Topological search and gradient descent boosted Runge–Kutta optimiser with application to engineering design and feature selection by Jinge Shi, Yi Chen, Ali Asghar Heidari, Zhennao Cai, Huiling Chen, Guoxi Liang

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Capacity and Coverage Dimensioning for 5G Standalone Mixed-Cell Architecture: An Impact of Using Existing 4G Infrastructure by Naba Raj Khatiwoda, Babu Ram Dawadi, Sashidhar Ram Joshi

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A Hybrid P&O-Fuzzy-Based Maximum Power Point Tracking (MPPT) Algorithm for Photovoltaic Systems Under Partial Shading Conditions by Hamed Karimi, Alireza Siadatan, Afshin Rezaei-Zare

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A novel metaheuristic approach for simultaneous loss minimization and torque ripple reduction of DTC- IM driven EV by Anjan Kumar Sahoo

“…However, these methods have convergence issues at optimal values, require large memory spaces, have higher computational complexity, and are difficult to implement. …”
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An overview of distributed economic dispatch of microgrids: advances and challenges by Lei Sun, Wenjing An, Yangkai Chen, Peifeng Zhao, Derui Ding

“…DED) schemes are receiving more research attention because of their high reliability, scalability and uniformity in communication and computation loads. The latest theoretical advancements in DED algorithms are reviewed in this paper to give a comprehensive review. …”
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Research on error control method for polynomial approximation based on equal amplitude oscillation theorem by Letong Zhou, Liguo Zhao

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Distributionally robust microgrid formation for service restoration in distribution systems against extended extreme events by Ran Zhu, Hongzhe Liu, Wenwu Yu, Wei Gu, Jin Zhao

“…Furthermore, to enhance the computational efficiency, a parallel solving strategy is developed, based on the column-and-constraint generation algorithm, the alternating optimization procedure, and the progressive hedging algorithm. …”
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Double layered expansion planning for virtual power plants considering virtual energy storage systems by Jianghai Ma, Xuanwen Gu, Yao Zhang, Jinming Gu, Wenjie Luo, Feng Gao

“…To improve computational efficiency, a hybrid Grey Wolf Optimization algorithm is employed for model solution. …”
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Research on the Thrust Allocation Method for Straight-Line Sailing of Multiple AUVs in Tandem Connection by Jin Zhang, Shengfan Zhu, Shuai Kang

“…Third, to address the computational challenges of thrust allocation in large MATC systems, an offline model training method was introduced, combining the Harris Hawks Optimization (HHO) algorithm with a BP neural network. …”
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Mitigating Dead Node Impact on Coverage and Connectivity in Wireless Sensor Networks Using a Hybrid Approach by Omeed K. Khorsheed

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Optimal Design of Integrating Two‐Level Artificial Intelligent With Three Degrees of Freedom‐PDF (TLNF‐3DOFPDF) Controller for AGC of Three‐Area Multi‐Sources Power System... by Getaneh Mesfin Meseret, Rajesh Kumhar, Tarkesh Kumar Mahato, Nishant Kumar, Poonam Lakra, M. D. Mofeed Alam

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Deep-Learning Approach for an Analysis of Real-Estate Prices and Transactions by Cheng-Hong Yang, Borcy Lee, Yu-Da Lin

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Optimal sizing of diesel-electric hybrid powertrain for locomotive by ZHANG Chi, WU Jian, ZHANG Weige, ZHENG Xinjie, CHE Zhanghang, ZHU Zhenlin

“…Although the traditional bi-loop optimal sizing method can generate the optimal parameters, the dynamic programming algorithms used as the inner-loop to improve energy management strategy results in a long computation time. …”
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Unveiling quantum phase transitions from traps in variational quantum algorithms by Chenfeng Cao, Filippo Maria Gambetta, Ashley Montanaro, Raul A. Santos

“…Addressing these challenges, our work introduces a hybrid algorithm that combines quantum optimization with classical machine learning. …”
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Mathematical Modeling and Optimal Blank Generation in Glass Manufacturing by Raymond Phillips, Matthew Woolway, Dario Fanucchi, M. Montaz Ali

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Daily Runoff Prediction Model Based on Multivariate Variational Mode Decomposition and Correlation Reconstruction by DING Jie, TU Peng-fei, FENG Yu, ZENG Huai-en

“…[Conclusions](1) The MVMD decomposition method can control the number of decomposition layers, ensuring complete signal feature extraction without overfitting while improving processing speed.(2) Pearson correlation coefficient method enhances prediction accuracy through decomposed data classification.(3) The MEA-BP can improve signal-to-noise ratio, adapt to complex environments, enhance learning efficiency and generalization ability, and reduce computational complexity.(4) The GWO-ELM algorithm integrates grey wolf optimizer with extreme learning machine, providing a fast and adaptive solution for time-series prediction with reduced overfitting and improved efficiency.(5) The overall combined model can efficiently and stably process large amount of data while ensuring high accuracy.…”
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Parameter Adaptive Manta Ray Foraging Optimization for Global Continuous Optimization Problems and Parameter Estimation of Solar Photovoltaic Models by Zhentao Tang, Kaiyu Wang, Yongxuan Yao, Mingxin Zhu, Lan Zhuang, Huiqin Chen, Jing Li, Li Yan, Shangce Gao

“…Abstract The manta ray foraging optimization (MRFO) algorithm suffers from a fixed parameter $$ S $$ S , limiting its adaptability in balancing search capability and convergence speed during different optimization stages. …”
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Scientific Workflow-Based Synthesis of Optimal Microgrid Configurations by Olga Edeleva, Alexei Edelev, Mikhail Voskoboinikov, Alexander Feoktistov

“…In this context, we propose a framework and subject-oriented environment for the synthesis of optimal microgrid configurations in a reasonable time considering the available computational resources. …”
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A TOPSIS based multi-objective optimal deployment of solar PV and BESS units in power distribution system electric vehicles load demand by Vinod Kumar Thunuguntla, Vijayasanthi Maineni, Satish Kumar Injeti, Polamarasetty P Kumar, Ramakrishna S S Nuvvula, C Dhanamjayulu, Mostafizur Rahaman, Baseem Khan

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Efficient and secure multi-party computation protocol supporting deep learning by Shancheng Zhang, Gang Qu, Zongyang Zhang, Minzhe Huang, Haochun Jin, Liqun Yang

“…Moreover, we introduce optimized protocols for two crucial deep learning operations: convolution and Softmax function computation. …”
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