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    Prediction of Optimum Operating Parameters to Enhance the Performance of PEMFC Using Machine Learning Algorithms by Arunadevi M, Karthikeyan B, Anirudh Shrihari, Saravanan S, Sundararaju K, R Palanisamy, Mohamed Awad, Mohamed Metwally Mahmoud, Daniel Eutyche Mbadjoun Wapet, Abdulrahman Al Ayidh, Hany S. Hussein, Mahmoud M. Hussein, Ahmed I. Omar

    Published 2025-03-01
    “…Different MLAs are modelled to explore the PEMFC performance and results proved that gradient boosting regression provides better predictions compared to other algorithms such as decision tree regressor, support vector machine regressor, and random forest regression.…”
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  3. 43

    Leveraging mixed-effects regression trees for the analysis of high-dimensional longitudinal data to identify the low and high-risk subgroups: simulation study with application to g... by Mina Jahangiri, Anoshirvan Kazemnejad, Keith S. Goldfeld, Maryam S. Daneshpour, Mehdi Momen, Shayan Mostafaei, Davood Khalili, Mahdi Akbarzadeh

    Published 2025-03-01
    “…Previous studies have shown that this model can be sensitive to parametric assumptions and provides less predictive performance than non-parametric methods such as random effects-expectation maximization (RE-EM) and unbiased RE-EM regression tree algorithms. …”
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    Model Klasifikasi Machine Learning untuk Prediksi Ketepatan Penempatan Karir by Hendri Mahmud Nawawi, Agung Baitul Hikmah, Ali Mustopa, Ganda Wijaya

    Published 2024-03-01
    “…The complexity of the job market requires individuals and organizations to understand the trends and needs of the world of work. One of the main challenges is the right career placement. That is becoming increasingly popular is the use of Machine Learning  algorithms in the decision-making process. …”
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  6. 46

    WGAN-DL-IDS: An Efficient Framework for Intrusion Detection System Using WGAN, Random Forest, and Deep Learning Approaches by Shehla Gul, Sobia Arshad, Sanay Muhammad Umar Saeed, Adeel Akram, Muhammad Awais Azam

    Published 2024-12-01
    “…While applying learning techniques to intrusion detection, researchers are facing challenges mainly due to the imbalanced training sets and the high dimensionality of datasets, resulting from the scarcity of attack data and longer training periods, respectively. …”
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    Proposal for Using AI to Assess Clinical Data Integrity and Generate Metadata: Algorithm Development and Validation by Caroline Bönisch, Christian Schmidt, Dorothea Kesztyüs, Hans A Kestler, Tibor Kesztyüs

    Published 2025-06-01
    “…Logistic regression, k-nearest neighbors, a naive bayes classifier, a decision tree classifier, a random forest classifier, extreme gradient boosting (XGB), and support vector machines (SVM) were selected as machine learning algorithms. …”
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  9. 49

    Integrated transportation system planning with gravitational search algorithm approach based on fuzzy mutant controller by Alireza Hosseinzadeh Kashani, Seyed Ahmad Shayannia, Mohammad Mehdi Movahedi, Soheila Sardar

    Published 2025-03-01
    “…In these relations, <strong>3r </strong>is a uniform random variable in the interval [1,0], which is used to create the random property of the speed of the particle population optimization algorithm and the acceleration of the gravitational search algorithm in the gravitational particle population algorithm, and <strong>3C </strong>and <strong>4C</strong> are two constants to determine the degree of the speed of the particle population optimizer algorithm and the acceleration of the gravitational search algorithm in the gravitational particle population algorithm the values of which are considered 3C and 4C. …”
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    TS-SSA: An improved two-stage sparrow search algorithm for large-scale many-objective optimization problems. by Xiaozhi Du, Kai Chen, Hongyuan Du, Zongbin Qiao

    Published 2025-01-01
    “…Large-scale many-objective optimization problems (LSMaOPs) are a current research hotspot. However, since LSMaOPs involves a large number of variables and objectives, state-of-the-art methods face a huge search space, which is difficult to be explored comprehensively. …”
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