Search Results - (( parameter classification system algorithm ) OR ( parameter equalization based algorithm ))

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  1. 1
    Classification of diabetic retinopathy clinical features using image enhancement technique and convolutional neural network / Abdul Hafiz Abu Samah

    Classification of diabetic retinopathy clinical features using image enhancement technique and convolutional neural network / Abdul Hafiz Abu Samah by Abu Samah, Abdul Hafiz

    Published 2021
    “…Based on investigation different architecture and parameter, the suitable deep learning model has been presented to get optimize best result and testing time. …”
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  2. 2
    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction

    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A

    Published 2022
    “…The best accuracy result of 99.97% is obtained when the model operates in a hybrid mode based on a combination of PCA, LDA and RF algorithms, and the data reduction parameter equals 40.…”
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  3. 3
    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction

    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A.

    Published 2022
    “…The best accuracy result of 99.97% is obtained when the model operates in a hybrid mode based on a combination of PCA, LDA and RF algorithms, and the data reduction parameter equals 40…”
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  4. 4
    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction

    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Ahmed Dheyab, Saad, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A

    Published 2022
    “…The best accuracy result of 99.97% is obtained when the model operates in a hybrid mode based on a combination of PCA, LDA and RF algorithms, and the data reduction parameter equals 40.…”
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  5. 5
    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction

    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama

    Published 2022
    “…The best accuracy result of 99.97% is obtained when the model operates in a hybrid mode based on a combination of PCA, LDA and RF algorithms, and the data reduction parameter equals 40.…”
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  6. 6
    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction

    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama

    Published 2023
    “…The best accuracy result of 99.97% is obtained when the model operates in a hybrid mode based on a combination of PCA, LDA and RF algorithms, and the data reduction parameter equals 40.…”
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  7. 7
    Development of a personified face emotion recognition technique using fitness function

    Development of a personified face emotion recognition technique using fitness function by Muthukaruppan, Karthigayan, Mohd Rizon, Mohamed Juhari, Ramachandran, Nagarajan, Masanori, Sugisaka, Sazali, Yaacob, Mohd Rozailan, Mamat, Hazry, Desa

    Published 2009
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  8. 8
    Heart sound diagnosis using nonlinear ARX model / Noraishah Shamsuddin

    Heart sound diagnosis using nonlinear ARX model / Noraishah Shamsuddin by Shamsuddin, Noraishah

    Published 2011
    “…The Resilient Backpropagation (RPROP) algorithm is used to train the network. The optimized learning parameter used is 0.07 and the network has best performance when hidden neurons equal to 220. …”
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  9. 9
    Non-invasive diagnosis of risk in dengue patients using bioelectrical impedance analysis and artificial neural network

    Non-invasive diagnosis of risk in dengue patients using bioelectrical impedance analysis and artificial neural network by Ibrahim, F., Faisal, T., Mohamad Salim, M.I., Taib, M.N.

    Published 2010
    “…Four parameters were used for training and testing the ANN which are day of fever, reactance, gender, and risk group's quantification. …”
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  10. 10
    Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System

    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
    “…In this paper, an improved intrusion detection algorithm for multiclass classification was presented and discussed in detail. …”
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  11. 11
    Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm

    Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm by Yap K.S., Abidin I.Z., Ahmad A.R., Hussien Z.F., Pok H.L., Ismail F.I., Mohamad A.M.

    Published 2023
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  12. 12
    An accurate infant cry classification system based on continuos hidden Markov model

    An accurate infant cry classification system based on continuos hidden Markov model by Abdulaziz Y., Ahmad S.M.S.

    Published 2023
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  13. 13
    Adaptive parameter control strategy for ant-miner classification algorithm

    Adaptive parameter control strategy for ant-miner classification algorithm by Al-Behadili, Hayder Naser Khraibet, Sagban, Rafid, Ku-Mahamud, Ku Ruhana

    Published 2020
    “…This paper presents a new hybrid Ant-Miner classification algorithm and ant colony system (ACS), called ACS-Ant Miner. …”
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  14. 14
    Application of Bat Algorithm and Its Modified Form Trained with ANN in Channel Equalization

    Application of Bat Algorithm and Its Modified Form Trained with ANN in Channel Equalization by Pradyumna Kumar Mohapatra, Saroja Kumar Rout, Sukant Kishoro Bisoy, Sandeep Kautish, Muzaffar Hamzah, Muhammed Basheer Jasser, Ali Wagdy Mohamed

    Published 2022
    “…An alternative approach to training neural network-based equalizers is to use metaheuristic algorithms. …”
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  15. 15
    Charging and discharging model of lithium-ion battery for charge equalization control using particle swarm optimization algorithm

    Charging and discharging model of lithium-ion battery for charge equalization control using particle swarm optimization algorithm by Hoque M.M., Hannan M.A., Mohamed A.

    Published 2023
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  16. 16
    Classification of gait parameters in stroke with peripheral neuropathy (PN) by using k-Nearest Neighbors (kNN) algorithm / N. Anang ...[et al.]

    Classification of gait parameters in stroke with peripheral neuropathy (PN) by using k-Nearest Neighbors (kNN) algorithm / N. Anang ...[et al.] by Anang, N., Jailani, R., Mustafah, N., Manaf, H.

    Published 2018
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  17. 17
    Feature extraction and selection algorithm based on self adaptive ant colony system for sky image classification

    Feature extraction and selection algorithm based on self adaptive ant colony system for sky image classification by Petwan, Montha

    Published 2023
    “…FESSIC outperforms other algorithms for average classification accuracy for the KSVM, MLP, RF and DT classifiers. …”
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  18. 18
    Fuzzy modeling using Bat Algorithm optimization for classification

    Fuzzy modeling using Bat Algorithm optimization for classification by Noor Amidah, Ahmad Sultan

    Published 2018
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    Undergraduates Project Papers
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  19. 19
    Soft Set Decision/Forecasting System Based on Hybrid Parameter Reduction Algorithm

    Soft Set Decision/Forecasting System Based on Hybrid Parameter Reduction Algorithm by Mohammed, Mohammed Adam Taheir, Sadiq, Ali Safa, Ruzaini, Abdullah Arshah, Ernawan, Ferda, Mirjalili, Seyedali

    Published 2017
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  20. 20
    Affect classification using genetic-optimized ensembles of fuzzy ARTMAPs

    Affect classification using genetic-optimized ensembles of fuzzy ARTMAPs by Liew, W.S., Seera, M., Loo, C.K., Lim, E.

    Published 2015
    “…In addition, manual design of classification tasks often uses sub-optimum classifier parameter settings, leading to average classification performance. …”
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