A dual time-scale optimal dispatch algorithm for PV systems: Integrating centralized optimal power dispatch with distributed power deviation absorption in DC smart grids by Jiahua Ni, Yuwei Chen, Arman Goudarzi, Tong Wang, Lingang Yang, Shengwei Mei

“…For short-term adjustments, a distributed consensus algorithm dynamically allocates power deviations among PV sources using reserve capacity, eliminating the need for probabilistic uncertainty modeling. …”
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Optimizing quantum convolutional neural network architectures for arbitrary data dimension by Changwon Lee, Israel F. Araujo, Dongha Kim, Junghan Lee, Siheon Park, Ju-Young Ryu, Ju-Young Ryu, Daniel K. Park, Daniel K. Park

“…., the number of features) of the input data that can be processed, restricting the applicability of QCNN algorithms to real-world data. To address this issue, we propose a QCNN architecture capable of handling arbitrary input data dimensions while optimizing the allocation of quantum resources such as ancillary qubits and quantum gates. …”
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Quantum-Inspired Hyperheuristic Framework for Solving Dynamic Multi-Objective Combinatorial Problems in Disaster Logistics by Kassem Danach, Hassan Harb, Louai Saker, Ali Raad

“…Disaster logistics presents a highly complex decision-making challenge under conditions of uncertainty, where the timely and efficient allocation of scarce resources is essential to minimize human suffering. …”
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Exploring the Role of Artificial Intelligence in Wastewater Treatment: A Dynamic Analysis of Emerging Research Trends by Javier De la Hoz-M, Edwan Anderson Ariza-Echeverri, Diego Vergara

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Research on elite hierarchical task offloading strategy based on reinforcement learning in edge-cloud collaboration scenario by Juan FANG, Zhiyuan YE, Mengyuan ZHANG, Jiamei SHI, Ziyi TENG

“…With the development of 5G and the enrichment of application functions, applications have put forward higher requirements on the computing capabilities of terminal devices.In order to improve the computing capabilities of terminal devices on applications and reduce the processing time of tasks, it is aimed at mobile edge computing environments, a task offloading method for edge-cloud collaboration was proposed，and an elite hierarchical evolutionary algorithm combined with reinforcement learning (RL-EHEA) was designed to perform offloading decisions, so that multiple tasks with dependencies and deadlines compete for computing resources.The simulation experiment results show that, compared with genetic algorithm (GA) and elite genetic algorithm (EGA), RL-EHEA can shorten task processing time and obtain better resource allocation strategy.…”
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Reinforcement Learning Solutions for Microgrid Control and Management: A Survey by Pedro I. N. Barbalho, Anderson L. Moraes, Vinicius A. Lacerda, Pedro H. A. Barra, Ricardo A. S. Fernandes, Denis V. Coury

“…It is an alternative to traditional algorithms and control methods in tasks, such as load frequency control, resource allocation, and energy management. …”
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A spherical fuzzy WASPAS approach to prioritize the factors enhancing the effectiveness of physical education classroom teaching by Yuhan Gao, Ali Yu

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Mitigating Dead Node Impact on Coverage and Connectivity in Wireless Sensor Networks Using a Hybrid Approach by Omeed K. Khorsheed

“…Previous research in the same context indicates the need for further investigation to achieve optimal trade-offs in network resource allocation. This research introduces a hybrid Artificial Bee Colony-Sequential Re-connectivity and Coverage Algorithm (ABC-SRCA) approach, combining the ABC algorithm with a developed SRCA. …”
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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

“…The latest theoretical advancements in DED algorithms are reviewed in this paper to give a comprehensive review. …”
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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

“…Abstract With the widespread integration of renewable energy sources, power systems increasingly require enhanced flexibility and economic efficiency. …”
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Interpretable Machine Learning for Multi-Energy Supply Station Revenue Forecasting: A SHAP-Driven Framework to Accelerate Urban Carbon Neutrality by Zhihui Zhao, Minjuan Wang, Jin Wei, Xiao Cen, Shengnan Du, Ziwen Wu, Huanying Liu, Weiqiang Wang

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Power Adaptation for Optimizing Secrecy Energy Efficiency in NOMA-Enabled Underlay Cognitive Radio Networks and DNN-Based Evaluation by P. P. Hema, A. V. Babu

