Search Results - (( binary classification using algorithm ) OR ( evolution optimization clustering algorithm ))

Search alternatives:

Refine Results
  1. 1
    A novel clustering based genetic algorithm for route optimization

    A novel clustering based genetic algorithm for route optimization by Aibinu, Abiodun Musa, Salau, Habeeb Bello, Najeeb, Athaur Rahman, Nwohu, Mark Ndubuka, Akachukwu, Chichebe

    Published 2016
    “…It was also observed that the introduction of clustering based selection algorithm guaranteed the selection of cluster with the optimal solution in every generation. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  2. 2
    Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier

    Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier by Siow, Shien Loong

    Published 2018
    “…There are a lot of feature extraction methods and classification methods for iris classification. Classic local binary pattern (LBP) is one of the most useful feature extraction methods. …”
    Get full text
    Get full text
    Monograph
    Save to List
    Saved in:
  3. 3
    Cluster head selection optimization in wireless sensor network via genetic-based evolutionary algorithm

    Cluster head selection optimization in wireless sensor network via genetic-based evolutionary algorithm by Vincent Chung, Hamzarul Alif Hamzah, Norah Tuah, Kit, Guan Lim, Min, Keng Tan, Kenneth Tze Kin Teo

    Published 2020
    “…Genetic-based evolutionary algorithms such as Genetic Algorithm (GA) and Differential Evolution (DE) have been popularly used to optimize cluster head selection in WSN to improve energy efficiency for the extension of network lifetime. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  4. 4
    Feature Selection using Binary Simulated Kalman Filter for Peak Classification of EEG Signals

    Feature Selection using Binary Simulated Kalman Filter for Peak Classification of EEG Signals by Badaruddin, Muhammad, Mohd Falfazli, Mat Jusof, Mohd Ibrahim, Shapiai, Asrul, Adam, Zulkifli, Md. Yusof, Kamil Zakwan, Mohd Azmi, Nor Hidayati, Abdul Aziz, Zuwairie, Ibrahim, Norrima, Mokhtar

    Published 2018
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  5. 5
    Broadening selection competitive constraint handling algorithm for faster convergence

    Broadening selection competitive constraint handling algorithm for faster convergence by Shaikh, T.A., Hussain, S.S., Tanweer, M.R., Hashmani, M.A.

    Published 2020
    “…In this study, the BSCCH algorithm has been coupled with Differential Evolution algorithm as a proof of concept because it is found to be an efficient algorithm in the literature for constrained optimization problems. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  6. 6
    A New Quadratic Binary Harris Hawk Optimization For Feature Selection

    A New Quadratic Binary Harris Hawk Optimization For Feature Selection by Abdullah, Abdul Rahim, Too, Jing Wei, Mohd Saad, Norhashimah

    Published 2019
    “…A comparative study is conducted to compare the effectiveness of QBHHO with other feature selection algorithms such as binary differential evolution (BDE), genetic algorithm (GA), binary multi-verse optimizer (BMVO), binary flower pollination algorithm (BFPA), and binary salp swarm algorithm (BSSA). …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  7. 7
    EMG Feature Selection And Classification Using A Pbest-Guide Binary Particle Swarm Optimization

    EMG Feature Selection And Classification Using A Pbest-Guide Binary Particle Swarm Optimization by Too, Jing Wei, Tee, Wei Hown, Abdullah, Abdul Rahim, Mohd Saad, Norhashimah

    Published 2019
    “…In order to measure the effectiveness of PBPSO, binary particle swarm optimization (BPSO), genetic algorithm (GA), modified binary tree growth algorithm (MBTGA), and binary differential evolution (BDE) were used for performance comparison. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  8. 8
    An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani

    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 urban growth images obtained are analysed to improve existing classification algorithms. The improved algorithm is constructed by adding new parameter and classification rule to existing algorithm. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  9. 9
    Performances of machine learning algorithms for binary classification of network anomaly detection system

    Performances of machine learning algorithms for binary classification of network anomaly detection system by Nawir, M., Amir, A., Lynn, O.B., Yaakob, N., Ahmad, R.B.

    Published 2018
    “…The finding showed that AODE algorithm is performed well in term of accuracy and processing time for binary classification towards UNSW-NB15 dataset.…”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  10. 10
    Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals

    Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals by Too, Jing Wei

    Published 2020
    “…In this regard, this thesis proposes five FS methods for efficient EMG signals classification. The first method is the Binary Tree Growth Algorithm (BTGA), which implements a hyperbolic tangent function to convert the Tree Growth Algorithm into the binary version. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  11. 11
    Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms

    Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms by Alswaitti, Mohammed Y. T.

