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  1. 1
    Intelligent grading of agarwood essential oil quality using artificial neural network (ANN) / Noratikah Zawani Mahabob

    Intelligent grading of agarwood essential oil quality using artificial neural network (ANN) / Noratikah Zawani Mahabob by Mahabob, Noratikah Zawani

    Published 2022
    “…The training and validation of the ANN was based on optimization of its training parameters and guided by the convergence of the mean squared errors (MSE). …”
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  2. 2
    Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying

    Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying by Khaw , Hui Ying

    Published 2019
    “…In order to reduce the training time and computational cost of the algorithm, Principal Components Analysis (PCA) pretraining strategy is deployed to obtain data adaptive filter banks. …”
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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
    “…Researchers seek to develop intelligent algorithms to detect and prevent DDoS attacks. …”
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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 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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  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 Ahmed Dheyab, Saad, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A

    Published 2022
    “…Researchers seek to develop intelligent algorithms to detect and prevent DDoS attacks. …”
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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 2022
    “…Researchers seek to develop intelligent algorithms to detect and prevent DDoS attacks. …”
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  7. 7
    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
    “…Researchers seek to develop intelligent algorithms to detect and prevent DDoS attacks. …”
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  8. 8
    Optimization and discretization of dragonfly algorithm for solving continuous and discrete optimization problems

    Optimization and discretization of dragonfly algorithm for solving continuous and discrete optimization problems by Bibi Amirah Shafaa, Emambocus

    Published 2024
    “…The ANNs trained by the optimized DA also achieve higher accuracy than those trained by some other swarm intelligence algorithms. …”
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  9. 9
    Classification of left/right hand movement from EEG signal by intelligent algorithms

    Classification of left/right hand movement from EEG signal by intelligent algorithms by Baig, M.Z., Javed, E., Ayaz, Y., Afzal, W., Gillani, S.O., Naveed, M., Jamil, M.

    Published 2015
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  10. 10
    Multidimensional Minimization Training Algorithms for Steam Boiler Drum Level Trip Using Artificial Intelligence Monitoring System

    Multidimensional Minimization Training Algorithms for Steam Boiler Drum Level Trip Using Artificial Intelligence Monitoring System by Ismail, F. B., Al-Kayiem, Hussain H.

    Published 2010
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  11. 11
    Performance Evaluation of BPSO & PCA as Feature Reduction Techniques for Bearing Fault Diagnosis

    Performance Evaluation of BPSO & PCA as Feature Reduction Techniques for Bearing Fault Diagnosis by Faysal, Atik, Ngui, Wai Keng, M. H., Lim

    Published 2022
    “…The reduced feature subsets were 12 and 35 for PCA and BPSO, respectively. K-Nearest Neighbours (K-NN) was used as an intelligent method for fault diagnosis. …”
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  12. 12
    Hybrid Intelligent Warning System for Boiler tube Leak Trips

    Hybrid Intelligent Warning System for Boiler tube Leak Trips by Singh D., Ismail F.B., Shakir Nasif M.

    Published 2023
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  13. 13
    Integration of dual intelligent algorithms in shunt active power filter

    Integration of dual intelligent algorithms in shunt active power filter by Abdul Rahman, Nor Farahaida, Mohd Radzi, Mohd Amran, Mariun, Norman, Che Soh, Azura, Abd Rahim, Nasrudin

    Published 2013
    “…This paper presents an integration of dual intelligent algorithms: artificial neural network (ANN) based fundamental component extraction algorithm and fuzzy logic based DC-link voltage self-charging algorithm (fuzzy self-charging algorithm), in a three-phase three-wire shunt active power filter (SAPF). …”
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  14. 14
    Effect of input variables selection on energy demand prediction based on intelligent hybrid neural networks

    Effect of input variables selection on energy demand prediction based on intelligent hybrid neural networks by Islam, B., Baharudin, Z., Nallagownden, P.

    Published 2015
    “…The efficacy of these models depends upon many factors such as, neural network architecture, type of training algorithm, input training and testing data set and initial values of synaptic weights. …”
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  15. 15
    Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process

    Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process by Ali Al-Assadi, Hayder M. A.

    Published 2004
    “…The design network is trained by presenting several target machining data that the network must learn according to a learning rule (algorithm). …”
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  16. 16
    Optimising neural network training efficiency through spectral parameter-based multiple adaptive learning rates

    Optimising neural network training efficiency through spectral parameter-based multiple adaptive learning rates by Yeong, Lin Koay, Hong, Seng Sim, Yong, Kheng Goh, Sing, Yee Chua, Wah, June Leong

    Published 2024
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  17. 17
    A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption

    A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption by Chiroma, H., Abdullahi, U.A., Hashem, I.A.T., Saadi, Y., Al-Dabbagh, R.D., Ahmad, M.M., Dada, G.E., Danjuma, S., Maitama, J.Z., Abubakar, A., Abdulhamid, S.�M.

    Published 2019
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  18. 18
    Analyzing CT images for detecting lung cancer by applying the computational intelligence-based optimization techniques

    Analyzing CT images for detecting lung cancer by applying the computational intelligence-based optimization techniques by Pethuraj, Mohamed Shakeel, Mohd Aboobaider, Burhanuddin, Salahuddin, Lizawati

    Published 2022
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  19. 19
    Performance evaluation of BPSO & PCA as feature reduction techniques for bearing fault diagnosis

    Performance evaluation of BPSO & PCA as feature reduction techniques for bearing fault diagnosis by Faysal, Atik, Ngui, Wai Keng, Lim, M. H.

    Published 2021
    “…The reduced feature subsets were 12 and 35 for PCA and BPSO, respectively. K-Nearest Neighbours (K-NN) was used as an intelligent method for fault diagnosis. …”
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  20. 20
    Hybrid Intelligent Warning System for Boiler tube Leak Trips

    Hybrid Intelligent Warning System for Boiler tube Leak Trips by Singh, D., Ismail, F.B., Shakir Nasif, M.

    Published 2017
    “…The first intelligent warning system (IWS-1) represents the use of pure artificial neural network system whereas the second intelligent warning system (IWS-2) represents merging of genetic algorithms and artificial neural networks as a hybrid intelligent system. …”
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