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  1. 1881

    Optimal energy management for multi-energy microgrids using hybrid solutions to address renewable energy source uncertainty by M. Siva Ramkumar, Jaganathan Subramani, M. Sivaramkrishnan, Arunkumar Munimathan, Goh Kah Ong Michael, Mohammad Mukhtar Alam

    Published 2025-03-01
    “…In this study, a new hybrid algorithm is used for system modelling and low-cost, optimal management of Micro Grid (MG) networked systems. …”
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    Article
  2. 1882

    Robust techno-economic optimization of energy hubs under uncertainty using active learning with artificial neural networks by Aya M. A. Heikal, Shady H. E. Abdel Aleem, Ragab A. El-Sehiemy, Almoataz Y. Abdelaziz

    Published 2025-07-01
    “…Results demonstrate significant improvements in system reliability, cost efficiency, and flexible operation, validating the effectiveness of ANN-based AL to optimize EHs management and ensure sustainable operation complexities. …”
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    Article
  3. 1883

    Construction of Clinical Predictive Models for Heart Failure Detection Using Six Different Machine Learning Algorithms: Identification of Key Clinical Prognostic Features by Qu FZ, Ding J, An XF, Peng R, He N, Liu S, Jiang X

    Published 2024-12-01
    “…Following the elimination of features with significant missing values, the remaining features were utilized to construct predictive models employing six machine learning algorithms. The optimal model was selected based on various performance metrics, including the area under the curve (AUC), accuracy, precision, recall, and F1 score. …”
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  4. 1884

    Optimizing Location of Car-Sharing Stations Based on Potential Travel Demand and Present Operation Characteristics: The Case of Chengdu by Yu Cheng, Xu Chen, Xiaohua Ding, Linting Zeng

    Published 2019-01-01
    “…This study aims to use different data source with statistical models and machine learning algorithm to help car-sharing operator to choose the optimal location of new stations and adjust the location of existing stations. …”
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    Article
  5. 1885

    Peak Arm Current Reduction of Modular Multilevel Converter Based on Particle Swarm Optimizer for Circulating Current Injections by Riyadh Toman Thahab, Tahani Hamodi Al-Mhana

    Published 2025-01-01
    “…This paper uses a particle swarm optimisation (PSO) algorithm to determine the optimal values for the injected components. …”
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    Article
  6. 1886

    Multi-Objective Optimization Methods for University Campus Planning and Design—A Case Study of Dalian University of Technology by Lin Qi, Chaoran Chen, Jun Dong

    Published 2025-07-01
    “…This study focuses on the multi-objective coordination problem in university campus planning and design, proposing an optimized methodology integrating an improved multi-objective decision-making framework. …”
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  7. 1887

    A Wi-Fi Indoor Localization Strategy Using Particle Swarm Optimization Based Artificial Neural Networks by Nan Li, Jiabin Chen, Yan Yuan, Xiaochun Tian, Yongqiang Han, Mingzhe Xia

    Published 2016-03-01
    “…In this paper, we propose an indoor localization system using the affinity propagation (AP) clustering algorithm and the particle swarm optimization based artificial neural network (PSO-ANN). …”
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  8. 1888

    An Efficient Mutual Authentication and Fractional Lyrebird Optimization With Deep Learning–Based SIP-Based DRDoS Attack Detection by V. Sreenivasulu, C. V. Ravikumar

    Published 2025-01-01
    “…The detection performance of DSA is increased by training using the fractional lyrebird optimization algorithm (FLOA); FLOA provides a more effective, reliable, and scalable optimization strategy for training DSAs than traditional algorithms. …”
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    Article
  9. 1889

    Distributionally robust optimal scheduling of flexible distribution networks considering dynamic spatio-temporal correlation of renewable energy by Shunxiang Yu, Xiaoming Dong, Chengfu Wang, Tianguang Lu

    Published 2025-08-01
    “…By utilizing the 1-norm and ∞-norm to characterize the uncertainty sets between sources and loads, this strategy effectively minimizes operational costs while ensuring robust performance. The proposed model is linearized and relaxed through second-order cone programming and solved using the column and constraint generation (C&CG) algorithm. …”
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    Article
  10. 1890

