harmony Search-Based Fuzzy Clustering Algorithms For Image Segmentation by Alia, Osama Moh’d Radi

    Published 2011
    “…First, two alternative HS-based fuzzy clustering methods are proposed. The aim of these methods is to overcome the limitation faced by conventional fuzzy clustering algorithms, which are known to provide sub-optimal clustering depending on the choice of the initial clusters. …”
    Get full text
    Get full text
    Thesis