Search Results - (( parameter evaluation method algorithm ) OR ( variable deep learning algorithm ))

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    Enhancing wind power forecasting accuracy with hybrid deep learning and teaching-learning-based optimization by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

    Published 2024
    “…This paper presents an innovative approach that combines deep learning (DL) with Teaching-Learning-Based Optimization (TLBO) to predict wind power output accurately. …”
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    Article
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    Predicting mortality of Malaysian patients with acute coronary syndrome (ACS) subtypes using machine learning and deep learning approaches / Muhammad Firdaus Aziz by Muhammad Firdaus , Aziz

    Published 2022
    “…The purpose of this study is to use machine learning (ML) and deep learning (DL) algorithms to predict and identify variables linked to short and long-term mortality in Asian STEMI and NSTEMI/UA patients and to compare these results to a conventional risk score. …”
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    Recent Automatic Segmentation Algorithms of MRI Prostate Regions: A Review by Khan, Z., Yahya, N., Alsaih, K., Al-Hiyali, M.I., Meriaudeau, F.

    Published 2021
    “…This survey reviewed 22 machine learning and 88 deep learning-based segmentation of prostate MRI papers, including all MRI modalities. …”
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    Recent Automatic Segmentation Algorithms of MRI Prostate Regions: A Review by Khan, Z., Yahya, N., Alsaih, K., Al-Hiyali, M.I., Meriaudeau, F.

    Published 2021
    “…This survey reviewed 22 machine learning and 88 deep learning-based segmentation of prostate MRI papers, including all MRI modalities. …”
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    Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Rahman S.A., Jang G., Mahlia T.M.I.

    Published 2025
    “…To address these problems, this paper introduces a novel hybrid approach for RUL prediction, combining a Lightning Search Algorithm (LSA) with a Long-Short Term Memory (LSTM) deep learning model. …”
    Article
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    A stacked ensemble deep learning model for water quality prediction / Wong Wen Yee by Wong , Wen Yee

    Published 2023
    “…The proposed deep learning model renders faster without the use of SMOTE. …”
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    Forecasting and Trading of the Stable Cryptocurrencies With Machine Learning and Deep Learning Algorithms for Market Conditions by Shamshad, H., Ullah, F., Ullah, A., Kebande, V.R., Ullah, S., Al-Dhaqm, A.

    Published 2023
    “…Thus, this proposed system employs a data science-based framework and six highly advanced data-driven Machine learning and Deep learning algorithms: Support Vector Regressor, Auto-Regressive Integrated Moving Average (ARIMA), Facebook Prophet, Unidirectional LSTM, Bidirectional LSTM, Stacked LSTM. …”
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    A review on deep learning approaches to forecasting the changes of sea level by Nosius Luaran, Rayner Alfred, Joe Henry Obit, Chin Kim On

    Published 2021
    “…The present paper aims to review several Deep Learning (DL) algorithms that address critical issues of forecasting, specifically a time variable known as time series by managing complex patterns and inefficiently capturing long-term multivariate data dependency. …”
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    Ensemble-based machine learning algorithms for classifying breast tissue based on electrical impedance spectroscopy by Rahman, Sam Matiur, Ali, Md. Asraf, Altwijri, Omar, Alqahtani, Mahdi, Ahmed, Nasim, Ahamed, Nizam Uddin

    Published 2020
    “…In addition, the ranked order of the variables based on their importance differed across the ML algorithms. …”
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    A deep learning approach for facial detection in targeted billboard advertising / Lau Sian En by Lau , Sian En

    Published 2025
    “…This system utilises sophisticated deep learning algorithm using Convolutional Neural Network (CNN) to identify and examine human faces, enabling advertisers to customise their content according to demographic variables including age and gender. …”
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    Multi-label risk diabetes complication prediction model using deep neural network with multi-channel weighted dropout by Dzakiyullah, Nur Rachman

    Published 2025
    “…Seven machine learning models—Artificial Neural Network (ANN), Random Forest (RF), Decision Tree (DTT), k-Nearest Neighbors (k-NN), Naïve Bayes (NB), Support Vector Machine (SVM), and Deep Neural Network (DNN)—were used for multi-label classification of the complications. …”
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    Automated model selection for corporation credit risk assessment using machine learning / Zulkifli Halim by Halim, Zulkifli

    Published 2023
    “…The global trend in the CCRA study shows that implementing machine learning and deep learning techniques is expanding rapidly. …”
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