Search Results - (( parameter optimization based algorithm ) OR ( case detection using algorithm ))*

Refine Results
  1. 1

    On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing by Kamal Z., Zamli, Alsariera, Yazan A., Nasser, Abdullah B., Alsewari, Abdulrahman A.

    Published 2015
    “…Although useful, strategies based on the aforementioned optimization algorithms are not without limitation. …”
    Get full text
    Get full text
    Get full text
    Article
  2. 2

    Optimizing in-car-abandoned children’s sounds detection using deep learning algorithms / Nur Atiqah Izzati Md Fisol by Md Fisol, Nur Atiqah Izzati

    Published 2023
    “…To address this problem, an optimized in-car-abandoned children's sounds detection model using deep learning algorithms is proposed. …”
    Get full text
    Get full text
    Student Project
  3. 3

    Evaluating Bees Algorithm for Sequence-based T-way Testing Test Data Generation by M. H., Mohamed Zabil, Kamal Z., Zamli, K. C., Lim

    Published 2018
    “…T-way testing is a testing technique that is used to detect faults due to parameter interactions or software configurations. …”
    Get full text
    Get full text
    Get full text
    Article
  4. 4

    Sequence and sequence-less t-way test suite generation strategy based on the elitist flower pollination algorithm by Mohammed Abdullah, Abdullah Nasser

    Published 2018
    “…Interaction, or t-way, testing, where t indicates the interaction strength, is an approach to generate test suite for detecting fault due to interaction. In line with the emerging field called Search based Software Engineering, many recently developed t-way strategies have adopted meta-heuristic algorithms as the basis of their implementations such as Simulated Annealing, Genetic Algorithm, Ant Colony Optimization Algorithm, Particle Swarm Optimization, Harmony Search and Cuckoo Search, owing their superior performance in term of test size reduction as compared to general computational based strategies, such as General t-way, Test Vector Generator, In Parameter Order General, Jenny, and Automatic Efficient Test Generator. …”
    Get full text
    Get full text
    Thesis
  5. 5

    Pairwise Test Suite Generation Based on Hybrid Artificial Bee Colony Algorithm by Alazzawi, A.K., Rais, H.M., Basri, S., Alsariera, Y.A.

    Published 2020
    “…Pairwise testing is one of the efficient CTT that used widely for fault detection based on the caused failures by two interactions parameters. …”
    Get full text
    Get full text
    Article
  6. 6

    Optimized techniques for landslide detection and characteristics using LiDAR data by Mezaal, Mustafa Ridha

    Published 2018
    “…The segmentation process was optimized using Fuzzy-based Segmentation Parameter. …”
    Get full text
    Get full text
    Get full text
    Thesis
  7. 7
  8. 8
  9. 9
  10. 10
  11. 11

    Detection of corneal arcus using rubber sheet and machine learning methods by Ramlee, Ridza Azri

    Published 2019
    “…The benchmark of the classification algorithm for CA is needed to analyze the optimal output of the algorithm. …”
    Get full text
    Get full text
    Thesis
  12. 12

    Hybrid Intelligent Warning System for Boiler tube Leak Trips by Singh, D., Ismail, F.B., Shakir Nasif, M.

    Published 2017
    “…The Extreme Learning Machine (ELM) methodology was also adopted in IWS-1 and compared with traditional training algorithms. Genetic algorithm (GA) was adopted in IWS-2 to optimize the ANN topology and the boiler parameters. …”
    Get full text
    Get full text
    Article
  13. 13

    A fuzzy multi-objective optimisation model of risk-based gas detector placement methodology for explosion protection in oil and gas facilities by Idris, A.M., Rusli, R., Nasif, M.S., Ramli, A.F., Lim, J.S.

    Published 2022
    “…Risk analysis is conducted to identify high risk areas that need flammable gas detectors protection, which is the input for the mathematical model. The proposed risk-based model was tested using a case study involving a natural gas liquids (NGL) recovery unit, and the results were compared to a published greedy algorithm (GA) formulation. …”
    Get full text
    Get full text
    Article
  14. 14

    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
  15. 15

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

    Published 2019
    “…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
    Get full text
    Get full text
    Thesis
  16. 16

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

    Published 2019
    “…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
    Get full text
    Get full text
    Thesis
  17. 17
  18. 18

    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
  19. 19

    Optimization of turning parameters using genetic algorithm method by Shah Izwandi, Mohd Zawawi

    Published 2008
    “…This study about development of optimization for turning parameters based on the Genetic Algorithm (GA). …”
    Get full text
    Get full text
    Undergraduates Project Papers
  20. 20

    Optimization of milling parameters using ant colony optimization by Mohd Saupi, Mohd Sauki

    Published 2008
    “…The simulation based on ACO algorithm are successful develop and the optimization of parameters values is to maximize the production rate is obtain from the simulation.…”
    Get full text
    Get full text
    Undergraduates Project Papers