Research on Day-Ahead Optimal Scheduling of Wind–PV–Thermal–Pumped Storage Based on the Improved Multi-Objective Jellyfish Search Algorithm by Yunfei Hu, Kefei Zhang, Sheng Liu, Zhong Wang

“…To address this issue, this study fully exploits the fast response and flexible operation of variable-speed pumped storage (VS-PS) by developing a day-ahead scheduling model for a wind–photovoltaic–thermal–VS-PS system. The optimization model aims to minimize system operating costs, carbon emissions, and thermal power output fluctuations, while maximizing the regulation flexibility of the VS-PS plant. …”
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Comprehensive Benefit Evaluation for Prefabricated Buildings Based on NSGA-II and Simulated Annealing Optimization Projection Pursuit Method by Fang Wang, Binbin Dai, Shiyu Song

“…Finally, the NSGA-II and simulated annealing algorithm optimization projection pursuit method are applied to solve and evaluate the comprehensive benefit model, obtaining the optimal prefabricated component solution with the best comprehensive benefits. …”
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Spectrum Sharing Design for Integrated Aeronautical Communication and Radar System by Lanchenhui Yu, Jingjing Zhao, Quan Zhou, Yanbo Zhu, Kaiquan Cai

“…An alternative optimization (AO) algorithm is proposed to solve the non-convex problem with highly coupled variables. …”
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Geographical Peer Matching for P2P Energy Sharing by Romaric Duvignau, Vincenzo Gulisano, Marina Papatriantafilou, Ralf Klasing

“…Our experimental study, based on real-world energy data, demonstrates that our proposed solutions are efficient both in terms of cost savings achieved by the peers and in terms of communication and computing requirements. Our scalable algorithms thus provide one core building block for practical and data-efficient peer-to-peer energy sharing communities within large-scale optimization systems.…”
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Coordinated Optimal Dispatch of Distribution Grids and P2P Energy Trading Markets by Jing Deng, Fawu He, Qingbin Zeng, Jie Yan, Rangxiong Liu, Dongsheng He, Song Zhou

“…This study proposes a bi‐level optimization framework for distribution networks integrating peer‐to‐peer (P2P) energy trading and shared energy storage. …”
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Synthesizing Sum and Difference Patterns with Low Complexity Feeding Network by Sharing Element Excitations by Jafar Ramadhan Mohammed

“…To achieve these two goals, an iterative fast Fourier transform (FFT) algorithm is used to synthesize sum and difference patterns with the main focus on obtaining a maximum allowable sharing percentage in the element excitations. …”
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A hybrid blockchain-based solution for secure sharing of electronic medical record data by Gang Han, Yan Ma, Zhongliang Zhang, Yuxin Wang

“…Additionally, our external sharing algorithm resolves the prevalent issue of medical data silos by facilitating better data categorization and enabling selective, secure external sharing through the social blockchain. …”
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Predicting Trip Duration and Distance in Bike-Sharing Systems Using Dynamic Time Warping by Ahmed Ali, Ahmad Salah, Mahmoud Bekhit, Ahmed Fathalla

“…Bike-sharing systems (BSSs) have recently become important in urban transportation due to several factors, such as their cost-effectiveness and environmental considerations. …”
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Robust QoT Assured Resource Allocation in Shared Backup Path Protection Based EONs by Venkatesh Chebolu, Sadananda Behera, Goutam Das

“…Next, we employ our SBPP-IA algorithm for dynamic traffic scenario and compare it with existing algorithms in terms of different QoT parameters. …”
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Artificial Intelligence-driven optimization of V2G and charging point selection en-route: A systematic literature review by Christoph Sommer, M.J. Hossain

“…Further investigation is warranted into the impact of high PV generation shares on charging behavoir and the optimization of charging strategies within the Australian context. …”
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Deep deterministic policy gradient-based automatic negotiation framework for shared decision-making by Xin Chen, Ping Lu, Yong Liu, Fei-Ping Hong

“…This study introduces AutoSDM-DDPG, an automated SDM framework based on the Deep Deterministic Policy Gradient (DDPG) algorithm. Using an Actor-Critic network, the framework dynamically optimizes negotiation strategies to address multidimensional demands and resolve preference inconsistencies in treatment planning. …”
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Navigating the landscape: Unveiling the reflection of AI in the sharing economy through bibliometric-based approach by Veljko Uskoković, Milica Maričić, Aleksandra Dacić-Pilčević, Veljko Jeremić

