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  1. 1
    Hybrid intelligent approach for network intrusion detection

    Hybrid intelligent approach for network intrusion detection by Al-Mohammed, Wael Hasan Ali

    Published 2015
    “…Due to the prevailing limitations of finding novel attacks, high false detection, and accuracy in previous intrusion detection approaches, this study has proposed a hybrid intelligent approach for network intrusion detection based on k-means clustering algorithm and support vector machine classification algorithm. …”
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  2. 2
    Domestic garbage target detection based on improved YOLOv5 algorithm

    Domestic garbage target detection based on improved YOLOv5 algorithm by Ma, Haohao, Wu, Xuping, As'arry, Azizan, Han, Weiliang, Mu, Tong, Feng, Yanwei

    Published 2023
    “…Experiments have proved that the accuracy of intelligent classification reached 98.27%, which is 3.85% higher than the original algorithm. …”
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  3. 3
    Leveraging CQT-VMD and pre-trained AlexNet architecture for accurate pulmonary disease classification from lung sound signals

    Leveraging CQT-VMD and pre-trained AlexNet architecture for accurate pulmonary disease classification from lung sound signals by Neili, Zakaria, Sundaraj, Kenneth

    Published 2025
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  4. 4
    The use of artificial neural network in the classification of EMG signals

    The use of artificial neural network in the classification of EMG signals by Ahsan, Md. Rezwanul, Ibrahimy, Muhammad Ibn, Khalifa, Othman Omran

    Published 2012
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    Proceeding Paper
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  5. 5
    A novel hybrid artificial intelligence technique for colpitts oscillator design

    A novel hybrid artificial intelligence technique for colpitts oscillator design by Ghazali , Mohamad, Amsa, B Ameer, Aibinu, Abiodun Musa, Salami, Momoh Jimoh Emiyoka

    Published 2014
    “…In this paper, a new method of designing Colpitts oscillator using hybrid artificial intelligence comprising evolutionary-based Genetic Algorithm (GA) and artificial neural network (ANN) has been proposed. …”
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  6. 6
    Evaluation of energy-saving potential for optimal time response of HVAC control system in smart buildings

    Evaluation of energy-saving potential for optimal time response of HVAC control system in smart buildings by Homod R.Z., Gaeid K.S., Dawood S.M., Hatami A., Sahari K.S.

    Published 2023
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  7. 7
    IOT Based Smart Wastewater Treatment Model for Industry 4.0 Using Artificial Intelligence

    IOT Based Smart Wastewater Treatment Model for Industry 4.0 Using Artificial Intelligence by Singh, D.N., Murugamani, C., Kshirsagar, P.R., Tirth, V., Islam, S., Qaiyum, S., Suneela, B., Al Duhayyim, M., Waji, Y.A.

    Published 2022
    “…To anticipate COD levels in influential and effluent areas, two ANN-based techniques have been presented. The proper structure for the neural network models was identified via a variety of training and model testing methods. …”
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  8. 8
    Pengesanan Kerosakan Bahan Penebat Transformer Dengan Menggunakan Rangkaian Neural Buatan

    Pengesanan Kerosakan Bahan Penebat Transformer Dengan Menggunakan Rangkaian Neural Buatan by Che Osman, Suzita

    Published 2006
    “…Three types of learning algorithm are used in this project to train the MLP network, which are resilient backpropagation, Bayesian regularization and Levenberg-Marquardt. …”
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    Monograph
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  9. 9
    Design of intelligent control system and its application on fabricated conveyor belt grain dryer

    Design of intelligent control system and its application on fabricated conveyor belt grain dryer by Lutfy, Omar F.

    Published 2011
    “…Moreover, three evolutionary algorithms (EAs), in particular a real-coded genetic algorithm (GA), a particle swarm optimization (PSO), and a global-best harmony search (GHS), were separately used to train the proposed controller and to determine its scaling factors. …”
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  10. 10
    Real time self-calibration algorithm of pressure sensor for robotic hand glove system

    Real time self-calibration algorithm of pressure sensor for robotic hand glove system by Almassri, Ahmed M. M.

    Published 2019
    “…Afterwards, the PSCA was implemented and tested in real time based on MCU and software (MATLAB). For validity and performance purpose of PSCA, the MSE and MAPE are calculated of 0.30 and 1.21% base on MCU and 0.08 and 0.6 base on MATLAB respectively. …”
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  11. 11
    Classification of agarwood grades using ANN

    Classification of agarwood grades using ANN by M. S., Najib, Mohd Nasir, Taib, Nor Azah, Mohd Ali, Mohd Nasir, Mat Arip, Abd. Majid, Jalil

    Published 2011
    “…The price of the Agarwood is determined according to its quality, which is generally decided based on certain grade. This paper proposes an intelligent grading technique for the wood using advanced signal processing of E-nose measurements. …”
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  12. 12
    Multilanguage speech-based gender classification using time-frequency features and SVM classifier

    Multilanguage speech-based gender classification using time-frequency features and SVM classifier by Wani, Taiba, Gunawan, Teddy Surya, Mansor, Hasmah, Ahmad Qadri, Syed Asif, Sophian, Ali, Ambikairajah, Eliathamby, Ihsanto, Eko

    Published 2021
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  13. 13
    Agarwood oil grade clustering of aquilaria malaccensis species using Extraction by GC-MS analysis: Efficient KNN algorithm based on patterns visualization of two-dimensional graph

    Agarwood oil grade clustering of aquilaria malaccensis species using Extraction by GC-MS analysis: Efficient KNN algorithm based on patterns visualization of two-dimensional graph by Siti Mariatul Hazwa, Mohd Huzir, Anis Hazirah ‘Izzati H., Al-Hadi, Amir Hussairi, Zaidi, Nurlaila F., Ismail, Zakiah, Mohd Yusoff, Saiful Nizam, Tajuddin, Mohd Nasir, Taib

    Published 2024
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  14. 14
    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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  15. 15
    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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  16. 16
    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
    Conference Paper
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  17. 17
    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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  18. 18
    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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  19. 19
    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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  20. 20
    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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