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  1. 1
    Segmentation Assisted Object Distinction For Direct Volume Rendering

    Segmentation Assisted Object Distinction For Direct Volume Rendering by Irani, Arash Azim Zadeh

    Published 2013
    “…A set of image processing techniques are creatively employed in the design of K-means based hybrid segmentation algorithm.…”
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  2. 2
    A De-noising Scheme for Enhancing Power Quality Problem Classification System Based on Wavelet Transform and Rule-Based Method

    A De-noising Scheme for Enhancing Power Quality Problem Classification System Based on Wavelet Transform and Rule-Based Method by Keow, Chuah Heng, Nallagownden, Perumal, K. S. , Rama Rao

    Published 2011
    “…A Power quality Classification system can easily extract features from the second detail signal obtained after Discrete Wavelet Transform and using these features to construct a Rule Based Algorithm for identifying types of disturbances that exist in the captured power signal. …”
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  3. 3
    A De-noising Scheme for Wavelet Based Power Quality Disturbances Detection and Classification system

    A De-noising Scheme for Wavelet Based Power Quality Disturbances Detection and Classification system by Keow, Chuah Heng, Nallagownden, Perumal, K. S. , Rama Rao

    Published 2011
    “…A Power quality Classification system can easily extract features from the second detail signal obtained after Discrete Wavelet Transform and using these features to construct a Rule Based Algorithm for identifying types of disturbances that exist in the captured power signal. …”
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  4. 4
    POWER QUALITY CLASSIFICATION WITH DE-NOISING SCHEME USING WAVELET TRANSFORM AND RULE- BASED METHOD

    POWER QUALITY CLASSIFICATION WITH DE-NOISING SCHEME USING WAVELET TRANSFORM AND RULE- BASED METHOD by HENG KEOW, CHUAH

    Published 2012
    “…Unique features from the I", 4t h ,7th and 8thl evel details are obtained as criteria for developing a Rules-Based Algorithm for classifying disturbances that have occurred. …”
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  5. 5
    Detecting Malware with Classification Machine Learning Techniques

    Detecting Malware with Classification Machine Learning Techniques by Mohd Yusof, Mohd Azahari, Abdullah, Zubaile, Hamid Ali, Firkhan Ali, Mohamad Sukri, Khairul Amin, Shaker Hussain, Hanizan

    Published 2023
    “…The evergrowing volume of malware threats renders conventional signature-based methods insufficient in shielding against novel and intricate attacks. …”
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  6. 6
    Detecting Malware with Classification Machine Learning Techniques

    Detecting Malware with Classification Machine Learning Techniques by Mohd Yusof, Mohd Azahari, Abdullah, Zubaile, Hamid Ali, Firkhan Ali, Mohamad Sukri, Khairul Amin, Shaker Hussain, Hanizan

    Published 2023
    “…The evergrowing volume of malware threats renders conventional signature-based methods insufficient in shielding against novel and intricate attacks. …”
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  7. 7
    A Reference Based Surface Defect Segmentation Algorithm For Automatic Optical Inspection System

    A Reference Based Surface Defect Segmentation Algorithm For Automatic Optical Inspection System by Wong, Ze-Hao

    Published 2020
    “…However, present complex algorithms which are accurate require high processing power using a large size of learning dataset without labelling error. …”
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  8. 8
    Training functional link neural network with ant lion optimizer

    Training functional link neural network with ant lion optimizer by Mohmad Hassim, Yana Mazwin, Ghazali, Rozaida

    Published 2020
    “…Functional Link Neural Network (FLNN) has becoming as an important tool used in machine learning due to its modest architecture. …”
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  9. 9
    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 single layer property of FLNN also make the learning algorithm used less complicated compared to MLP network. …”
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  10. 10
    A modified generalized RBF model with EM-based learning algorithm for medical applications

