Search Results - (( using function methods algorithm ) OR ( _ classification modified algorithm ))

Search alternatives:

Refine Results
  1. 1
    Functional link neural network with modified bee-firefly learning algorithm for classification task

    Functional link neural network with modified bee-firefly learning algorithm for classification task by Mohmad Hassim, Yana Mazwin

    Published 2016
    “…The standard learning method for tuning weights in FLNN is Backpropagation (BP) learning algorithm. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  2. 2
    An approach to improve functional link neural network training using modified artificial bee colony for classification task

    An approach to improve functional link neural network training using modified artificial bee colony for classification task by Yana Mazwin Mohmad Hassim, Rozaida Ghazali

    Published 2013
    “…The standard method for tuning the weight in FLNN is using a Backpropagation (BP) learning algorithm. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  3. 3
    An approach to improve functional link neural network training using modified artificial bee colony for classification task

    An approach to improve functional link neural network training using modified artificial bee colony for classification task by Mohmad Hassim, Yana Mazwin, Ghazali, Rozaida

    Published 2012
    “…The standard method for tuning the weight in FLNN is using a Backpropagation (BP) learning algorithm. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  4. 4
    An approach to improve functional link neural network training using modified artificial bee colony for classification task

    An approach to improve functional link neural network training using modified artificial bee colony for classification task by Mohmad Hassim, Yana Mazwin, Ghazali, Rozaida

    Published 2012
    “…The standard method for tuning the weight in FLNN is using a Backpropagation (BP) learning algorithm. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  5. 5
    Modified anfis architecture with less computational complexities for classification problems

    Modified anfis architecture with less computational complexities for classification problems by Talpur, Noureen

    Published 2018
    “…Furthermore, researchers have mainly used metaheuristic algorithms to avoid the problem of local minima in standard learning method. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  6. 6
    Feature fusion using a modified genetic algorithm for face and signature recognition system

    Feature fusion using a modified genetic algorithm for face and signature recognition system by Suryanti, Awang

    Published 2015
    “…A modified fitness function in Wrapper GA was introduced by adding a function to maintain the balanced of the selected features. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  7. 7
    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
    “…Firstly, a non-linear time-varying modified Sigmoid transfer function is used as the binarization method. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  8. 8
    Fair bandwidth distribution marking and scheduling algorithm in network traffic classification

    Fair bandwidth distribution marking and scheduling algorithm in network traffic classification by Al-Kharasani, Ameen Mohammed Abdulkarem

    Published 2019
    “…Thus, proposing the method of reestimating the dropping functions in the RED algorithm. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  9. 9
    Logistic regression methods for classification of imbalanced data sets

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

    Published 2012
    “…These results can be seen as further explanation on the success of Truncated Newton method in TR-KLR and TR Iteratively Re-weighted Least Square (TR-IRLS) algorithm respectively, because of the equivalence of iterative method used by these algorithms. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  10. 10
    A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani

    A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani by Mahmoud Reza, Saybani

    Published 2016
    “…The components of the AIRS2 algorithm that pose problems will be modified. This thesis proposes three new hybrid algorithms: The FRA-AIRS2 algorithm uses fuzzy logic to improve data reduction capability of AIRS2 and to solve the linearity problem associated with resource allocation of AIRS. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  11. 11
    Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification

    Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification by Myaser, Jwan

    Published 2020
    “…Nevertheless, AC is not required for LCM if the original multi-spectral image is used. The last phase involves developing a new fusion algorithm using SVM and Fuzzy K-Means Clustering (FKM) algorithms for Sentinel 2 data to enhance LCM accuracy. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  12. 12
    RMIL/AG: A new class of nonlinear conjugate gradient for training back propagation algorithm

    RMIL/AG: A new class of nonlinear conjugate gradient for training back propagation algorithm by Basri, S.M.M., Nawi, N.M., Mamat, M., Hamid, N.A.

    Published 2018
    “…The results show that the computational efficiency of the proposed method was better than the conventional BP algorithm.…”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  13. 13
    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
    “…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:
  14. 14
    A framework of modified adaptive neuro-fuzzy inference engine

    A framework of modified adaptive neuro-fuzzy inference engine by Hossen, Md. Jakir

    Published 2012
    “…The Takagi-Sugeno-Kang (TSK) type fuzzy inference system was chosen and constructed by an automatic generation of clusters as well as membership functions and minimal rules through the use of hybrid fuzzy clustering and the modified apriori algorithms respectively. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  15. 15
    Modern fuzzy min max neural networks for pattern classification

    Modern fuzzy min max neural networks for pattern classification by Al Sayaydeh, Osama Nayel Ahmad

    Published 2019
    “…Among these algorithms, Fuzzy Min Max (FMM) neural network algorithm has been proven to be one of the premier neural networks for undertaking the pattern classification problems. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  16. 16
    Modified Piecewise Linear Mapping Contrast Enhancement And Local Otsu Segmentation Methods For Hep-2 Cell Images

    Modified Piecewise Linear Mapping Contrast Enhancement And Local Otsu Segmentation Methods For Hep-2 Cell Images by Baharom, Mohamad Shahrul Affendi

    Published 2019
    “…This study analyses the importance of both methods, which could possibly improve the HEP-2 classification process. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  17. 17
    Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network

    Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network by Zafar, R., Kamel, N., Naufal, M., Malik, A.S., Dass, S.C., Ahmad, R.F., Abdullah, J.M., Reza, F.

    Published 2017
    “…In this study, an algorithm is developed using Multivariate pattern analysis (MVPA) and modified CNN to decode the behavior of brain for different images with limited data set. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  18. 18
    Development of a new robust hybrid automata algorithm based on surface electromyography (SEMG) signal for instrumented wheelchair control

    Development of a new robust hybrid automata algorithm based on surface electromyography (SEMG) signal for instrumented wheelchair control by Mohd Hanafi, Muhammad Sidik

    Published 2020
    “…This method would be a control method to activate power assist system and selected based on conditions set in the algorithm. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  19. 19
    A fuzzy approach for early human action detection / Ekta Vats

    A fuzzy approach for early human action detection / Ekta Vats by Ekta, Vats

    Published 2016
    “…In order to perform early human action detection, the conventional classification problem is modified into frame-by-frame level classification. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  20. 20
    An efficient anomaly intrusion detection method with feature selection and evolutionary neural network

    An efficient anomaly intrusion detection method with feature selection and evolutionary neural network by Sarvari, Samira, Mohd Sani, Nor Fazlida, Mohd Hanapi, Zurina, Abdullah @ Selimun, Mohd Taufik

    Published 2020
    “…This research designed an anomaly-based detection, by adopting the modified Cuckoo Search Algorithm (CSA), called Mutation Cuckoo Fuzzy (MCF) for feature selection and Evolutionary Neural Network (ENN) for classification. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:

Search Tools: