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    Enhanced Success History Adaptive DE for Parameter Optimization of Photovoltaic Models by Yingjie Song, Daqing Wu, Ali Wagdy Mohamed, Xiangbing Zhou, Bin Zhang, Wu Deng

    Published 2021-01-01
    “…Comparison results demonstrate that the EBLSHADE is an effective and efficient method and the parameter optimization method is beneficial to design, control, and optimize the PV systems.…”
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  6. 1066

    IHDETBO: A Novel Optimization Method of Multi-Batch Subtasks Parallel-Hybrid Execution Cloud Service Composition for Cloud Manufacturing by Li-Nan Zhu, Peng-Hang Li, Xiao-Long Zhou

    Published 2019-01-01
    “…These candidate services will be selected and composed together to complete a complex manufacturing task. …”
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  7. 1067

    Application of Multiple-Population Genetic Algorithm in Optimizing the Train-Set Circulation Plan Problem by Yu Zhou, Leishan Zhou, Yun Wang, Zhuo Yang, Jiawei Wu

    Published 2017-01-01
    “…However, TCPP involves additional complexity due to the maintenance constraint of train-sets: train-sets must conduct maintenance tasks after running for a certain time and distance. …”
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    Improved Monarch Butterfly Optimization Algorithm Based on Opposition-Based Learning and Random Local Perturbation by Lin Sun, Suisui Chen, Jiucheng Xu, Yun Tian

    Published 2019-01-01
    “…By comparing the opposition-based population with the original population, the better individuals are selected and pass to the next generation, and then this process can efficiently prevent the MBO from falling into a local optimum. …”
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    Compressive Strength Prediction Using Coupled Deep Learning Model with Extreme Gradient Boosting Algorithm: Environmentally Friendly Concrete Incorporating Recycled Aggregate by Mayadah W. Falah, Sadaam Hadee Hussein, Mohammed Ayad Saad, Zainab Hasan Ali, Tan Huy Tran, Rania M. Ghoniem, Ahmed A. Ewees

    Published 2022-01-01
    “…Several statistical measures and graphical methods were generated to evaluate the efficiency of the presented models. In this regard, the results confirmed that the DLNN model attained the highest value of prediction performance with minimal root mean squared error (RMSE = 2.23). …”
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