Search Results - (( parameter estimation methods algorithm ) OR ( pattern machine learning algorithm ))

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    Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network by Zafar, R., Kamel, N., Naufal, M., Malik, A.S., Dass, S.C., Ahmad, R.F., Abdullah, J.M., Reza, F.

    Published 2017
    “…MVPA-CNN based proposed algorithm is compared with region of interest (ROI) based method and MVPA based estimated values. …”
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    Article
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    River flow prediction based on improved machine learning method: Cuckoo Search-Artificial Neural Network by Zanial W.N.C.W., Malek M.B.A., Reba M.N.M., Zaini N., Ahmed A.N., Sherif M., Elshafie A.

    Published 2024
    “…Therefore, it is necessary to precisely estimate how the river flow will alter as a result of changing rainfall patterns. Finding the best value for the hyper-parameters is one of the problems with machine learning algorithms, which have lately been adopted by many academics. …”
    Article
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    Three-dimensional craniometrics identification model and cephalic index classification of Malaysian sub-adults: A multi-slice computed tomography study / Sharifah Nabilah Syed Mohd... by Sharifah Nabilah , Syed Mohd Hamdan

    Published 2024
    “…The primary focus is to determine the biological profile of unknown individuals by estimating their sex and ethnicity. Sex and ethnicity estimation methods utilised in adult are less effective in sub-adults due to varied cranium patterns during growth. …”
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    Thesis
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    Machine learning predictions of stock market pattern using Econophysics approach by Roslan, Nur Nadia Hani, Abdullah, Shahino Mah

    Published 2025
    “…Hence, this research will be using Monte Carlo Simulation and identify which machine learning algorithm is suitable for predicting stock market patterns. …”
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    Book Section
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    Financial time series predicting using machine learning algorithms by Tiong, Leslie Ching Ow *

    Published 2013
    “…Thereafter, Artificial Neural Network (ANN) and Support Vector Machine (SVM) algorithms are implemented separately to train with the trend patterns for predicting the movement direction of financial trends. …”
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    Enhancing time series prediction with Hybrid AFSA-TCN: A unified approach to temporal data and optimization by Nur Alia Shahira, Mohd Zaidi, Zuriani, Mustaffa, Muhammad Arif, Mohamad

    Published 2025
    “…Time series data, with its sequential dependencies presents a unique challenge for traditional machine learning methods such as Random Forest (RF), Support Vector Machines (SVM), and Decision Trees (DT), which often struggle to capture temporal patterns effectively. …”
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    A Truly Online Learning Algorithm using Hybrid Fuzzy ARTMAP and Online Extreme Learning Machine for Pattern Classification by Wong S.Y., Yap K.S., Yap H.J., Tan S.C.

    Published 2023
    “…Algorithms; Benchmarking; E-learning; Knowledge acquisition; Learning systems; Pattern recognition; Bench-mark problems; Efficient learning; Extreme learning machine; Fuzzy ARTMAP; Generalization performance; Online learning; Online learning algorithms; Online sequential extreme learning machine; Learning algorithms…”
    Article
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    An algorithm for Elliott Waves pattern detection by Vantuch, T., Zelinka, I., Vasant, P.

    Published 2018
    “…The Random Decision Forest and the Support Vector Machine are the machine learning algorithms employed for this task. …”
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    An algorithm for Elliott Waves pattern detection by Vantuch, T., Zelinka, I., Vasant, P.

    Published 2018
    “…The Random Decision Forest and the Support Vector Machine are the machine learning algorithms employed for this task. …”
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    Article
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    A Review of Unsupervised Machine Learning Frameworks for Anomaly Detection in Industrial Applications by Usmani, U.A., Happonen, A., Watada, J.

    Published 2022
    “…Unsupervised learning, also known as unsupervised machine learning, analyzes and clusters unlabeled data utlizing machine learning techniques. …”
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    Article
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    Semiparametric inference procedure for the accelarated failure time model with interval-censored data by Karimi, Mostafa

    Published 2019
    “…A computationally simple two-step iterative algorithm, called estimationapproximation algorithm, is introduced for estimating the parameters of the model on the basis of the rank estimators. …”
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    Thesis
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    An empirical study of pattern leakage impact during data preprocessing on machine learning-based intrusion detection models reliability by Bouke, Mohamed Aly, Abdullah, Azizol

    Published 2023
    “…In this paper, we investigate the impact of pattern leakage during data preprocessing on the reliability of Machine Learning (ML) based intrusion detection systems (IDS). …”
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    Article
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    A New Probabilistic Output Constrained Optimization Extreme Learning Machine by Wong S.Y., Yap K.S., Li X.C.

    Published 2023
    “…Benchmarking; Classification (of information); Constrained optimization; Decision making; Electric power systems; Iterative methods; Knowledge acquisition; Learning algorithms; Pattern recognition; Probability; Confidence threshold; Decision making process; Extreme learning machine; Machine learning approaches; Pattern classification problems; Post-processing procedure; Power system applications; Probabilistic output; Machine learning…”
    Article