“…Furthermore, AI optimizes resource allocation and improves matching algorithms on online labour platforms, thereby boosting platform efficiency. …”
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Heterogeneous Multi-Agent Deep Reinforcement Learning for Cluster-Based Spectrum Sharing in UAV Swarms by Xiaomin Liao, Yulai Wang, Yang Han, You Li, Chushan Lin, Xuan Zhu

“…However, due to the scarcity of spectrum resources, UAV swarm clustering technology has emerged as an effective method for achieving spectrum sharing among UAV swarms. This paper introduces a distributed heterogeneous multi-agent deep reinforcement learning algorithm, named HMDRL-UC, which is specifically designed to address the cluster-based spectrum sharing problem in heterogeneous UAV swarms. …”
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A Long-Term Shared Autonomous Vehicle System Design Problem considering Relocation and Pricing by Jingjing Tian, Hongfei Jia, Guanfeng Wang, Yu Lin, Ruiyi Wu, Ao Lv

“…Then, we integrate the Particle Swarm Optimization (PSO) algorithm with the optimization solver Gurobi to address the complex problem. …”
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Joint Allocation of Shared Yard Space and Internal Trucks in Sea–Rail Intermodal Container Terminals by Xiaohan Wang, Zhihong Jin, Jia Luo

“…Numerical experiments verify the model and algorithm performance, revealing that the proposed method achieves an optimality gap of only 1.82% compared to CPLEX in small-scale instances while outperforming benchmark algorithms in solution quality. …”
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A Distribution Model for Shared Parking in Residential Zones that Considers the Utilization Rate and the Walking Distance by Wenhui Zhang, Fan Gao, Shurui Sun, Qiuying Yu, Jinjun Tang, Bohang Liu

“…The particle swarm optimization (PSO) algorithm is used to solve this model. …”
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Game-based resource allocation in heterogeneous downlink CR-NOMA network without subchannel sharing by Deepa Das, Rajendra Kumar Khadanga, Deepak Kumar Rout, Md. Minarul Islam, Taha Selim Ustun

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Client grouping and time-sharing scheduling for asynchronous federated learning in heterogeneous edge computing environment by Qianpiao MA, Qingmin JIA, Jianchun LIU, Hongli XU, Renchao XIE, Tao HUANG

“…., edge heterogeneity, data Non-IID, and communication resource constraints, a grouping asynchronous federated learning (FedGA) mechanism was proposed.Edge nodes were divided into multiple groups, each of which performed global updated asynchronously with the global model, while edge nodes within a group communicate with the parameter server through time-sharing communication.Theoretical analysis established a quantitative relationship between the convergence bound of FedGA and the data distribution among the groups.A time-sharing scheduling magic mirror method (MMM) was proposed to optimize the completion time of a single round of model updating within a group.Based on both the theoretical analysis for FedGA and MMM, an effective grouping algorithm was designed for minimizing the overall training completion time.Experimental results demonstrate that the proposed FedGA and MMM can reduce model training time by 30.1%～87.4% compared to the existing state-of-the-art methods.…”
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An Adaptive Wireless Droop Control with Adaptive Virtual Resistance for Power Sharing Management in MTDC Grid by Hasan Alrajhi , Ahmed Al-Zahrani , Syed A. Raza , Fahad Al-Shareef 

“…The main objective of this methodology is to increase the reliability of the MTDC system by eliminating the need for fast communication links and ensuring proper power sharing between inverters. Additionally, this communication-free scheme includes a power management algorithm that controls power sharing during peak hours of the inverters among the rectifiers as per mutual agreements between the operators to mitigate the risk of a system overload and optimize the power sharing. …”
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Development of A Novel Discharge Routing Method Based On the Large Discharge Dataset, Muskingum Model, Optimization Methods, and Multi-Criteria Decision Making by Mahdi Valikhan Anaraki, Saeed Farzin, Iman Ahmadianfar, Amin Shams

“…Different MOAs, including a Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Firefly Algorithm (FFA), Cuckoo Search (CS), Bat Algorithm (BA), Shark Smell Optimization (SSO), Whale Optimization Algorithm (WOA), Harris Hawk''s Optimization (HHO), and hybrid of WOA and CS (WOA_CS), were developed for Muskingum calibration. …”
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