    Published 2018
    “…Nature-inspired optimization-based clustering techniques are powerful, robust and more sophisticated than the conventional clustering methods due to their stochastic and heuristic characteristics. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  12. 12
    Improving amphetamine-type stimulants drug classification using chaotic-based time-varying binary whale optimization algorithm

    Improving amphetamine-type stimulants drug classification using chaotic-based time-varying binary whale optimization algorithm by Draman @ Muda, Azah Kamilah, Mohd Yusof, Norfadzlia, Pratama, Satrya Fajri, Carbo-Dorca, Ramon, Abraham, Ajith

    Published 2022
    “…A new chaotic time-varying binary whale optimization algorithm (CBWOATV) is introduced in this paper to optimize the feature selection process in Amphetamine-type Stimulants (ATS) and non-ATS drugs classification. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  13. 13
    Seed disperser ant algorithm for optimization / Chang Wen Liang

    Seed disperser ant algorithm for optimization / Chang Wen Liang by Chang , Wen Liang

    Published 2018
    “…The optimal results obtained for constrained engineering problems as well as data clustering are very promising in terms of quality of solutions and convergence speed of the algorithm.…”
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  14. 14
    An improved algorithm for iris classification by using support vector machine and binary random machine learning

    An improved algorithm for iris classification by using support vector machine and binary random machine learning by Kamarulzalis, Ahmad Haadzal

    Published 2018
    “…The first objective of this study is to improve a new algorithm technique for classification. The new algorithm come from a combination of an ideas of k-NN algorithm and ensemble concept. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  15. 15
    A novel nonlinear time‑varying sigmoid transfer function in binary whale optimization algorithm for descriptors selection in drug classifcation

    A novel nonlinear time‑varying sigmoid transfer function in binary whale optimization algorithm for descriptors selection in drug classifcation by Mohd Yusof, Norfadzlia, Muda, Azah Kamilah, Pratama, Satrya Fajri, Abraham, Ajith

    Published 2022
    “…The comparative optimization algorithms include two BWOA variants, binary bat algorithm (BBA), binary gray wolf algorithm (BGWOA), and binary manta-ray foraging algorithm (BMRFO). …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  16. 16
    Classification System for Wood Recognition using K-Nearest Neighbor with Optimized Features from Binary Gravitational Algorithm

    Classification System for Wood Recognition using K-Nearest Neighbor with Optimized Features from Binary Gravitational Algorithm by Taman, Ishak, Md Rosid, Nur Atika, Karis, Mohd Safirin, Hasim, Saipol Hadi, Zainal Abidin, Amar Faiz, Nordin, Nur Anis, Omar, Norhaizat, Jaafar, Hazriq Izzuan, Ab Ghani, Zailani, Hassan, Jefery

    Published 2014
    “…The project proposes a classification system using Gray Level Co-Occurrence Matrix (GLCM) as feature extractor, K-Nearest Neighbor (K-NN) as classifier and Binary Gravitational Search Algorithm (BGSA) as the optimizer for GLCM’s feature selection and parameters. …”
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  17. 17
    An ensemble learning method for spam email detection system based on metaheuristic algorithms

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

    Published 2015
    “…In order to address the challenges that mentioned above in this study, in the first phase, a novel architecture based on ensemble feature selection techniques include Modified Binary Bat Algorithm (NBBA), Binary Quantum Particle Swarm Optimization (QBPSO) Algorithm and Binary Quantum Gravita tional Search Algorithm (QBGSA) is hybridized with the Multi-layer Perceptron (MLP) classifier in order to select relevant feature subsets and improve classification accuracy. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  18. 18
    A Preliminary Study of Wood Species Classifacation System Based on Wood Knot Texture Using K-Nearest Neighbour With Optimized Features From Binary Magnetic Optimization Algorithm Selection

    A Preliminary Study of Wood Species Classifacation System Based on Wood Knot Texture Using K-Nearest Neighbour With Optimized Features From Binary Magnetic Optimization Algorithm S... by Osman, Khairuddin, Mohamad, Syahrul Hisham, Jaafar, Hazriq Izzuan

    Published 2013
    “…The features of the wood knot images are extracted using Gray Level Co-Occurrence Matrix. Binary Magnetic Optimization Algorithm is use to optimize the feature selection process. …”
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  19. 19
    Arabic text classification using hybrid feature selection method using chi-square binary artificial bee colony algorithm

    Arabic text classification using hybrid feature selection method using chi-square binary artificial bee colony algorithm by Hijazi, Musab, Zeki, Akram M., Ismail, Amelia Ritahani

    Published 2021
    Get full text
    Get full text
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  20. 20
    Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection

    Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection by Almazini, Hussein

    Published 2022
    “…Thus, this study proposes an enhanced binary grey wolf optimiser (EBGWO) algorithm for FS in anomaly detection to overcome the algorithm issues. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:

Search Tools: