Search Results - (( developing improving classification algorithm ) OR ( java simulation optimization algorithm ))

Refine Results
  1. 1

    An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani by Ab Ghani, Nur Laila

    Published 2015
    “…The improved algorithm is constructed by adding new parameter and classification rule to existing algorithm. …”
    Get full text
    Get full text
    Thesis
  2. 2
  3. 3

    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

    Published 2011
    “…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
    Get full text
    Get full text
    Get full text
    Thesis
  4. 4

    An adaptive ant colony optimization algorithm for rule-based classification by Al-Behadili, Hayder Naser Khraibet

    Published 2020
    “…Various classification algorithms have been developed to produce classification models with high accuracy. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  5. 5

    Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2012
    “…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
    Get full text
    Get full text
    Get full text
    Monograph
  6. 6

    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

    Published 2005
    “…Methods for improving supervised and unsupervised classification of remotely sensed data were developed in this study. …”
    Get full text
    Get full text
    Thesis
  7. 7

    Domestic garbage target detection based on improved YOLOv5 algorithm by Ma, Haohao, Wu, Xuping, As'arry, Azizan, Han, Weiliang, Mu, Tong, Feng, Yanwei

    Published 2023
    “…In order to reduce the intensity of manual garbage classification and improve the efficiency and accuracy of garbage classification, a new type of household garbage classification based on improved YOLOv5 algorithm visual recognition is designed. …”
    Get full text
    Get full text
    Conference or Workshop Item
  8. 8

    Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach by Moheb Pour, Majid Reza

    Published 2009
    “…The method was developed based on the grid structure, whereby it was done to create a successful method of improving performance in classification. …”
    Get full text
    Get full text
    Thesis
  9. 9

    OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT by Murad S.S., Badeel R., Alsandi N.S.A., Alshaaya R.F., Ahmed R.A., Muhammed A., Derahman M.

    Published 2023
    “…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”
    Review
  10. 10

    A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network by Salari, Nader, Shohaimi, Shamarina, Najafi, Farid, Nallappan, Meenakshii, Karishnarajah, Isthrinayagy

    Published 2014
    “…Among numerous artificial intelligence approaches, k-Nearest Neighbor algorithms, genetic algorithms, and artificial neural networks are considered as the most common and effective methods in classification problems in numerous studies. …”
    Get full text
    Get full text
    Get full text
    Article
  11. 11

    Kernel and multi-class classifiers for multi-floor wlan localisation by Abd Rahman, Mohd Amiruddin

    Published 2016
    “…Unlike the classical kNN algorithm which is a regression type algorithm, the proposed localisation algorithms utilise machine learning classification for both linear and kernel types. …”
    Get full text
    Get full text
    Thesis
  12. 12

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

    Published 2019
    “…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
    Get full text
    Get full text
    Thesis
  13. 13

    Enhancement of bearing defect diagnosis via genetic algorithm optimized feature selection by Chia, Yee Shin

    Published 2015
    “…Thus, it can be concluded that the developed algorithm is capable to improve the classification efficiency by improving the generality of the classifier in classifying test data with unpredictable variations under various working conditions.…”
    Get full text
    Get full text
    Get full text
    Thesis
  14. 14

    Dengue classification system using clonal selection algorithm / Karimah Mohd by Mohd, Karimah

    Published 2012
    “…This project focused on three main objectives: to investigate dengue data and Clonal Selection Algorithm for classification of Dengue, to design and develops Clonal Selection Classification System (CSCS) and to evaluate Clonal Selection Classification System symptoms. …”
    Get full text
    Get full text
    Thesis
  15. 15

    Ant colony optimization algorithm for rule based classification: Issues and potential by Al-Behadili, Hayder Naser Khraibet, Ku-Mahamud, Ku Ruhana, Sagban, Rafid

    Published 2018
    “…Potential solutions that may be considered to improve the performance of ACO algorithms in the classification domain were also presented. …”
    Get full text
    Get full text
    Get full text
    Article
  16. 16

    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
  17. 17

    Grid base classifier in comparison to nonparametric methods in multiclass classification by Moheb Pour, Majid Reza, Jantan, Adznan, Saripan, M. Iqbal

    Published 2010
    “…This method carries the advantages of the two previous methods in order to improve the classification tasks. The problem with the current lazy algorithms is that they learn quickly, but classify very slowly. …”
    Get full text
    Get full text
    Get full text
    Article
  18. 18

    Improved building roof type classification using correlation-based feature selection and gain ratio algorithms by Norman, M., Mohd Shafri, Helmi Zulhaidi, Pradhan, Biswajeet, Yusuf, B.

    Published 2017
    “…Accurate feature selection is a necessary step to improve the accuracy of classification. This process depends on the number of feature attributes available for interactive synthesis of common characteristics that discriminate different features. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  19. 19

    Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System by Aljanabi, Mohammad, Mohd Arfian, Ismail, Mezhuyev, Vitaliy

    Published 2020
    “…The proposed method combined the improved teaching-learning-based optimisation (ITLBO) algorithm, improved parallel JAYA (IPJAYA) algorithm, and support vector machine. …”
    Get full text
    Get full text
    Get full text
    Article
  20. 20

    Logistic regression methods for classification of imbalanced data sets by Santi Puteri Rahayu, -

    Published 2012
    “…This thesis aims to develop the simple and effective imbalanced classification algorithms by previously improving the algorithms performance of general classifiers i.e. …”
    Get full text
    Get full text
    Thesis