    Determination of Sequential Well Placements Using a Multi-Modal Convolutional Neural Network Integrated with Evolutionary Optimization by Seoyoon Kwon, Minsoo Ji, Min Kim, Juliana Y. Leung, Baehyun Min

    Published 2024-12-01
    “…This complex multi-million-dollar problem involves optimizing multiple parameters using computationally intensive reservoir simulations, often employing advanced algorithms such as optimization algorithms and machine/deep learning techniques to find near-optimal solutions efficiently while accounting for uncertainties and risks. …”
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    Article
  11. 1891
  12. 1892

    Neural network inspired efficient scalable task scheduling for cloud infrastructure by Punit Gupta, Arnaav Anand, Pratyush Agarwal, Gavin McArdle

    Published 2024-01-01
    “…In this work, we aim to use the Harmony Search Algorithm and neural networks to create a fault aware system for optimal usage of cloud resources. …”
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    Article
  13. 1893

    On the Use of Azimuth Cutoff for Sea Surface Wind Speed Retrieval From SAR by Yuting Zhu, Giuseppe Grieco, Jiarong Lin, Marcos Portabella, Xiaoqing Wang

    Published 2024-01-01
    “…The methodology probabilistically combines SAR data with ancillary meteorological information and optimizes the retrieval process through a cost function that leverages the sensitivity of the azimuth cutoff to changes in wind vector fields. …”
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    Article
  14. 1894

    Process parameter optimization of laser beam machining for AISI -P20 mold steel using ANFIS method by Abdullah Eaysin, Sarower Kabir, Ebru Gunister, Nur Jahan, Amir Hamza, Muhammad Ali Zinnah, Adib Bin Rashid

    Published 2025-01-01
    “…The ANFIS model, developed and analyzed using MATLAB, successfully predicted response parameters and was experimentally validated, showing improved predictions over actual measurements. The Brute Force algorithm identified the minimum combination for an optimal parameter set. …”
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    Article
  15. 1895
  16. 1896

    Enhancing the prediction of groundwater quality index in semi-arid regions using a novel ANN-based hybrid arctic puffin-hippopotamus optimization model by Moustafa Gamal Snousy, Hussein M. Elshafie, Ashraf R. Abouelmagd, Najmaldin Ezaldin Hassan, Mahmoud E. Abd-Elmaboud, Ali Akbar Mohammadi, Ashraf M.T. Elewa, E. EL-Sayed, Ahmed M. Saqr

    Published 2025-06-01
    “…Study focus: This study presents a novel hybrid arctic puffin–hippopotamus optimization (HPHO) algorithm combined with an artificial neural network (ANN) to improve irrigation water quality index (IWQI) predictions in semi-arid areas. …”
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  17. 1897

    DAB unified ZVS control strategy with optimal current stress in full power range under TPS control by Shuai Cheng, Fusheng Wang, Zongfeng Han, Chuanqi Zhang

    Published 2024-11-01
    “…Based on three‐phase shift control, Karush–Kuhn–Tucker (KKT) algorithm is used to solve the optimal control strategy of current stress under soft switching conditions, and the interval construction method that KKT cannot solve is given. …”
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  18. 1898
  19. 1899

    Optimal sleep time controller based on traffic prediction and residual energy in duty-cycled wireless sensor networks by Haibo Luo, Minghua He, Zhiqiang Ruan, Xiaxia Zeng

    Published 2017-12-01
    “…In duty-cycled wireless sensor networks, energy efficiency and packet latency are two most important metrics in the design of medium access control and routing algorithms. …”
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  20. 1900

    Intelligent Optimized Combined Model Based on GARCH and SVM for Forecasting Electricity Price of New South Wales, Australia by Yi Yang, Yao Dong, Yanhua Chen, Caihong Li

    Published 2014-01-01
    “…In this paper, we propose an optimized combined forecasting model by ant colony optimization algorithm (ACO) based on the generalized autoregressive conditional heteroskedasticity (GARCH) model and support vector machine (SVM) to improve the forecasting accuracy. …”
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