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  1. 1
    Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak

    Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak by Dak, Ahmad Yusri

    Published 2019
    “…It involves development of Max-Min Rule-Based Classification Algorithm. The fourth stage is to design evaluation methodology of Max-Min Rule-Based Classification Algorithm using classifier model. …”
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  2. 2
    Swarm negative selection algorithm for electroencephalogram signals classification

    Swarm negative selection algorithm for electroencephalogram signals classification by Sahel Ba-Karait, Nasser Omer, Shamsuddin, Siti Mariyam, Sudirman, Rubita

    Published 2009
    “…DWT was used to analyze EEG signals at different frequency bands and statistics over the set of the wavelet coefficients were calculated to introduce the feature vector for SNS classifier. The SNS classification model use negative selection and PSO algorithms to form a set of memory Artificial Lymphocytes (ALCs) that have the ability to distinguish between normal and epileptic EEG patterns. …”
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  3. 3
    Artificial immune system based on real valued negative selection algorithms for anomaly detection

    Artificial immune system based on real valued negative selection algorithms for anomaly detection by Khairi, Rihab Salah

    Published 2015
    “…Self data are regarded as the normal behavioral pattern of the monitored system. …”
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  4. 4
    EEG Eye State Identification based on Statistical Feature and Common Spatial Pattern Filter

    EEG Eye State Identification based on Statistical Feature and Common Spatial Pattern Filter by Woon, W.C., Yahya, N., Badruddin, N.

    Published 2019
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  5. 5
    EEG Eye State Identification based on Statistical Feature and Common Spatial Pattern Filter

    EEG Eye State Identification based on Statistical Feature and Common Spatial Pattern Filter by Woon, W.C., Yahya, N., Badruddin, N.

    Published 2019
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  6. 6
    Pemetaan Pm10 Dan Aot Menggunakan Teknik Penderiaan Jauh Di Semenanjung Malaysia

    Pemetaan Pm10 Dan Aot Menggunakan Teknik Penderiaan Jauh Di Semenanjung Malaysia by San, Limhwee

    Published 2006
    “…The proposed algorithms were also validated using the multidate data. …”
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  7. 7
    The effect of pre-processing techniques and optimal parameters on BPNN for data classification

    The effect of pre-processing techniques and optimal parameters on BPNN for data classification by HUSSEIN, AMEER SALEH

    Published 2015
    “…In this research, a performance analysis based on different activation functions; gradient descent and gradient descent with momentum, for training the BP algorithm with pre-processing techniques was executed. …”
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  8. 8
    Improved Genetic Algorithm Multilayer Perceptron Network For Data Classification

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

    Published 2017
    “…The performance of improved GA has been evaluated using highly complicated and multimodal benchmark test functions and compared with the standard GA. Based on the occurrences of the best result obtained by an algorithm across different test functions; it is proven that the proposed method outperforms standard GA. …”
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  9. 9
    Ultrasound-based tissue characterization and classification of fatty liver disease: A screening and diagnostic paradigm

    Ultrasound-based tissue characterization and classification of fatty liver disease: A screening and diagnostic paradigm by Acharya, U.R., Faust, O., Molinari, F., Sree, S.V., Junnarkar, S.P., Sudarshan, V.

    Published 2015
    “…We then review the state-of-the-art US-based CAD techniques that utilize a range of image texture based features like entropy, Local Binary Pattern (LBP), Haralick textures and run length matrix in several automated decision making algorithms. …”
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  10. 10
    Rule-base wearable embedded platform for seizure detection from real EEG data in ambulatory state

    Rule-base wearable embedded platform for seizure detection from real EEG data in ambulatory state by Shakir, M., Malik, A.S., Kamel, N., Qidwai, U.

