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  1. 1

    Machine learning models and dimensionality reduction for improving the Android malware detection by Pablo Morán, Antonio Robles-Gómez, Andres Duque, Llanos Tobarra, Rafael Pastor-Vargas

    Published 2024-12-01
    “…This work first proposes a new efficient dimensionality reduction of features, as well as the application of several supervised machine learning algorithms for prediction purposes. …”
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    Article
  2. 2

    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Saad Ahmed Dheyab, Shaymaa Mohammed Abdulameer, Salama Mostafa

    Published 2022-12-01
    “…The present study proposes an efficient DDoS attack detection model. This model relies mainly on dimensionality reduction and machine learning algorithms. …”
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    Article
  3. 3

    Physics-informed machine learning for automatic model reduction in chemical reaction networks by Joseph Pateras, Colin Zhang, Shriya Majumdar, Ayush Pal, Preetam Ghosh

    Published 2025-03-01
    “…Abstract Physics-informed machine learning bridges the gap between the high fidelity of mechanistic models and the adaptive insights of artificial intelligence. …”
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    Unsupervised Machine Learning Approaches for Test Suite Reduction by Anila Sebastian, Hira Naseem, Cagatay Catal

    Published 2024-12-01
    “…Over the past decade, machine learning-based solutions have emerged, demonstrating remarkable effectiveness and efficiency. …”
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    Refining Integration-by-Parts Reduction of Feynman Integrals with Machine Learning by Matt von Hippel, Matthias Wilhelm

    Published 2025-05-01
    “…In this paper, we investigate the use of machine-learning techniques to find improved heuristics. …”
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  11. 11

    Predicting practical reduction potential of electrolyte solvents via computational hydrogen electrode and interpretable machine-learning models by Zonglin Yi, Yi Zhou, Hao Liu, Li Li, Yan Zhao, Jiayuan Li, Yixuan Mao, Fangyuan Su, Cheng-Meng Chen

    Published 2025-05-01
    “…Machine-learning models are trained based on the organic and inorganic electrolyte solvents that possess experimentally identified reduction mechanisms. …”
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    Article
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    Machine learning model to predicting synergy of ultrasonication and solvation impacts on crude oil viscosity by Nasir Khan, Mehdi Razavifar, Qazi Adnan Ahmad, Muhammad Siyar, Masoud Riazi, Waqar Khan, Jafar Qajar

    Published 2025-08-01
    “…In the second part of the study, a Machine Learning (ML) model was developed using the experimental data. …”
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  14. 14

    Predicting the reduction in heatstroke and heart disease-related mortality under urban modification scenarios using machine learning by Yukitaka Ohashi, Ko Nakajima, Yuya Takane, Yukihiro Kikegawa, Tomohiko Ihara, Kazutaka Oka

    Published 2025-01-01
    “…This study proposes a novel approach combining machine learning (ML) techniques with meteorological model simulations to evaluate the heat-related mortality reduction potential of a climate change adaptation measure, namely, the installation of energy-saving or temperature-decreasing modifications in an urban area (e.g. greening, high-albedo paints, and photovoltaics). …”
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    Optimizing Concrete Mix Design for Cost and Carbon Reduction Using Machine Learning by Angga T. Yudhistira, Arief S. B. Nugroho, Iman Satyarno, Tantri N. Handayani, Malindu Sandanayake, Rimba Erlangga, Jonathan Lianto, Alfa Rosyid Ernanto

    Published 2025-06-01
    “…This study aims to create an optimal concrete mixture of cost and minimal carbon emissions, but the compressive strength meets the requirements. XGBoost Machine Learning Algorithm is used to make predictions, and PSO is used to obtain the optimal mixture. …”
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  19. 19

    Machine Learning Exploration of Experimental Conditions for Optimized Electrochemical CO2 Reduction by Vuri Ayu Setyowati, Shiho Mukaida, Kaito Nagita, Takashi Harada, Shuji Nakanishi, Kazuyuki Iwase

    Published 2024-12-01
    “…In this study, we investigated the impact of the electrode fabrication and electrolysis conditions on the product selectivity of Ag electrocatalysts using a machine learning (ML) approach. Specifically, we explored the experimental conditions for obtaining the desired H2/CO mixture ratio with high CO efficiency. …”
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  20. 20

    Impact of dimensionality reduction techniques on student performance prediction using machine learning by Koushik Roy, Huu-Hoa Nguyen, Dewan Md. Farid

    Published 2023-10-01
    “…The study evaluates ADRA using four different student performance datasets and six machine learning algorithms, comparing it to three existing dimensionality reduction methods. …”
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