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  1. 1981

    Quantifying the impact of precision errors on quantum approximate optimization algorithms by Gregory Quiroz, Paraj Titum, Phillip Lotshaw, Pavel Lougovski, Kevin Schultz, Eugene Dumitrescu, Itay Hen

    Published 2025-06-01
    “…The quantum approximate optimization algorithm (QAOA) is a hybrid quantum-classical algorithm that seeks to achieve approximate solutions to optimization problems by iteratively alternating between intervals of controlled quantum evolution. …”
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    Article
  2. 1982

    Sustainable Mineral Processing Technologies Using Hybrid Intelligent Algorithms by Olga Shiryayeva, Batyrbek Suleimenov, Yelena Kulakova

    Published 2025-06-01
    “…The optimization is performed using a constrained Interior-Point algorithm. The model demonstrates high predictive accuracy, with a mean squared error (MSE) below 0.01. …”
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    Article
  3. 1983

    Application of the metaheuristic algorithms to quantify the GSI based on the RMR classification by Pouya Koureh Davoodi, Farnusch Hajizadeh, Mohammad Rezaei

    Published 2025-08-01
    “…This study addresses this challenge by analyzing data from fourteen different rock types and employing three metaheuristic optimization algorithms, namely Particle Swarm Optimization (PSO), Simulated Annealing (SA), and Grey Wolf Optimization (GWO), to develop predictive models for quantifying GSI based on the RMR. …”
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    Article
  4. 1984
  5. 1985
  6. 1986

    Predicting Affinity Through Homology (PATH): Interpretable binding affinity prediction with persistent homology. by Yuxi Long, Bruce R Donald

    Published 2025-06-01
    “…Compared to current binding affinity prediction algorithms, PATH+ shows similar or better accuracy and is more generalizable across orthogonal datasets. …”
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    Article
  7. 1987

    Benchmarking reinforcement learning and accurate modeling of ground source heat pump systems: Intelligent strategy using spiking recurrent neural network combined with spider WASP... by Sana Qaiyum, Kashif Irshad, Mohamed E. Zayed, Salem Algarni, Talal Alqahtani, Asif Irshad Khan

    Published 2025-09-01
    “…Consequently, Emperor Penguins Colony (EPC) optimization algorithm was also employed for selecting the essential features, which reduces the data dimensionality and assists the predictive algorithm to focus on important features in its training phase. …”
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    Article
  8. 1988
  9. 1989
  10. 1990
  11. 1991
  12. 1992
  13. 1993
  14. 1994
  15. 1995
  16. 1996

    Commodity Price Recognition and Simulation of Image Recognition Technology Based on the Nonlinear Dimensionality Reduction Method by Yongbin Liu, Jingjie Wang, Wei Bai

    Published 2021-01-01
    “…Although some traditional algorithms have achieved some results in the process of dimensionality reduction, they also expose their respective defects. …”
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    Article
  17. 1997
  18. 1998

    A simplified approach for efficiency analysis of machine learning algorithms by Muthuramalingam Sivakumar, Sudhaman Parthasarathy, Thiyagarajan Padmapriya

    Published 2024-11-01
    “…This article presents a comprehensive framework for evaluating ML algorithm efficiency by incorporating metrics, such as training time, prediction time, memory usage, and computational resource utilization. …”
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    Article
  19. 1999

    Advanced Deep Learning Algorithms for Energy Optimization of Smart Cities by Izabela Rojek, Dariusz Mikołajewski, Krzysztof Galas, Adrianna Piszcz

    Published 2025-01-01
    “…These algorithms analyze real-time data from sensors and IoT devices to predict energy demand, enabling dynamic load balancing and reducing waste. …”
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    Article
  20. 2000

    Modeling Analysis of the Relationship between Adolescent Aerobic Exercise and Obesity Reduction Based on Deep Learning by Peng Mu

    Published 2022-01-01
    “…In order to explore the modeling analysis of the relationship between adolescent aerobic exercise and obesity reduction, the relationship modeling method of deep learning algorithm is proposed. …”
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    Article