    Published 2014
    “…This gives an enhanced advantage over the existing EEG based seizure detection systems due to their complex pattern classification methodologies. …”
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  11. 11
    Rule-Base Wearable Embedded Platform for Seizure Detection from Real EEG Data in Ambulatory State

    Rule-Base Wearable Embedded Platform for Seizure Detection from Real EEG Data in Ambulatory State by Mohamed, Shakir, Malik, Aamir Saeed, Kamel , Nidal, Qidwai, Uvais

    Published 2014
    “…This gives an enhanced advantage over the existing EEG based seizure detection systems due to their complex pattern classification methodologies. …”
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  12. 12
    Fuzzy Platform for Embedded Wearable EEG Seizure Detection in Ambulatory State

    Fuzzy Platform for Embedded Wearable EEG Seizure Detection in Ambulatory State by Shakir, Mohamed, Malik, Aamir Saeed, Kamel , Nidal, Qidwai, Uvais

    Published 2014
    “…This gives an enhanced advantage over the existing EEG based seizure detection systems due to their complex pattern classification methodologies. …”
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  13. 13
    Embedded wearable EEG seizure detection in ambulatory state

    Embedded wearable EEG seizure detection in ambulatory state by Shakir, M., Malik, A.S., Kamel, N., Qidwai, U.

    Published 2014
    “…This gives an enhanced advantage over the existing EEG based seizure detection systems due to their complex pattern classification methodologies. …”
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  14. 14
    Intelligent Fuzzy Classifier for Pre-Seizure Detection from Real Epileptic Data

    Intelligent Fuzzy Classifier for Pre-Seizure Detection from Real Epileptic Data by Shakir, Mohamed, Malik, Aamir Saeed, Kamel, Nidal S., Qidwai, Uvais

    Published 2014
    “…This gives a more practical functionality for such a system to be used in a wearable fashion over the existing Electroencephalogram (EEG) based seizure detection systems due to their complex pattern classification methodologies. …”
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  15. 15
    Intelligent Fuzzy Classifier for pre-seizure detection from real epileptic data

    Intelligent Fuzzy Classifier for pre-seizure detection from real epileptic data by Shakir, M., Malik, A.S., Kamel, N., Qidwai, U.

    Published 2014
    “…This gives a more practical functionality for such a system to be used in a wearable fashion over the existing Electroencephalogram (EEG) based seizure detection systems due to their complex pattern classification methodologies. …”
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  16. 16
    Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using k-Nearest Neighbour (k-NN)

    Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using k-Nearest Neighbour (k-NN) by Mohamad Hushnie, Haron, Nur Azzimah, Zamri, Khairunisa, Muthusamy

    Published 2023
    “…The data from this process were first transformed using min-max normalization and then, analysed using exploratory and descriptive analysis to discover patterns between input variables and concrete grades. …”
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  17. 17
    Analyzing RNA-Seq gene expression data using deep learning approaches for cancer classification

    Analyzing RNA-Seq gene expression data using deep learning approaches for cancer classification by Laiqa Rukhsar, Waqas Haider Bangyal, Muhammad Sadiq Ali Khan, Ag Asri Ag Ibrahim, Kashif Nisar, Danda B. Rawat

    Published 2022
    “…In the last phase, classification is performed, and eight DL algorithms are used. …”
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  18. 18
    Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using kNearest Neighbour (k-NN)

    Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using kNearest Neighbour (k-NN) by Mohamad Hushnie, Haron, Nur Azzimah, Zamri, Khairunisa, Muthusamy

    Published 2023
    “…The data from this process were first transformed using min-max normalization and then, analysed using exploratory and descriptive analysis to discover patterns between input variables and concrete grades. …”
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  19. 19
    Pattern Classification of Human Epithelial Images

    Pattern Classification of Human Epithelial Images by Mohd Isa, Mohd Fazlie

    Published 2016
    “…This project shows an important role to diagnosis autoimmune disorder which is by a comparative analysis on the most appropriate clustering technique for the segmentation and also to develop algorithm for positivity classification. …”
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  20. 20
    A hybrid-based modified adaptive fuzzy inference engine for pattern classification

    A hybrid-based modified adaptive fuzzy inference engine for pattern classification by Sayeed, Md. Shohel, Ramli, Abdul Rahman, Hossen, Md. Jakir, Samsudin, Khairulmizam, Rokhani, Fakhrul Zaman

    Published 2011
    “…The Neuro-Fuzzy hybridization scheme has become of research interest in pattern classification over the past decade. The present paper proposes a hybrid Modified Adaptive Fuzzy Inference Engine (MAFIE) for pattern classification. …”
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