Search Results - (( parameter estimation bees algorithm ) OR ( parallel evaluation using algorithm ))

Refine Results
  1. 1

    Artificial Bee Colony algorithm in estimating kinetic parameters for yeast fermentation pathway by Ahmad Muhaimin, Ismail, Muhammad Akmal, Remli, Yee Wen, Choon, Nurul Athirah, Nasarudin, Norsyahidatul Nazirah, Ismail, Mohd Arfian, Ismail, Mohd Saberi, Mohamad

    Published 2023
    “…Therefore, we propose the Artificial Bee Colony algorithm (ABC) to estimate the parameters in the fermentation pathway of S. cerevisiae to obtain more accurate values. …”
    Get full text
    Get full text
    Get full text
    Article
  2. 2

    Parameter estimation of essential amino acids in Arabidopsis thaliana using hybrid of bees algorithm and harmony search by Aw, Mei Yee, Mohd Saberi, Mohamad, Chong, Chuii Khim, Safaai, Deris, Muhammad Akmal, Remli, Mohd Arfian, Ismail, Corchado, Juan Manuel, Omatu, Sigeru

    Published 2019
    “…This paper proposes the Hybrid of Bees Algorithm and Harmony Search (BAHS) to estimate the kinetics parameters of essential amino acid production in the aspartate metabolism for Arabidopsis thaliana. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Get full text
    Book Chapter
  3. 3

    Estimation of optimal machining control parameters using artificial bee colony by Norfadzlan, Yusup, Arezoo, Sarkheyli, Azlan, Mohd Zain, Siti Zaiton, Mohd Hashim, Norafida, Ithnin

    Published 2013
    “…This research employed ABC algorithm to optimize the machining control parameters that lead to a minimum surface roughness (R a) value for AWJ machining. …”
    Get full text
    Get full text
    Get full text
    Article
  4. 4
  5. 5

    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
    “…This study combined models such as the artificial neural network (ANN) algorithm with the Firefly algorithm (FA) and Artificial Bee Colony (ABC) optimization techniques for the estimation of monthly SL values in the �oruh River in Northeastern Turkey. …”
    Article
  6. 6

    Optimising a waste management system using the Artificial Bee Colony (ABC) algorithm by Mohamad Fadzil, Nur Hamisha Helanie

    Published 2025
    “…Future work may focus on integrating real-time data, adjusting algorithm parameters and hybridizing ABC algorithm with other metaheuristics to further improve performance.…”
    Get full text
    Get full text
    Student Project
  7. 7

    Enhancing performance of XTS cryptography mode of operation using parallel design by Ahmed Alomari, Mohammad

    Published 2009
    “…In addition, the parallel XTS mode was also simulated using Twofish and RC6 encryption algorithms. …”
    Get full text
    Get full text
    Thesis
  8. 8

    Hydroclimatic data prediction using a new ensemble group method of data handling coupled with artificial bee colony algorithm by Basri Badyalina, Nurkhairany Amyra Mokhtar, Nur Amalina Mat Jan, Muhammad Fadhil Marsani, Mohamad Faizal Ramli, Muhammad Majid, Fatin Farazh Ya'acob

    Published 2022
    “…It is rare to find a hydrological application using the group method of data handling (GMDH) model, artificial bee colony (ABC) algorithm, and ensemble technique, precisely predicting ungauged sites. …”
    Get full text
    Get full text
    Get full text
    Article
  9. 9

    Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems by Shakeel Ahmed, Kamboh

    Published 2014
    “…To implement the parallel algorithms a distributed parallel computing laboratory using easily available low cost computers is setup. …”
    Get full text
    Get full text
    Thesis
  10. 10

    Artificial Bee Colony-based satellite image contrast and brightness enhancement technique using DWT-SVD by Bhandari, A.K., Soni, V., Kumar, A., Singh, G.K.

