Search Results - (( evolution constructing optimisation algorithm ) OR ( java implementation bayes algorithm ))

  • Showing 1 - 5 results of 5
Refine Results
  1. 1

    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

    Published 2019
    “…In this system, the layout was designed under two categories which are the standard bay size and the small bay size to increase the parking bays. …”
    Get full text
    Get full text
    Thesis
  2. 2

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…The support vector machines (SVM) algorithm obtained the overall best results of 94.5% accuracy, 91.8% precision, 91.7% recall, and 91.1% f-Measure while the naïve bayes (NB) algorithm obtained the best AUC score of 0.944 with the tweet data of Dato Seri Anwar. …”
    Get full text
    Get full text
    Get full text
    Thesis
  3. 3

    B-spline curve fitting with different parameterization methods by Kheng, Jia Shen

    Published 2020
    “…After generating control points, distance between the generated and original data points is used to identify the error of the algorithm. Later, genetic algorithm and differential evolution optimization are used to optimise the error of the curve. …”
    Get full text
    Get full text
    Final Year Project / Dissertation / Thesis
  4. 4

    Reliability assessment of power system generation adequacy with wind power using population-based intelligent search methods by Kadhem, Athraa Ali

    Published 2017
    “…This study sought to examine the performance of three newly proposed techniques, for reliability assessment of the power systems, namely Disparity Evolution Genetic Algorithm (DEGA), Binary Particle Swarm Optimisation (BPSO), and Differential Evolution Optimization Algorithm (DEOA). …”
    Get full text
    Get full text
    Get full text
    Thesis
  5. 5