“…The computation of the JOTPA for the SUs is enabled by an iterative algorithm that utilizes the Dinkelbach method. It is demonstrated that the suggested JOTPA scheme significantly enhances the SEE of the secondary network in comparison to the random transmit power allocation and equal transmit power allocation strategies. …”
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Pilot-Based Codebook Non-Orthogonal Artificial Noise Schemes for Physical Layer Security: Secrecy Capacity Optimization Under Unknown Eavesdropper Channels by Yi Zhang, Yebo Gu, Tao Zhao, Bo Wang

“…Considering the eavesdropper as an illegitimate user, whose channel state information matrix is unknown to the legitimate receiver and does not follow a simple distribution pattern, this study employs random matrix theory to model the channel of an unknown eavesdropper. It uses the successive convex approximation algorithm to analyze the optimal power allocation strategy and the maximum number of eavesdropper antennas that the system can tolerate under these conditions. …”
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Data Siting and Capacity Optimization of Photovoltaic–Storage–Charging Stations Considering Spatiotemporal Charging Demand by Dandan Hu, Doudou Yang, Zhi-Wei Liu

“…In the second stage, charging load results from the first stage, photovoltaic generation forecast, and electricity price are jointly considered to minimize the operator’s total cost determined by the capacity of PV and ESS, which is solved by the genetic algorithm. To validate the model, we leverage large-scale GPS trajectory data from electric taxis in Shenzhen as a data-driven source of spatiotemporal charging demand. …”
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Development and validation of a probability-assessment nomogram for non-suicidal self-injury in hospitalized adolescents and young adults with mental disorders by Qi Liu, Yanjuan Ren, Yalin Huang, Ruyi Xie, Yinyuan Li, Zaiquan Dong, Xiaoxia Zhang

“…This detective model can support the rational allocation of medical resources and facilitate the early detection and intervention of NSSI behaviors in hospitalized adolescents and young adults.…”
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Dynamic Workload Management System in the Public Sector: A Comparative Analysis by Konstantinos C. Giotopoulos, Dimitrios Michalopoulos, Gerasimos Vonitsanos, Dimitris Papadopoulos, Ioanna Giannoukou, Spyros Sioutas

“…This study addresses these challenges by optimizing load distribution through predicting employee capability using data-driven approaches, ensuring efficient resource utilization and enhanced productivity. Using a dataset encompassing public/private sector experience, educational history, and age, we evaluate the effectiveness of seven machine learning algorithms: Linear Regression, Artificial Neural Networks (ANNs), Adaptive Neuro-Fuzzy Inference System (ANFIS), Support Vector Machine (SVM), Gradient Boosting Machine (GBM), Bagged Decision Trees, and XGBoost in predicting employee capability and optimizing task allocation. …”
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Dynamic Optimization of Tunnel Construction Scheduling in a Reverse Construction Scenario by Jianying Wei, Yuming Liu, Xiaochun Lu, Rong Zhao, Gan Wang

“…The Mixed-Integer Programming (MIP) approach is used to build the mathematical model, solved with both exact algorithms and Genetic Algorithms (GA), and implemented in Python 3.12.7. …”
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Physical and mental health management for the older adult using XGBoost algorithm supported by new media technology: developing personalized health intervention plans using healthc... by Yutong Wang, Xin Guan, Shiyuan Qu, Jiarong Liao, Xin Ming, Enhui Li, Zixi Wang

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Generalized BER Performance Analysis for SIC-Based Uplink NOMA by Mahmoud AlaaEldin, Emad Alsusa, Mohammad Al-Jarrah, Karim G. Seddik, Michail Matthaiou

“…It is shown that these expressions are essential for designing optimal uplink power allocation (PA) strategies and mitigating SIC error floors, as evidenced by the proposed PA algorithm which achieves significant performance gains. …”
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An analytical framework for regional integration development in the Guangdong-Hong Kong-Macao Greater Bay Area urban agglomeration using fuzzy clustering by Manchang Du

“…Collaboration and resource allocation will be maximized through the CUD-FCA, creating a more integrated and cost-effective urban agglomeration. …”
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