    Published 2014
    “…The proposed technique is based on the Artificial Bee Colony (ABC) algorithm using Discrete Wavelet Transform and Singular Value Decomposition (DWT-SVD). …”
    Get full text
    Get full text
    Article
  11. 11
  12. 12

    Parallelization of speech compression based algorithm based on human auditory system on multicore system by Gunawan, Teddy Surya, Kartiwi, Mira, Khalifa, Othman Omran

    Published 2012
    “…Finally, the performance of the developed parallel algorithm was evaluated using Perceptual Evaluation of Speech Quality (PESQ) and parallel execution time. …”
    Get full text
    Get full text
    Get full text
    Article
  13. 13

    Parallel genetic algorithms for shortest path routing in high- performance computing / Mohd Erman Safawie Che Ibrahim by Che Ibrahim, Mohd Erman Safawie

    Published 2012
    “…This project focuses on step-up cluster computing and a parallel Genetic Algorithm. The objectives of this project to set-up Beowulf cluster computer to apply the Travelling Salesman Problem in parallel by using Genetic Algorithms and evaluate sequential algorithms and parallel algorithms by Genetic Algorithms. …”
    Get full text
    Get full text
    Thesis
  14. 14

    Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS by Hassan, S., Khanesar, M.A., Jaafar, J., Khosravi, A.

    Published 2017
    “…In this paper, heuristic optimization approaches such as genetic algorithm and artificial bee colony are used to optimize the parameters of the antecedent part of interval type-2 fuzzy logic systems. …”
    Get full text
    Get full text
    Article
  15. 15

    Analysis of evolutionary computing performance via mapreduce parallel processing architecture / Ahmad Firdaus Ahmad Fadzil by Ahmad, Ahmad Firdaus

    Published 2014
    “…MR is an emerging parallel processing framework that hides the complex parallelization processes by employing the functional abstraction of "map and reduce" The Performance of the parallelized GA via MR and PSO via MR are evaluated using an analogous case study to find out the speedup and efficiency in order to measure the scalability of both proposed algorithms. …”
    Get full text
    Get full text
    Thesis
  16. 16

    SLOW DRIFT MOTIONS IDENTIFICATION OF FLOATING STRUCTURES USING TIME-VARYING INPUT -OUTPUT MODELS by YAZID, EDWAR

    Published 2015
    “…The first step is presenting the backward estimator and combined forward-backward estimator instead of the only forward estimator in the original input-output models; the second step is reformulating the input-output models into a state-space model so that the Kalman Smoother (KS) adaptive filter can be used to estimate the model coefficients; the third step is optimization of KS parameters using evolutionary computing algorithms such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Artificial Bee Colony (ABC) to form the PSO-KS, GA-KS and ABC-KS as estimation methods.…”
    Get full text
    Get full text
    Thesis
  17. 17

    An Experimental Study on Relationship between Performance and Energy Consumption of Serial and Parallel Text Searching Algorithm. by Isahak, Siti Zulaikha

    Published 2013
    “…In this paper, text searching algorithm is using to study the relationship between performance of computer and amount of energy produced in serial and parallel text searching algorithm. …”
    Get full text
    Get full text
    Final Year Project
  18. 18

    Communication and computational cost on parallel algorithm of PDE elliptic type by Alias, Norma

    Published 2009
    “…Due to this needs, this paper presents the parallel performance evaluations of algorithms that will be discussed in term of communication and computational cost.…”
    Get full text
    Get full text
    Book Section
  19. 19

    Improving the modeling capacity of Volterra model using evolutionary computing methods based on Kalman Smoother adaptive filter by ., Edwar Yazid, Mohd Shahir Liew, Setyamartana Parman, Velluruzhati

    Published 2015
    “…The first step is combining the forward and backward estimator in the original Volterra model; the second step is reformulating the Volterra model into a state-space model so that the Kalman Smoother (KS) adaptive filter can be used to estimate the kernel coefficients; the third step is optimization of KS parameters using evolutionary computing algorithms such as particle swarm optimization (PSO), genetic algorithm (GA) and artificial bee colony (ABC). …”
    Get full text
    Get full text
    Article
  20. 20