    A modified generalized RBF model with EM-based learning algorithm for medical applications by Ma, Li Ya, Abdul Rahman, Abdul Wahab, Quek, Chai

    Published 2006
    “…Radial Basis Function (RBF) has been widely used in different fields, due to its fast learning and interpretability of its solution. …”
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  11. 11
    An improved artificial bee colony algorithm for training multilayer perceptron in time series prediction

    An improved artificial bee colony algorithm for training multilayer perceptron in time series prediction by Shah, Habib

    Published 2014
    “…Furthermore, here these algorithms used to train the MLP on two tasks; the seismic event's prediction and Boolean function classification. …”
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  12. 12
    Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Predicting Reservoir Water Level

    Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Pr... by Sammen S.S., Ehteram M., Sheikh Khozani Z., Sidek L.M.

    Published 2024
    “…For water level prediction, lagged rainfall and water level are used. In this study, we used extreme learning machine (ELM)-multi-kernel least square support vector machine (ELM-MKLSSVM), extreme learning machine (ELM)-LSSVM-polynomial kernel function (PKF) (ELM-LSSVM-PKF), ELM-LSSVM-radial basis kernel function (RBF) (ELM-LSSVM-RBF), ELM-LSSVM-Linear Kernel function (LKF), ELM, and MKLSSVM models to predict water level. …”
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  13. 13
    Differential evolution for neural networks learning enhancement

    Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

    Published 2008
    “…These algorithms can be used successfully in many applications requiring the optimization of a certain multi-dimensional function. …”
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  14. 14
    Dynamic training rate for backpropagation learning algorithm

    Dynamic training rate for backpropagation learning algorithm by Al-Duais, M. S., Yaakub, Abdul Razak, Yusoff, Nooraini

    Published 2013
    “…In this paper, we created a dynamic function training rate for the Back propagation learning algorithm to avoid the local minimum and to speed up training.The Back propagation with dynamic training rate (BPDR) algorithm uses the sigmoid function.The 2-dimensional XOR problem and iris data were used as benchmarks to test the effects of the dynamic training rate formulated in this paper.The results of these experiments demonstrate that the BPDR algorithm is advantageous with regards to both generalization performance and training speed. …”
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  15. 15
    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy

    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

    Published 2019
    “…The proposed algorithm is compared with the state-of-the-art feature selection algorithms using three different datasets. …”
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  16. 16
    Particle swarm optimization for neural network learning enhancement

    Particle swarm optimization for neural network learning enhancement by Abdull Hamed, Haza Nuzly

    Published 2006
    “…Backpropagation (BP) algorithm is widely used to solve many real world problems by using the concept of Multilayer Perceptron (MLP). …”
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  17. 17
    Support directional shifting vector: A direction based machine learning classifier

    Support directional shifting vector: A direction based machine learning classifier by Kowsher, Md., Hossen, Imran, Tahabilder, Anik, Prottasha, Nusrat Jahan, Habib, Kaiser, Zafril Rizal, M Azmi

    Published 2021
    “…The positional error of the linear function has been modelled as a loss function which is iteratively optimized using the gradient descent algorithm. …”
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  18. 18
    Modeling time series data using Genetic Algorithm based on Backpropagation Neural network

    Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

    Published 2018
    “…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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  19. 19
    Comparison between Lamarckian Evolution and Baldwin Evolution of neural network

    Comparison between Lamarckian Evolution and Baldwin Evolution of neural network by Taha, Imad, Inazy, Qabas

    Published 2006
    “…Hybrid genetic algorithms are the combination of learning algorithms(Back propagation), usually working as evaluation functions, and genetic algorithms. …”
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  20. 20
    A harmony search-based learning algorithm for epileptic seizure prediction

    A harmony search-based learning algorithm for epileptic seizure prediction by Kee, Huong Lai, Zainuddin, Zarita, Ong, Pauline

    Published 2016
    “…The proposed harmony search-based learning algorithm is used in the task of epileptic seizure prediction. …”
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