Search Results - (( initial optimization method algorithm ) OR ( using classification _ algorithm ))

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  1. 1

    Application of Optimization Methods for Solving Clustering and Classification Problems by Shabanzadeh, Parvaneh

    Published 2011
    “…Also a new algorithm for finding the initial point is proposed. …”
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  2. 2

    Improved cuckoo search based neural network learning algorithms for data classification by Abdullah, Abdullah

    Published 2014
    “…Specifically, 6 benchmark classification datasets are used for training the hybrid Artificial Neural Network algorithms. …”
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  3. 3

    Efficient classifying and indexing for large iris database based on enhanced clustering method by Khalaf, Emad Taha, Mohammed, Muamer N., Kohbalan, Moorthy, Khalaf, Ahmad Taha

    Published 2018
    “…The proposed method can be used to perform global search and exhibits quick convergence rate while optimizing the initial clustering centers of the K-means algorithm. …”
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  4. 4

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

    Published 2019
    “…The classification of estimation-based metaheuristic algorithms has been introduced for solving optimization problems. …”
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  5. 5

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

    Published 2019
    “…The classification of estimation-based metaheuristic algorithms has been introduced for solving optimization problems. …”
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  6. 6

    Opposition Based Competitive Grey Wolf Optimizer For EMG Feature Selection by Too, Jing Wei, Abdullah, Abdul Rahim

    Published 2020
    “…Four state-of-the-art algorithms include particle swarm optimization, flower pollination algorithm, butterfly optimization algorithm, and CBGWO are used to examine the effectiveness of proposed methods in feature selection. …”
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  7. 7

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

    Published 2020
    “…Five state-of-the-art FS methods are used to evaluate the effectiveness of proposed methods in this work. …”
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  8. 8

    Condition diagnosis of bearing system using multiple classifiers of ANNs and adaptive probabilities in genetic algorithms by Wulandhari, Lili A., Wibowo, Antoni, Desa, Mohammad I.

    Published 2014
    “…The mANNs are used to provide several best initial weights which are optimized by APGAs.The set optimized weights from APGAs, afterward, are used as the best weights for condition diagnosis. …”
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  9. 9

    Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images by Adil Humayun, Khan

    Published 2024
    “…This proposed classifier achieved 98.2% classification accuracy on the ISIC dataset. These algorithms are proposed while implying modifications to existing statistical, machine, and deep learning methods.…”
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  10. 10

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

    Published 2018
    “…In the OGC framework, the exhibited explorative search behavior of the Gravitational Clustering (GC) algorithm has been addressed by (i) eliminating the agent velocity accumulation, and (ii) integrating an initialization method of agents using variance and median to subrogate the exploration process. …”
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  11. 11

    Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System by Ali, Mohammed Hasan, Mohamed Fadli, Zolkipli

    Published 2019
    “…In this paper, the particle swan optimization algorithm (PSO) was used to obtain an optimal set of initial parameters for Reduce Kernel FLN (RK-FLN), thus, creating an optimal RKFLN classifier named PSO-RKELM. …”
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  14. 14

    Nature-Inspired Drone Swarming for Wildfires Suppression Considering Distributed Fire Spots and Energy Consumption by Alsammak I.L.H., Mahmoud M.A., Gunasekaran S.S., Ahmed A.N., Alkilabi M.

    Published 2024
    “…Our quantitative tests show that the improved model has the best coverage (95.3%, 84.3% and 65.8%, respectively) compared to two other methods Levy Flight (LF) algorithm and Particle Swarm Optimization (PSO), which use the same initial parameter values. …”
    Article
  15. 15

    A New Competitive Binary Grey Wolf Optimizer To Solve The Feature Selection Problem In EMG Signals Classification by Too, Jing Wei, Abdullah, Abdul Rahim, Mohd Saad, Norhashimah, Mohd Ali, Nursabillilah, Tee, Wei Hown

    Published 2018
    “…To evaluate the effectiveness of proposed method, CBGWO is compared with binary grey wolf optimization (BGWO1 and BGWO2), binary particle swarm optimization (BPSO), and genetic algorithm (GA). …”
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  16. 16

    Application of Decision Trees in Athlete Selection: A Cart Algorithm Approach by Riska Wahyu, Romadhonia, A'yunin, Sofro, Danang, Ariyanto, Dimas Avian, Maulana, Junaidi Budi, Prihanto

    Published 2023
    “…The focus of this study is on the use of DTs, employing the Classification and Regression Trees (CART) algorithm, in the initial screening of athletes. …”
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  17. 17

    Fault classification in smart distribution network using support vector machine by Chuan O.W., Ab Aziz N.F., Yasin Z.M., Salim N.A., Wahab N.A.

    Published 2023
    “…Initial finding from simulation result indicates that the proposed method is quick in learning and shows good accuracy values on faults type classification in distribution system. …”
    Article
  18. 18

    Comparative Analysis Using Bayesian Approach To Neural Network Of Translational Initiation Sites In Alternative Polymorphic Contex by Herman, Nanna Suryana, Husin, Nurul Arneida, Hussin, Burairah

    Published 2012
    “…The objectives of this paper are to develop useful algorithms and to build a new classification model for the case study.The first approach of neural network includes training on algorithms of Resilient Backpropagation,Scaled Conjugate Gradient Backpropagation and Levenberg-Marquardt.The outputs are used in comparison with Bayesian Neural Network for efficiency comparison.The results showed that Resilient Backpropagation have the consistency in all measurement but performs less in accuracy.In second approach,the Bayesian Classifier_01 outperforms the Resilient Backpropagation by successfully increasing the overall prediction accuracy by 16.0%.The Bayesian Classifier_02 is built to improve the accuracy by adding new features of chemical properties as selected by the Information Gain Ratio method,and increasing the length of the window sequence to 201.The result shows that the built model successfully increases the accuracy by 96.0%.In comparison,the Bayesian model outperforms Tikole and Sankararamakrishnan (2008) by increasing the sensitivity by 10% and specificity by 26%. …”
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  19. 19

    Improved Genetic Algorithm Multilayer Perceptron Network For Data Classification by Ahmad, Fadzil

    Published 2017
    “…Hidden node size, initial weights and feature selection of the MLP that play significant role in the classification performance are selected to be automatically optimized by the improved GA. …”
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  20. 20

    Using genetic algorithms to optimise land use suitability by Pormanafi, Saeid

    Published 2012
    “…The third objective is to optimize the land use map using economic benefits. …”
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