Showing 141 - 160 results of 7,642 for search '(( improve most optimization algorithm ) OR ( improved model optimization algorithm ))', query time: 0.46s Refine Results
  1. 141

    Boosting feature selection efficiency with IMVO: Integrating MVO and mutation-based local search algorithms by Maryam Askari, Farid Khoshalhan, Hodjat Hamidi

    Published 2025-06-01
    “…In this research, we introduce the Improved Multi-Verse Optimizer (IMVO) algorithm, a novel feature selection method that integrates the Multi-Verse Optimizer (MVO) with local search algorithms (LSAs). …”
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    Article
  2. 142
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    Parameter Sensitivity Analysis and Algorithm Improvement of Optimization Scheduling Model for Cascade Pumping Stations by LIU Xiaolian, LI Zhenrong, WANG Xue-ni, ZHAI Yu, ZHANG Lei-ke, GUO Weiwei, TIAN Yu

    Published 2024-01-01
    “…ObjectiveThe low operating efficiency, massive energy consumption and large carbon emissions often exist in the operation of cascade pumping stations. To improve the operational efficiency of cascade pumping stations and vigorously promote dual carbon construction, an optimization scheduling model for cascade pumping stations was established with the goal of minimizing carbon emissions, and the Runge Kutta algorithm (RUN) was introduced to solve the model. …”
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  4. 144
  5. 145

    Modeling methylene blue removal using magnetic chitosan carboxymethyl cellulose multiwalled carbon nanotube composite with genetic algorithms and regression techniques by Mahmood Yousefi, Saeid Fallahizadeh, Yosra Maleki, Amir Sheikhmohammadi, Alieh Rezagholizade-shirvan

    Published 2025-07-01
    “…Abstract The purpose of this study was to model and optimize the removal of methylene blue using a novel magnetic chitosan-carboxymethyl cellulose/multiwalled carbon nanotubes and to identify the most significant parameters influencing the adsorption efficiency. …”
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    Article
  6. 146

    Simulation study on the urban-rural integration circulatory mechanism system in China: Based on system dynamics model and multi-objective genetic algorithm by Gaoyang Liang, Mingqiang Xing, Jianqiang Zhao

    Published 2025-12-01
    “…Additionally, multi-objective optimization solutions are proposed using a Multi-Objective Genetic Algorithm (MOP-GA), which suggest that a comprehensive development strategy that balances urban-rural resource allocation achieves the highest level of integration. …”
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    Article
  7. 147

    The calculation algorithm of oil and gas production enterprise energy efficiency indicators by A. Yu. Arestova, V. N. Ulyanov, M. Yu. Frolov

    Published 2022-04-01
    “…It allows creating an optimal schedule of organizational and technical measures to regulate energy consumption and improve the energy efficiency of the enterprise.…”
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  8. 148

    Improving air quality prediction using hybrid BPSO with BWAO for feature selection and hyperparameters optimization by Mohamed S. Sawah, Hela Elmannai, Alaa A. El-Bary, Kh. Lotfy, Osama E. Sheta

    Published 2025-04-01
    “…Feature selection (FS) was conducted using Binary version of Grey Wolf Optimizer (BGWO), Particle Swarm Optimization (BPSO), Whale Optimization Algorithm (BWAO), and a novel hybrid BPSO-BWAO approach to identify the most relevant features for AQI prediction. …”
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  9. 149

    A Two-echelon Model of Location-routing Problem for Optimizing Relief Operations in Natural Disasters by Hossein Jamali, Mehdi Kabiri Naeini, Zeynab Elahi

    Published 2025-09-01
    “…Conclusion The proposed model is an effective method to improve relief operations and strengthen crisis management during natural disasters.…”
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  10. 150

    Milling Machine Fault Diagnosis Using Acoustic Emission and Hybrid Deep Learning with Feature Optimization by Muhammad Umar, Muhammad Farooq Siddique, Niamat Ullah, Jong-Myon Kim

    Published 2024-11-01
    “…A convolutional neural network (CNN) based on the VGG16 architecture is utilized for spatial feature extraction, followed by a bidirectional long short-term memory (BiLSTM) network to capture the temporal dependencies of the scalograms. The genetic algorithm (GA) is used to optimize feature selection and ensure the selection of the most relevant features to further improve the model’s performance. …”
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  11. 151

    Optimizing Cancer Detection: Swarm Algorithms Combined with Deep Learning in Colon and Lung Cancer using Biomedical Images by HariKrishna Pathipati, Lova Naga Babu Ramisetti, Desidi Narsimha Reddy, Swetha Pesaru, Mashetty Balakrishna, Thota Anitha

    Published 2025-03-01
    “…Eventually, the whale optimization algorithm (WOA) is used to optimally choose the hyperparameters of the CNN‐BiGRU model. …”
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  12. 152

    Recent advancements in stereolithography (SLA) and their optimization of process parameters for sustainable manufacturing by Asmaul Husna, Salahuddin Ashrafi, ANM Amanullah Tomal, Noshin Tasnim Tuli, Adib Bin Rashid

    Published 2024-12-01
    “…Furthermore, the paper discusses the application of optimization methods like Genetic Algorithms and Artificial Neural Networks (ANN) to analyze, refine, and determine the optimal processing parameters for stereolithography. …”
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  13. 153

    An optimized proportional resonant current controller based genetic algorithm for enhancing shunt active power filter performance by Behnam Amini, Hasan Rastegar, Mohammad Pichan

    Published 2024-02-01
    “…Therefore, by performing accurate and optimal adjustments for APF control, system performance and power quality level can be improved significantly. …”
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    Enhancing patient rehabilitation outcomes: artificial intelligence-driven predictive modeling for home discharge in neurological and orthopedic conditions by Leonardo Buscarini, Paola Romano, Elena Sofia Cocco, Carlo Damiani, Sanaz Pournajaf, Marco Franceschini, Francesco Infarinato

    Published 2025-05-01
    “…This process involved variables recoding, scaling, and the evaluation of different dataset balancing methods to optimize model performance. Following a thorough review and comparison of algorithms commonly employed in the clinical-rehabilitative field, the Random Over Sampling (ROS) technique, in combination with the Random Forest (RF) machine learning model, was selected. …”
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