Search Results - (( exploring e function algorithm ) OR ( java data optimization algorithm ))

Refine Results
  1. 1

    Fuzzy modeling using Bat Algorithm optimization for classification by Noor Amidah, Ahmad Sultan

    Published 2018
    “…A Sazonov Engine which is a fuzzy java engine is use to apply Bat Algorithm in the experiment. …”
    Get full text
    Get full text
    Get full text
    Undergraduates Project Papers
  2. 2

    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

    Published 2022
    “…Therefore, in this paper, we proposed Dynamic tasks scheduling algorithm based on attribute reduction with an enhanced hybrid Genetic Algorithm and Particle Swarm Optimization for optimal device selection. …”
    Get full text
    Get full text
    Article
  3. 3

    A random search based effective algorithm for pairwise test data generation by Sabira, Khatun, K. F., Rabbi, Che Yahaya, Yaakub, Klaib, Mohammad F. J.

    Published 2011
    “…This paper proposes an effective random search based pairwise test data generation algorithm named R2Way to optimize the number of test cases. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  4. 4
  5. 5

    EasyA: Easy and effective way to generate pairwise test data by Rabbi, Khandakar Fazley, Sabira, Khatun, Che Yahaya, Yaakub, Klaib, Mohammad F. J.

    Published 2013
    “…This paper proposes a matrix based calculation for pairwise test data generation algorithm named EasyA to optimize the number of test cases. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  6. 6

    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
    Get full text
    Get full text
    Thesis
  7. 7

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
    Get full text
    Get full text
    Thesis
  8. 8

    Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions by Abbas, Iraq Tareq

    Published 2018
    “…The BOGS-BAT algorithm is based on three techniques. The first technique is to move or switch solution from single function to functions that contain more than one objective functions. …”
    Get full text
    Get full text
    Thesis
  9. 9
  10. 10
  11. 11

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

    Published 2020
    “…Enhancements could also be done to eGSA by exploring the possibility to hybrid the algorithm with other well-known meta heuristic algorithms.…”
    Get full text
    Get full text
    Thesis
  12. 12

    Development Of Artificial Bee Colony (Abc) Variants And Memetic Optimization Algorithms by Sulaiman, Noorazliza

    Published 2017
    “…The performances of all modified ABC variants and formulated memetic ABC algorithms have been evaluated on 27 benchmark functions. …”
    Get full text
    Get full text
    Thesis
  13. 13

    A new multiobjective tiki-taka algorithm for optimization of assembly line balancing by M. F. F., Ab Rashid, Ariff Nijay, Ramli

    Published 2023
    “…Purpose: This study aims to propose a new multiobjective optimization metaheuristic based on the tiki-taka algorithm (TTA). The proposed multiobjective TTA (MOTTA) was implemented for a simple assembly line balancing type E (SALB-E), which aimed to minimize the cycle time and workstation number simultaneously. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  14. 14

    Crossover and mutation operators of real coded genetic algorithms for global optimization problems by Lim, Siew Mooi

    Published 2016
    “…The numerical results obtained from the performance evaluation indicated that the RX crossover is the most fitting pair to the STPM mutator in competently solving two CS problems i.e. minimizing a molecular potential energy function and finding the most stable conformation of pseudoethane through a molecular model, which involves a realistic energy function.…”
    Get full text
    Get full text
    Thesis
  15. 15
  16. 16

    Dynamic Probability Selection for Flower Pollination Algorithm based on Metropolis-hastings Criteria by Zamli, Kamal Zuhairi, Din, Fakhrud, Nasser, Abdullah, Ramli, Nazirah, Mohamed, Noraini

    Published 2021
    “…Having only one parameter control (i.e. the switch probability, pa) to choose from the global search (i.e. exploration) and local search (i.e. exploitation) is the main strength of FPA as compared to other meta-heuristic algorithms. …”
    Get full text
    Get full text
    Article
  17. 17
  18. 18

    PMT : opposition based learning technique for enhancing metaheuristic algorithms performance by Hammoudeh, S. Alamri

    Published 2020
    “…Nevertheless, many metaheuristic algorithms are still suffering from a low convergence rate because of the poor balance between exploration (i.e. roaming new potential search areas) and exploitation (i.e., exploiting the existing neighbors). …”
    Get full text
    Get full text
    Thesis
  19. 19

    Dynamic probability selection for flower pollination algorithm based on metropolis-hastings criteria by Zamli, Kamal Zuhairi, Din, Fakhrud, Nasser, Abdullah, Ramli, Nazirah, Mohamed, Noraini

    Published 2021
    “…Having only one parameter control (i.e. the switch probability, pa) to choose from the global search (i.e. exploration) and local search (i.e. exploitation) is the main strength of FPA as compared to other meta-heuristic algorithms. …”
    Get full text
    Get full text
    Get full text
    Article
  20. 20