Showing 661 - 680 results of 3,188 for search '(( improve while optimization algorithm ) OR ( improve whole optimization algorithm ))', query time: 0.30s Refine Results
  1. 661

    Hybrid optimization technique for matrix chain multiplication using Strassen’s algorithm [version 2; peer review: 3 approved, 1 approved with reservations] by Srinivasarao Thota, Rakshitha T, Thulasi Bikku

    Published 2025-05-01
    “…By selectively applying Strassen’s method for large matrices, the proposed technique improves efficiency while preserving accuracy. Future work can focus on parallel computing and GPU acceleration for further optimization.…”
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    Article
  2. 662
  3. 663

    A fuzzy-optimized hybrid ensemble model for yield prediction in maize-soybean intercropping system by Amna Ikram, Sunnia Ikram, El-Sayed M. El-kenawy, El-Sayed M. El-kenawy, Adil Hussain, Amal H. Alharbi, Marwa M. Eid, Marwa M. Eid

    Published 2025-05-01
    “…This study proposes a Fuzzy-Optimized Hybrid Ensemble Model (FOHEM), integrating stacked ensemble machine learning algorithms with a fuzzy inference system (FIS) to improve yield prediction. …”
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    Article
  4. 664

    Maximizing efficiency and performance of water distribution systems through the implementation of optimization algorithms: A comprehensive analysis of valve and chlorine booster pl... by Mohamadreza Najarzadegan, Mehrtash Eskandaripour

    Published 2025-02-01
    “…By employing advanced optimization algorithms, specifically the Genetic Algorithm (GA) and Slime Mould Algorithm (SMA), the research identifies optimal configurations across two benchmark networks, Jowitt and Xu and GoYang. …”
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    Article
  5. 665

    GA4RF: An Effective Fall Detection System Through Optimizing Random Forest Hyperparameters Using Genetic Algorithm With Mobile Sensor Data by Ha-Nam Nguyen, Hong-Lam Le, Ngo-Thi-Thu-Trang, Duc-Nhan Nguyen

    Published 2025-01-01
    “…In this paper, we introduce a Genetic Algorithm (GA) based Random Forest (RF) method, named GA4RF, to enhance the accuracy of fall detection models by optimizing their hyperparameters. …”
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    Article
  6. 666

    Prediction of compressive strength of fiber-reinforced concrete containing silica (SiO2) based on metaheuristic optimization algorithms and machine learning techniques by Hamed Shokrnia, Ashkan KhodabandehLou, Peyman Hamidi, Fedra Ashrafzadeh

    Published 2025-06-01
    “…So, this study integrates the ANFIS (adaptive neuro-fuzzy inference system) and ELM (extreme learning machine) machine learning models with three optimization algorithms, i.e., WCA (water cycle algorithm), PSO (particle swarm optimization), and GWO (grey wolf optimizer) to precisely estimate the CS of fiber-reinforced concrete (FRC) containing SiO2. …”
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    Article
  7. 667

    Improving distributed systems failure prediction via multi-objective feature selection and deep forest by Zhidan Yuan, Yikai Zhang, Yingqi Yu, Taizhi Lv, Tao Huang

    Published 2025-01-01
    “…This optimization process is achieved through the NSGA-III algorithm. …”
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    Article
  8. 668
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  10. 670

    Enhanced Reinforcement Learning Algorithm Based-Transmission Parameter Selection for Optimization of Energy Consumption and Packet Delivery Ratio in LoRa Wireless Networks by Batyrbek Zholamanov, Askhat Bolatbek, Ahmet Saymbetov, Madiyar Nurgaliyev, Evan Yershov, Kymbat Kopbay, Sayat Orynbassar, Gulbakhar Dosymbetova, Ainur Kapparova, Nurzhigit Kuttybay, Nursultan Koshkarbay

    Published 2024-12-01
    “…One of the critical issues in the implementation of wireless networks is the selection of optimal transmission parameters to minimize EC while maximizing the packet delivery ratio (PDR). …”
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    Article
  11. 671
  12. 672

    A new stochastic multi-objective model for the optimal management of a PV/wind integrated energy system with demand response, P2G, and energy storage devices by Hossein Faramarzi, Navid Ghaffarzadeh, Farhad Shahnia

    Published 2025-07-01
    “…Optimal energy hub scheduling (EHS) has emerged as a promising strategy for improving the efficiency and flexibility of power systems. …”
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    Article
  13. 673
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    Exploring dynamical whole-brain models in high-dimensional parameter spaces. by Kevin J Wischnewski, Florian Jarre, Simon B Eickhoff, Oleksandr V Popovych

    Published 2025-01-01
    “…To enable the parameter optimizations for the high-dimensional model fitting to empirical data, we applied two dedicated mathematical optimization algorithms (Bayesian Optimization, Covariance Matrix Adaptation Evolution Strategy). …”
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    Article
  15. 675

    Assessing the quality of whole slide images in cytology from nuclei features by Paul Barthe, Romain Brixtel, Yann Caillot, Benoît Lemoine, Arnaud Renouf, Vianney Thurotte, Ouarda Beniken, Sébastien Bougleux, Olivier Lézoray

    Published 2025-04-01
    “…We strongly believe in the necessity of quality control from the algorithmic perspective and hope this kind of approach will be extended to improve quality and reliability of digital pathology whole slide images.…”
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    Article
  16. 676

    Optimizing Curriculum for Students: A Machine Learning Approach to Time Management Analysis by Jianmin Dong

    Published 2024-06-01
    “…Additionally, Tasmanian Devil Optimization (TDO) and Equilibrium Slime Mould Algorithm (ESMA) are integrated to enhance the accuracy of both XGBC and HGBC models. …”
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    Article
  17. 677

    Landslide Displacement Prediction Model Based on Optimal Decomposition and Deep Attention Mechanism by Shuai Ren, Kamarul Hawari Ghazali, Yuanfa Ji, Samra Urooj Khan

    Published 2025-01-01
    “…To address this, this study proposes an advanced forecasting framework integrating the Chebyshev Levy Flight-Sparrow Search Algorithm (CLF-SSA) with Variational Mode Decomposition (VMD) to enhance decomposition accuracy and optimize parameter selection. …”
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    Improving Surgical Site Infection Prediction Using Machine Learning: Addressing Challenges of Highly Imbalanced Data by Salha Al-Ahmari, Farrukh Nadeem

    Published 2025-02-01
    “…We also improved several resampling strategies, such as undersampling and oversampling. …”
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    Article